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Long Distance Transportation Patterns: Mode Choice

Americans total 1.3 trillion person-miles of long distance travel a year on about 2.6 billion long-distance trips. Long-distance trips are journeys of more than 50 miles from home to the furthest destination. More than half of long-distance trips are taken for pleasure, while fewer than one out of five long-distance trips is for business. While most long-distance trips are made by personal vehicle, the National Household Travel Survey (NHTS), conducted in 2001 and 2002, explored the choices that travelers make for their long-distance travel.

Among the key findings are:

• Long-distance trips originating in urban and metropolitan areas are more likely to use public transportation modes than trips originating in rural and non-metro areas.
• About 8 percent of long-distance trips that use a public transportation mode [ 1 ] use a different mode in each direction of travel.
• Almost 90 percent of long-distance trips are by personal vehicle.
• Mode choice varies somewhat by trip purpose and distance.
• Personal vehicle is the most frequent mode used to initially access long distance public transportation, but on the arrival end a greater mix of modes is used.

A more detailed discussion of these findings follows.

Long Distance Travel Mode

Based on the 20012002 NHTS data, Americans take 2.6 billion long-distance trips per year, or 7.2 million trips per day. Almost 9 out of 10 long-distance trips are taken by personal vehicle, [ 2 ] and about 10 percent use public transportation modes. Over 7 percent of long-distance trips are taken by air, while 2 percent are by bus (including scheduled, charter, and other bus trips). Train travel represents almost 1 percent of long-distance trips. Table 1 in the Appendix shows the breakdown by mode.

Mode by Trip Purpose

More than half of long-distance trips (56 percent) are taken for pleasure, 16 percent for business, 13 percent each for commuting and for personal business, [ 3 ] and 3 percent for other reasons. Regardless of trip purpose, driving is the primary travel mode, accounting for 89 percent of all trips. Contrary to the popular vision of business travelers flying off to their meetings, nearly 80 percent of all business trips are done by driving. Personal vehicle travel accounts for 96 percent of commuting trips and about 90 percent of pleasure and personal business trips. Air travel accounts for only 18 percent of business trips, overall. About 7 percent of pleasure trips are by plane, and air accounts for only about 5 percent of personal business trips. Rail travel accounts for about 2 percent of all business trips and commute trips, but less than 1 percent of pleasure trips.

While personal vehicle and air are the primary and secondary modes for all other trip categories, bus is as important as air as the secondary mode for personal business trips. [ 4 ] Table 2 in the Appendix shows the modal breakdown of long-distance trips by trip purpose. Figure 1 (and table 3 in the Appendix) shows the modal breakdown by purpose for trips made by public transportation modes (personal vehicle trips excluded).

Mode by Trip Distance

Mode choice changes with trip distance. Trips of 50 to 499 miles, each way, account for 90 percent of long-distance trips. About 5 percent of long-distance trips are to destinations 500 to 999 miles away, and another 5 percent are 1,000 miles or longer. At shorter distances most trips are by personal vehicle, but the percentage of trips taken by public transportation increases with trip distance. For trips of less than 250 miles, 97 percent of trips are by personal vehicle, but once the trip distance is 750 miles or greater, travelers are more likely to use one of the public transportation modes.

At distances of 1,500 miles or more, only 15 percent of trips are by driving, with the large majority of trips (82 percent) being by air. Figure 2 shows how as trip distances increase, personal vehicle is replaced by air as the primary transportation mode. Because the share of trips using any of the other public transportation modes (bus, rail, and other) never exceeds 3.3 percent, and in many cases the sample is too small to be reliable, they are not shown on figure 2. Table 4 in the Appendix gives detailed information for all modes.

Mode Choice for International Trips

It is not surprising that U.S. residents choice between the two primary modes (air and personal vehicle) is much different for international trips than it is for domestic trips. Slightly more than half of international trips are by air, compared to only about 7 percent of domestic trips. Virtually all international trips to destinations outside of North America are by air. Within North America, about 86 percent of Caribbean trips are by air, and 29 percent of trips to both Canada and Mexico are by plane.

Personal vehicle, which accounts for over 90 percent of domestic trips, still accounts for 42 percent of international trips due to the volume of driving trips to Mexico and Canada. Those two countries account for 65 percent of international trips; driving accounts for about two-thirds of the trips to both of those countries.

Appendix table 5 compares mode choice for international and domestic trips. Table 6 shows mode choice for international trips by various destination areas of the world. The sample size for bus, train, and other modes is too small to be reliable.

Trips Using Different Modes in Opposite Directions

Not all travelers use the same mode for their going and return trips. About 8 percent of long-distance trips that involve travel on one of the public transportation modes will be made using a different transportation mode in the opposite direction. Among public transportation users, air and bus travelers are least likely to use a combination of modes, with only about 6 percent of air travelers and 10 percent of bus travelers using a second mode in the opposite direction. [ 5 ] About 17 percent of rail trips use a different mode in the other direction, although there is not a statistically significant difference between the percentage of bus, train, or other [ 6 ] trips that are likely to use a different mode in each direction. The sample size in the NHTS for the other modes is not large enough to provide a reliable estimate. Personal vehicle is the second mode of transportation for 79 percent of the multiple-mode long distance public transportation trips. Twenty-one percent of multiple-mode public transportation trips use another public mode in the opposite travel direction.

Because personal vehicles are used for 90 percent of all long-distance trips, multiple-mode trips represent a considerably lower percentage of personal vehicle trips than for the public transportation modes. Less than 1 percent of long distance personal vehicle trips use a different mode in the opposite travel direction.

Table 7 of the Appendix shows for each mode the percentage of trips that use the same mode and the percentage of trips that use a different mode in the opposite directions. Table 8 shows the percent of trips in the opposite direction that are via personal vehicle, for trips that use a public transportation mode in at least one direction. Table 9 shows the detail of return mode usage by going mode for all trips.

Mode Choice by Geography

There is a difference in intercity travel mode choice depending on where the traveler resides. While all groups rely predominantly on personal vehicles, those who live in urban areas are more likely than those who live in rural areas to use public transportation for their long-distance trips.

While the personal vehicle is the predominant mode for all travelers, those who live in rural areas use it for 95 percent of long-distance trips, while the personal vehicle is used for only 87 percent of trips originating in urban areas. Nine percent of long-distance trips originating in urban areas are made by air compared to only 3 percent by air from rural areas. Similarly, 1 percent use rail from urban areas, compared to about one-half of 1 percent in rural areas. There is no statistically significant difference between the use of bus in rural or urban areas, with about 2 percent of trips from both rural and urban households using that mode. Table 10 shows the urban/rural breakdown by mode.

Mode choice varies even between metropolitan areas of different size. Those living in Metropolitan Statistical Areas (MSAs) of 1 million or more population are more likely to use public transportation modes for long-distance trips than those who live in smaller metro areas. Those living in the smaller metro areas in turn use public transportation for a higher percentage of long-distance trips than those living outside of metropolitan areas. For example, in MSAs of more than 1 million residents, 85 percent of long-distance trips are made by driving and 15 percent are made using public transportation. In MSAs of less than 1 million, the percent of trips made by personal vehicle increases to 92 percent with the percent made by public modes dropping to 8 percent. Outside of metro areas, 96 percent of long-distance trips are made by personal vehicle, with only 4 percent using public modes. See table 11 in the Appendix for a breakdown of personal vehicle and public transportation long-distance trips by the MSA size.

Demographics and Mode Choice

Across all age groups, the personal vehicle accounts for about 90 percent of long-distance trips. The remaining 10 percent of long-distance trips are made via public transportation modes. Air service is the most frequently used public mode for long-distance trips by all age groups except those age 65 and above.

Among that age group there is no statistical difference between the percentage of trips made by air and the percentage made by bus.

Mode choice by age group is shown in Appendix table 12 .

While driving is the dominant mode across all income levels, household income has an influence, especially at the upper and lower levels, on mode choice. While personal vehicle is the dominant mode for all long-distance travel, the percentage of trips made by driving declines noticeably for those with incomes over $75,000 annually. Below that income level, more than 91 percent of long-distance trips are made by driving, but that figure drops to 84 percent for those in the highest income group. At the same time, those with incomes in excess of $75,000 make nearly 14 percent of their long-distance trips by air, compared to only three to 5 percent of trips by those below that income level.

Those with household incomes below $25,000, on the other hand, are more likely to make trips by bus than those at the higher income levels. Almost 4 percent of long-distance trips are made by bus among those making less than $25,000; but that share declines to less than 2 percent for those in the highest income bracket. There is no difference across income levels in the percentage of long-distance trips made by train.

Income breakdown by mode for long-distance trips is shown in Appendix table 13 .

Access and Egress Modes

Auto travel is generally door-to-door. However, those using public transportation modes for long-distance trips must get from the starting point to the intercity transportation terminal to board the public transportation mode. Similarly, at the destination, public transportation travelers need to get from the intercity transportation terminal to their actual destination location. The trips to access and egress the main transportation mode are examined in this section of the report.

The most frequent access mode used at the originating end of the trip is the personal vehicle, accounting for 71 percent of trips to access public long-distance transportation. Three out of four air trips begin by either driving or being driven to the airport, while 66 and 54 percent of bus and train trips, respectively, begin with access being provided by personal vehicle.

Public transportation is used by 15 percent of those needing to access a long-distance transportation terminal, and 10 percent use a combination of more than one mode to get from their origin point to the terminal. Overall, about 3 percent walk or bike to the terminal. However, bicycle and pedestrian access is used to access nearly 13 percent of long-distance train trips and over 10 percent of long-distance bus trips. Appendix table 14 shows how travelers access intercity transportation.

The significant use of local public transportation to access intercity modes (non-personal vehicle) is a phenomenon of the large metropolitan areas. In MSAs of more than 1 million population, where there are generally extensive public transit networks, about 18 percent of those accessing an airport, bus, or rail station use public transportation. This compares to less than 10 percent access by public transportation in MSAs of less than 1 million population, and non-MSA areas. Table 15 shows the access mode by MSA size.

At the arrival end of the trip, travelers use a greater mix of modes to egress from the intercity terminal to the final destination than they use for access. Personal vehicle is the primary egress mode only for those arriving by air. About two-thirds of arriving air travelers leave the airport via personal vehicle. Personal vehicle includes rental cars. Personal vehicle does not include taxicabs, which are counted in the other mode category. About one-fourth of air passengers use local public transport to egress from the destination terminal. Rail passengers are just as likely to get to their destination by walking, using local transport, using a personal vehicle, or taking a combination of more than one egress mode. Intercity bus travelers are most likely to walk or bike to their destination (44 percent) or use public transportation (33 percent). Table 16 shows how long-distance travelers get from their arrival terminal to their final destination.

While the access mode seems to be influenced by MSA size on the originating end of the trip, the arrival MSA size does not seem to have as great of an influence on egress mode. Regardless of MSA size, about half of trips are completed in personal vehicles, about one-fourth by public transit, 10 to 15 percent by walking or cycling, and about 10 percent by a combination of two or more modes. Table 17 shows egress modes by MSA size.

Methodology Notes

This analysis is based on the national sample long-distance trip file of the National Household Travel Survey. Long-distance trips are defined as those where the destination is at least 50 miles away from the originating point.

The modal analyses in this report use only trips where transportation mode information is available. Trip records are not considered if mode choice is unknown or if mode choice was not provided by a survey respondent. Less than one-half of 1 percent of the 2.6 billion weighted long-distance trips were eliminated due to the lack of mode information.

Public Transportation refers to all modes except Personal Vehicle. Public Transportation modes are air, bus (both scheduled and charter), rail, and other (primarily ship, limousine, taxi, shuttle services, bicycling, walking). In the analysis of modes used to access long distance transportation modes, bicycling and walking (bike/walk) are considered separately.

The NHTS data were collected from March 2001 through May 2002. The September 11, 2001 attacks on New York and Washington had an impact on travel, especially travel by air, in the following months. BTS is analyzing the impact of the 9/11 attacks on travel in the United States, but that analysis has not yet been completed, and thus the impact of those events cannot yet be quantified for the NHTS data used in this report. While those attacks likely had some impact on travelers modal choice and the percentages using the various modes, we do not believe at this time that the impact was significant enough to change the basic findings in this report.

Comparisons made in this report are statistically significant at a 0.05 level.

The following tables provide the data on which this report is based. The percentages used in each table are weighted, and standard errors are provided for all data in the tables. Cells with a small sample size (less than 30 observations), or with a coefficient of variation greater than 0.3, which can make the estimates unreliable, are shown underlined . Note that in many cases the sample size for other, train, and bus are too small to be reliable. Cells that are not statistically different from others in the same row are shaded. Notes below the tables clarify the statistical significance shading or other information where necessary.

[1] Public transportation refers to all transportation modes except personal vehicle.

[2] Personal vehicle includes car, van, noncommercial truck, recreational vehicle, sport utility vehicle or motorcycle.

[3] Personal business trips are those taken for family, personal, religious or medical reasons.

[4] The percentage of personal business trips completed by bus (5.6%) and air (4.7%) are not statistically different.

[5] There is no statistical difference between the percentage of air and bus travelers using a second mode.

[6] Examples of other modes are ship, ferries and limousines.

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Open Access

Peer-reviewed

Research Article

The analysis and solution for intercity travel behaviors during holidays in the post-epidemic era based on big data

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft

* E-mail: [email protected]

Affiliation China Academy of Transportation Sciences, Beijing, China

Roles Software, Supervision, Validation, Visualization, Writing – review & editing

Affiliation School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

• Xike Zhang, 

• Published: July 19, 2023
• https://doi.org/10.1371/journal.pone.0288510
• Reader Comments

The COVID-19 had a huge impact on the transportation industry. In the post-epidemic stage, intercity transportation will face great challenges as places are unsealed, tourism and other service industries begin to recover, and residents’ travel demand gradually increases. An in-depth study of residents’ intercity travel behavior during holidays in the post-epidemic era will help restore public trust in public transportation and improve the quality of public transportation services. Based on traditional research on ways of travelling, the study adopted the Complex Network Analysis Theory. The city clusters of Shandong Peninsula were taken as the research region. The research studied the impact of the differences in regional attributes of the cities in Shandong Peninsula on residents’ intercity travel in the post-epidemic times. A dynamic evolution model of how residents choose to travel was built to simulate the changes to their ways of traveling in the post-epidemic era under two conditions, which are: traveling under the government’s supervision of intercity travel and traveling under the government’s optimization of intercity travel conditions. The conclusions drawn from the analyses of Complex Network Theory and Evolutionary Game Theory are as follows. First, in the holiday intercity travel in the post-epidemic times, the neighboring cities of Shandong Peninsula are closely connected, thus traveling between neighboring cities dominates intercity travel. Second, the travel network concentration of residents on long-term holidays is lower than that on short-term holidays, and the migration intensity of residents is higher than that on short-term holidays, while the willingness of residents’ migration on short-term holidays is higher than that on long-term holidays. The willingness to migrate on holidays is generally lower than that before the epidemic. Third, in a normal intercity travel network, the travel between two cities with medium and long distances is mainly by public transport. However, the dominance of public transport will be affected under the impact of the epidemic. In short-distance travel between two cities, private transport is in an advantageous position, and under the impact of the epidemic, this advantage will become more significant. The government can improve the position of public transport in short-distance travel by making optimizations.

Citation: Zhang X, Gao J (2023) The analysis and solution for intercity travel behaviors during holidays in the post-epidemic era based on big data. PLoS ONE 18(7): e0288510. https://doi.org/10.1371/journal.pone.0288510

Editor: Jing Cheng, Shenzhen University, CHINA

Received: February 19, 2023; Accepted: June 27, 2023; Published: July 19, 2023

Copyright: © 2023 Zhang, Gao. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

According to the SIR model (Susceptible Infectious Recovered Model), the urban traffic system in the epidemic times can be divided into five stages: peacetime stage, epidemic latent stage, epidemic outbreak stage, post-epidemic stage and recovery and upgrading stage [ 1 ]. By March, 2020, the rate of resumption of work in Shanghai, Jiangsu, Zhejiang, Fujian, Liaoning, Jiangxi, Guangdong and other provinces has exceeded 70%, and many places have started the initial stage to resume work and production. The Ministry of Transport of China has introduced measures such as strictly controlling the full load rate of public transport, lifting traffic restrictions and lowering parking rates to support economic activities while ensuring the safety of travelers [ 2 , 3 ].

China has a huge population. The imbalance between the intercity passenger transport service level and the extremely high holiday travel demand is prominent. During the epidemic, intercity transport was greatly affected. In the post-epidemic stage, with the release of lock-down in some areas and the recovery of tourism and other service industries, this imbalance became more outstanding.

Most of the existing research results on travel behaviors are applicable to the pre-epidemic period, but there are few studies on the epidemic period and the post-epidemic times. The travel of residents under the influence of the epidemic is influenced by various factors (e.g., government control and their own psychological factors). Residents in cities with different levels of economic development have different perceptions of the travel risks associated with the epidemic, and the government’s management of residents’ travel needs to be considered based on social conditions (e.g., whether it is on a holiday), economic conditions, and the city’s geographic location. Traditional travel behavior research methods focus more on the activity travel itself, with less research on the interaction of the above-mentioned external factors, and also lack of in-depth discussion on the decision mechanism of travel behavior. Studying the intercity travel behaviors of residents in the post-epidemic times on holidays can not only provide decision-making basis for the planning, layout, design, traffic management and control of transportation infrastructure in the recovery and upgrading stage, but also help to restore people’s trust in public transport and improve its service quality [ 4 ].

Complex Network Analysis Theory and Evolutionary Game Theory are widely used in the research of transportation related fields. Yang et al. [ 5 ] used Complex Network Theory to evaluate the robustness of Beijing metro network in the face of random failures and malicious attacks. Ling et al. [ 6 , 7 ] adopted Complex Network Theory to study the role of dynamic characteristics of traffic in dynamic networks and the traffic processes of static networks in explosive synchronization. Yu et al. [ 8 ] studied Nanjing metro network by using Complex Network Theory. Their study took metro lines as subsystems and further simplified them as nodes, providing perspectives for complex network research. Meng et al. [ 9 ] employed the Complex Network Theory to study the optimization of train timetable, and proposed practical methods to improve the stability of train timetable. Zhang et al. [ 10 ] analyzed the stability of urban public transport network based on the Complex Network Theory, and provided some valuable insights for future public transport network planning. Talarico et al. [ 11 ] established a multi-mode safe transportation model according to Evolutionary Game Theory. Based on this model, safety resources in chemical supply chain were allocated, and transportation modes with different safety characteristics were selected for different transportation scenarios. Li et al. [ 12 ] used the topology structure of the complex network to characterize the interaction between travelers. Based on the assumptions of travelers’ bounded rationality and crowd wisdom, an evolutionary game model of travelers’ travel was established and the travel behavior rules of travelers was studied during rush hours. Chen et al. [ 13 ] adopted evolutionary game theory to dynamically analyze the parking decision-making behaviors of government management departments, cargo transportation enterprises and freight drivers, so as to reduce the negative impact of unreasonable parking behaviors on the traffic system in the process of freight transportation.

Currently, scholars have conducted a series of studies on the travel intentions of tourists and the spatial and temporal characteristics of human activities during the COVID-19 epidemic. Li et al. [ 14 ] found that travelers significantly reduced the scope of intercity travel during the May Day holiday in 2020; Ye et al. [ 15 ] found that the risk level of the epidemic in Guangdong Province was largely influenced by the scale of population movement and transportation location factors; Wu et al. [ 16 ] found that the tourism market in Hong Kong’s outlying islands and Kowloon was most severely affected by the epidemic. The above studies suggest that the COVID-19 epidemic has a significant impact on the spatial and temporal patterns of human activities, leading to large fluctuations in the structure of travel networks.

Although relevant studies on the impact of the epidemic on residents’ intercity travel behavior have been conducted in the industry, they are mostly in the form of questionnaire surveys with limited sample size, which cannot reflect the changes in residents’ intercity travel patterns on a macroscopic scale. So far, few studies have been conducted on the travel behaviors combining Evolutionary Game Theory and Complex Network Analysis Theory. Evolutionary Game Theory and Complex Network Analysis Theory can both reflect the changes of residents’ travel patterns on a fine spatial and temporal scale and effectively describe the relationship between the government and residents in intercity travel activities. The intercity traffic network is a typical complex system, and the participants of intercity traffic, as a game group, cannot quickly select the optimal strategy every time. Therefore, based on traditional research on ways of traveling, the study adopted the Complex Network Analysis Theory. The city clusters of Shandong Peninsula were taken as the research region. A dynamic evolution model of how residents choose to travel was built to simulate the changes to their ways of traveling in the post-epidemic times under two conditions, which are: traveling under the government’s supervision of intercity travel and traveling under the government’s optimization of intercity travel conditions.

2. Location analysis of city clusters of Shandong Peninsula

2.1 urban location analysis theory.

There are various reasons for the heterogeneity of urban residents’ travel behaviors, including the differences in residents’ travel purpose, travel time and regional attributes [ 17 ]. In this section, the complex network method is adopted to analyze the urban network characteristics of city clusters of Shandong Peninsula.

The population migration network in the real world often features a small world and is scale free. The commonly used network analysis indicators are as follows:

• (1) Degree. It is used to represent the number of edges connected to a node in a complex network. In a directed network, there are two concepts: in-degree and out-degree. Therefore, the population in-migration and out-migration intensity of any city in the study period can be expressed by Eqs ( 1 ) and ( 2 ):

• (2) In order to study the position potential of cities in the network, the weighted centrality index( WCI i ) [ 18 ] and the city weighted advantage coefficient ( WAC i ) are used to calculate the position potential and advantage of cities in the network.

• (3) The urban equilibrium coefficient UEC c is used to calculate the hierarchical structure characteristics of each city in the network. The calculation is shown in Eq (5) :

Where Z i represents the ratio of the sum of edge intensity associated with city i to the sum of edge intensity associated with all cities in the network. I represents the number of cities in the network. The value range of UEC i is [0, 1]. When UEC c = 0, it indicates that the difference of city level in the network is the largest. This index is used to describe the difference of city level of all cities in the whole intercity travel network.

• (4) The ratio of the migration willingness index to the actual migration index from the Gaud migration big data is used to obtain the migration willingness, which characterizes the intercity migration willingness of the urban residents in the network. The calculation equation is as follows:

Where m is the time range (in days) of the study; n is the number of migration routes between cities in the region of the study; W ij and R ij represent the migration willingness index and the actual migration index.

2.2 Data acquisition

The urban network is usually studied by using direct data and indirect data based on population flow [ 19 ]. The direct data includes big data from Tencent location, Baidu migration data, and Gaud Map traffic big data. The indirect data includes train schedule data, passenger coach schedule data, and flight schedule data. In this study, big data from Gaud is used to show the willingness of urban migration. The in-migration intensity and out-migration intensity are used to characterize the intensity of population flow between cities in the areas of the study, so as to measure the interaction between cities in the areas. The intended migration data and actual migration data on weekdays and holidays before the epidemic (New Year’s Day holiday in 2019 and New Year’s Day holiday in 2020) are compared (see the data listed in Tables 1 – 8 ) with the holidays during the post-epidemic period (National Day holiday in 2021, New Year’s Day holiday in 2022 and the May Day holiday in 2022 respectively correspond to holiday 1 to 3 below) to quantitatively analyze the impact of the presence or absence of COVID-19 on the intercity travel willingness of urban residents in weekdays and holidays, in pre-epidemic and post-epidemic times, and during holidays. OD matrix A-F is generated by using the migration willingness index and the actual migration index among cities in the region of the study (where the letters A, B, C, E, F, G, K and L listed in Tables 1 – 8 represent the license plate letters of cities Jinan, Qingdao, Zibo, Dongying, Yantai, Weifang, Weihai and Rizhao, respectively).

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https://doi.org/10.1371/journal.pone.0288510.t005

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https://doi.org/10.1371/journal.pone.0288510.t008

2.3 Analyses of calculation results

The ratio of the migration willingness index to the actual migration index of the three holidays was calculated to characterize the intercity migration willingness of the residents in all cities of the network. See the data in Table 9 for the results.

https://doi.org/10.1371/journal.pone.0288510.t009

The weighted centrality index WCI i of each city in the three holidays (holiday 1 to 3) is calculated respectively, which is compared with that of the weekdays and holidays of eastern cities before the epidemic ( Table 10 ) [ 14 ]. The results are shown in Table 11 . The UEC c of city clusters of Shandong Peninsula is shown in Table 12 .

https://doi.org/10.1371/journal.pone.0288510.t010

https://doi.org/10.1371/journal.pone.0288510.t011

https://doi.org/10.1371/journal.pone.0288510.t012

The WAC i of each city in Shandong Peninsula was calculated. The calculation results are shown in Table 13 ( the specially marked value indicates that the advantage value of the city is higher than that of the average level of cities in network ).

https://doi.org/10.1371/journal.pone.0288510.t013

The roles of cities in Shandong Peninsula were divided according to the urban role identification model [ 20 ]. The results are shown in Table 14 .

https://doi.org/10.1371/journal.pone.0288510.t014

According to the data in Table 9 , the willingness of residents to migrate on short-term holidays is higher than that on long-term holidays, and the willingness to migrate on holidays is generally lower than that before the epidemic. According to the results of urban equilibrium coefficient of city clusters of Shandong Peninsula in Table 12 , this value is very close to 1 in all three holidays, which shows that there is no obvious difference in the city level of the whole intercity travel network. Before and after the holiday 1 (National Day holiday in 2021), there were no local COVID cases in Shandong Province; the travel of residents was less restricted, and was therefore normal. Moreover, the duration of the National Day holiday was long. Therefore, Shandong Peninsula saw the largest intercity population flow on holiday 1. The weighted centrality index of Qingdao and Weifang, the regional hub cities in Shandong Peninsula city clusters, is also the closest to the average value of eastern cities during the National Day holiday before the epidemic. As the capital city of Shandong Province, Jinan’s relative position potential is not as good as Weifang and Qingdao. First, the intercity travel in this study is only limited to the city clusters of Shandong Peninsula, and does not involve other cities outside the region. Second, Qingdao and Weifang are located in the center of the region, which have strong attraction to the surrounding cities in the region. Before and after the holiday 2 (New Year’s Day holiday in 2022), there were no local COVID cases in Shandong Province, while cases of Omicron, which was highly infectious, occurred in some parts of China. The travel of residents in Shandong Peninsula was less restricted, and was therefore basically normal. The external environment of intercity travel was basically the same as that of holiday 1. The roles of cities in the region were roughly the same as those of holiday 1. The duration of New Year’s Day holiday was short, thus the intensity of residents’ migration during this period is low. However, the willingness of residents’ migration is 0.40, which is slightly higher than 0.37 of holiday 1. This indicates that the intercity traffic management capacity of Shandong Peninsula has been improved, and that the trust among intercity traffic was recovering in an orderly manner. Before the holiday 3 (the May Day holiday in 2022), there were concentrated Omicron cases in many places in Shandong Province. Shandong Provincial Health Commission designated 86 lock-down areas, 130 control areas, 67 prevention areas in Jinan. It designated 150 lock-down areas and 60 control areas in Yantai. Strict measures were taken against the epidemic. There were many travel restrictions for residents in Shandong Peninsula, and some urban public transport has been suspended. The epidemic has directly led to a significant reduction in the connection between the two cities and other cities. These two cites have a high position potential in Shandong Peninsula. As a result, this has further affected the willingness of all urban residents in the region to travel between cities.

3. Ways of travel selection model

3.1 evolutionary game analysis.

The single OD pair traveling by two ways (public transport and private transport) is considered. Assume that the total traffic demand is N and that the public transport supply can fully meet the traffic demand. The travel method selection problem between the OD pair can be regarded as a group game problem, and the game elements are as follows:

• (1) Let the selection set of the two travel modes by travelers between the OD pair be S = { s 1 , s 2 }.
• (2) The proportion of travelers choosing public transport is x , and that choosing private transport is (1-x) .
• (3) Assume that the travel cost is c i when the traveler selects s i , hence the travel benefit is the inverse of the travel cost - c i when the traveler selects s i .
• (4) In the case of road congestion, the cost of choosing private transportation is c 1 , the additional travel cost caused by road congestion is c 3 , and when both sides of the game use private transportation, the travel cost of both sides of the game is c 1 +c 3 ; When the game opponent chooses public transportation, it will not cause road congestion, and the travel cost of private transportation is c 1 ; The price and travel time of public transportation are relatively certain, so no matter what kind of travel method the other party chooses, the travel cost of the traveler choosing public transportation is c 2 .

Based on the above, the cost matrix of travel mode selection is obtained (see Table 15 ).

https://doi.org/10.1371/journal.pone.0288510.t015

Combine Eqs ( 14 ) and ( 16 ). As A is greater than 0, there is a unique solution to this equation system, and the obtained equilibrium point is shown in Fig 1 .

https://doi.org/10.1371/journal.pone.0288510.g001

The influence of the change of parameters A and B in Eq (13) on the equilibrium point x * is analyzed as follows:

If the value of A becomes larger, causing the equilibrium point x * to shift to the left, it means that the cost difference between road congestion and non-congestion increases when travelers choose private transport, that is, the delay cost of choosing private transport increases. According to the principle of maximum utility, some travelers who choose private transport will change their travel mode. If the value of B becomes large, causing the equilibrium point x * to shift to the left, it means that the difference between the travel cost of private transport and public transport increases when the road is not congested. Some travelers who choose private transport will change their travel mode. If the value of A decreases, causing the equilibrium point x * to shift to the right, it means that the cost difference between road congestion and non-congestion decreases when travelers choose private transport. The model becomes stable. If the value of B decreases, causing the equilibrium point x * to shift to the right, it means that the difference between the travel cost of private transport and public transport reduces when the road is not congested. The model becomes stable.

To sum up, if the government plans to increase the proportion of public transport trips, a number of measures need to be taken to make the equilibrium point of this model shift to the right. In the model, parameter A actually represents the delay cost whether the road is congested or not, and parameter B actually represents the difference in time cost and economic cost caused by the inherent attributes of private transport and public transport. Therefore, the residents can be encouraged to choose public transport during intercity travel by increasing the frequency of intercity railway trains and their speed, opening express lines of intercity railway trains in big stations, reducing the ticket price, and changing the expressway tolling mode (e.g., tolls can be based on both time and mileage).

3.2 Numerical simulation and calculation

(1) The most representative OD pair is analyzed, which is Jinan-Qingdao pair in the studied region. Assume the proportion of group 1 choosing private transport is x , and that choosing public transport is ( 1-x ); the proportion of group 2 choosing private transport is y , and that choosing public transport is ( 1-y ). The expressway is about 360 kilometers long, and the traffic time is about 4 hours if there is no congestion and 6 hours if there is congestion. The economic cost is assumed to be 200 yuan. Therefore, there are the following equations: c 1 = 4 + 200/20 = 14 h , c 1 +c 3 = 6 + 200/20 = 16 h ; For public transport, intercity coaches and trains are considered comprehensively: c 2 = 4 + 140/20 = 11 h . Based on the above conditions, the cost matrix of this OD pair for travel mode selection is given below ( Table 16 ). The evolution game process of travel mode selection is shown in Fig 2(a) .

https://doi.org/10.1371/journal.pone.0288510.g002

https://doi.org/10.1371/journal.pone.0288510.t016

The following is an analysis of the dynamic evolution process of residents’ travel behavior under the government’s involvement and supervision after a local small-scale epidemic occurs in a period such as holiday 3. The government’s supervision on intercity travel is mainly to restrict the full load rate of public transport and impose on procedures for residents to enter and leave the bus station and railway station. In the model, this indicates the increase of the time cost of public transport. Then there is the equation: c 2 = 5 + 140/15 = 14.33 h , and this situation is shown in Fig 2(b) .

According to Fig 2(a) , this evolutionary game process tends to be stable after a limited number of iterations. It indicates that the residents’ intercity travel mode selection behavior between Jinan and Qingdao tends to be stable. Therefore, the proportion of residents choosing public transport will increase with the gradual restoration of residents’ trust in public transport. Under the government’s involvement and supervision, as shown in Fig 2(b) , public transport no longer dominates the modes of travel between the two places. If the government wants to restore the dominant position of public transport under this condition, it can introduce measures such as simplifying the entry and exit procedures and properly increasing the full load rate on the premise of ensuring the safety of passengers.

(2) For the travel between two cities with little difference in position potential in a short distance, the OD pair of Zibo and Weifang is analyzed. The expressway is about 120 kilometers long, and the traffic time is about 1.5 hours if there is no congestion and 2.5 hours if there is congestion. The economic cost is assumed to be 50 yuan. Therefore, there are the following equations: c 1 + c 3 = 2.5 + 50/20 = 5 h ; c 1 = 1.5 + 50/20 = 4 h . For public transport, intercity coaches and trains are considered comprehensively: c 2 = 1.5 + +60/20 = 4.5 h . Based on the above conditions, the cost matrix of this OD pair for travel mode selection is given below ( Table 17 ).

https://doi.org/10.1371/journal.pone.0288510.t017

Under the condition that the public transport is optimized by adjusting the travel time cost to 4h (in reality, this can be realized by reducing the ticket price by 10 yuan), output the dynamic evolution process of residents’ travel behavior under the government’s involvement and supervision after a local small-scale epidemic which occurs during holiday 3. See Fig 3 .

https://doi.org/10.1371/journal.pone.0288510.g003

According to Fig 3(a) , the evolutionary game process of travel mode selection behavior between Weifang and Zibo will not be stable after a limited number of iterations, and under the existing conditions, residents are more inclined to choose private transport. If public transport is optimized by adjusting the travel time cost to 4h (in reality, this can be realized by reducing the ticket price by 10 yuan), as shown in Fig 3(b) , although the evolutionary game process is still not stable, the proportion of residents choosing public transport for travel increases significantly. As the fixed cost determined by the inherent nature of public transport cannot be reduced, the parameters in this case will not be adjusted. If government’s supervision is considered, as shown in Fig 3(c) , this evolutionary game process tends to be stable after a limited number of iterations. This indicates that residents’ intercity travel mode selection behavior between Weifang and Zibo tends to be stable, and that residents are more willing to choose private transport.

4. Discussions

• (1) The data obtained in this study suggest that the locational relationships among cities in urban agglomerations may change due to the impact of the epidemic, and the roles of cities in urban agglomerations may change in response to changes in the epidemic situation and government policies on epidemic prevention.
• (2) Changes in city roles and urban locations can change the extent to which the epidemic affects residents’ intercity travel choice behavior. In the city cluster of Shandong Peninsula selected for this study, travel between the two hub cities Jinan-Qingdao is dominated by public transportation in general, but under the influence of the epidemic and government involvement in regulation, residents’ trust in public transportation will decrease, and some residents will prefer private transportation for travel. In trips between two cities with short distances and little difference in location, Zibo-Weifang, residents always tend to choose private transportation trips unless the government intends to optimize public transportation trips.
• (3) At present, travel during holidays is still significantly affected by the epidemic. Before and after the National Day holiday in 2021 and the New Year’s Day holiday in 2022, the travel situation of residents was not so different from that during the holidays before the epidemic. This situation to a certain extent reflects the improvement of the management capacity of intercity traffic in Shandong Peninsula and the continuous enhancement of the “certainty” for residents to travel. The trust among intercity traffic is recovering in an orderly manner. However, before the May Day holiday in 2022, there were concentrated Omicron cases in many places in Shandong. There were many travel restrictions for residents in Shandong Peninsula, and some urban public transport has been suspended.
• (4) The limitations of this paper are mainly reflected in the following two aspects. On the one hand, due to time constraints, the study of residents’ travel behavior during holidays in the post-epidemic era only covers some holidays in the past two years, and there are problems such as incomplete data collection and small samples; on the other hand, the study of intercity travel in this paper is only limited to the inner city cluster, and does not consider the connection between cities within the city cluster and cities outside the region.
• (5) Future studies need to collect more extensive and comprehensive data, and take into account other factors influencing travel behavior, for example, adding consideration of latent variables such as residents’ perceived risk capacity, economic constraints, and travel time.

5. Conclusion

• (1) On the whole, the neighboring cities in Shandong Peninsula are closely connected, and the intercity travel is dominantly between neighboring cities. The migration intensity between Yantai and Weihai, Weifang and Qingdao, and Jinan and Zibo is prominent. The strong attraction between neighboring cities also leads to the weak overall connection of the urban network in Shandong Peninsula. The provincial capital city Jinan and the sub-provincial city Qingdao have limited attraction to non-neighboring cities in the region, and there is no obvious difference in the city level of the whole intercity travel network.
• (2) According to the current data, the travel network concentration of residents in long-term holidays is lower than that in short-term holidays, and the migration intensity of residents is higher than that in short-term holidays, while the willingness of resident migration in short-term holidays is higher than that in long-term holidays. The willingness to migrate during the holidays is lower than that before the epidemic. For one thing, this suggests that the travel willingness of residents in the post-epidemic era is still recovering. For another, this shows that the intercity traffic management capacity in the post-epidemic era needs to be improved, and that the recovery and development of the traffic field are still complex.
• (3) The epidemic has directly led to a significant reduction in the connection between the two cities and other cities. These two cites have a high position potential in Shandong Peninsula. As a result, this has further affected the willingness of all urban residents in the region to travel between cities. Besides, the epidemic will affect the change of the equilibrium coefficient of the city clusters, which lead to a more significant city level difference among the cities in the network. For example, in the region of the study, the urban advantage of Qingdao and Weifang is significantly higher than that of other cities due to the epidemic.
• (4) In the intercity travel network, the travel between two cities with medium and long distances is normally dominated by public transport. Due to the impact of COVID-19, the dominant position of public transport will be affected, but it will not be replaced by private transport. In short-distance travel between two cities, private transport is in an advantageous position, and under the impact of the epidemic, this position will become dominant. The government can improve the position of public transport in short-distance travel by making optimizations (such as appropriately reducing ticket prices and simplifying entry and exit procedures).
• (5) There are many kinds of direct linked data and indirect linked data in process of the study about intercity travel behavior during holidays, and the amount of data is large, which requires more powerful computing power. At the same time, in order to prevent some sensitive data information from being stolen by malicious attackers, federated learning model can be used to analyze and process traffic travel data, which is helpful to achieve better research results and ensure data security.

Supporting information

S1 appendix..

https://doi.org/10.1371/journal.pone.0288510.s001

https://doi.org/10.1371/journal.pone.0288510.s002

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• Chilpancingo De Los Bravo, Guerrero
• Cidade Ocidental, GO
• Ciechocinek
• Cincinnati, OH
• Cirò Marina
• Cista Provo
• Cista Velika
• Città di Castello
• Cittadella del Capo
• Ciudad de Mexico, MX
• Ciudad Juarez, MX
• Ciudad Valles, San Luis Potosi
• Civitanova Marche
• Civitavecchia
• Clara City, MN
• Claregalway
• Claremorris
• Clarinbridge
• Clarinda, IA
• Clarksdale, MS
• Clarksville, TN
• Clausthal-Zellerfeld
• Cle Elum, WA
• Clear Lake, IA
• Clearfield, PA
• Clendenin, WV
• Clermont-Ferrand
• Cleveland, MS
• Cleveland, OH
• Clewiston, FL
• Clinton, AR
• Clinton, MO
• Clinton, NC
• Cloquet, MN
• Cluj-Napoca
• Coalinga, CA
• Cobleskill, NY
• Coeur d'Alene, ID
• Coffeyville, KS
• Colima, Colima
• Colle di Val d'Elsa
• College Park, MD
• College Station, TX
• Collingwood
• Collins, MO
• Colonial Heights, VA
• Colorado Springs, CO
• Columbia, MO
• Columbia, SC
• Columbus, GA
• Columbus, IN
• Columbus, NE
• Columbus, OH
• Colville, WA
• Comfort, TX
• Concepción Del Oro, Zacatecas
• Concord, NH
• Contagem, MG
• Contrada Amica
• Contrada Foresta
• Contrada Frasso
• Contrada Toscano
• Conyers, GA
• Conza della Campania
• Cookeville, TN
• Coolville, OH
• Cooperstown, NY
• Coos Bay, OR
• Copenhagen Airport
• Corning, NY
• Corpus Christi, TX
• Cortina d'Ampezzo
• Cortland, NY
• Corvallis, OR
• Corydon, IN
• Cosne-Cours-sur-Loire
• Cottonwood, ID
• Covington, KY
• Craigmont, ID
• Crescent City, CA
• Crescent, OR
• Cristalina, GO
• Cristuru Secuiesc
• Croce di Magara
• Crockett, TX
• Crookston, MN
• Crossville, TN
• Crvena Reka
• Cuernavaca, Morelos
• Çuğun (Kırşehir)
• Culiacán, Sinaloa
• Cumberland, MD
• Cupra Marittima
• Curitiba, PR
• Czarna Górna
• Częstochowa
• D Hanis, TX
• Danilovgrad
• Dansville, NY
• Danville, IL
• Danville, PA
• Dapčevački Brđani
• Davenport Center, NY
• Davenport, IA
• Davenport, NY
• Daytona Beach, FL
• De Kalb Junction, NY
• De Queen, AR
• Death Valley, CA
• Decatur, IN
• Deer Park, WA
• Degirmendere
• Del Rey Oaks, CA
• Del Rio, TX
• Delaware Water Gap, PA
• Delicias, Chihuahua
• Delmenhorst
• Delmont, PA
• Delphos, OH
• Demopolis, AL
• Den Bosch (‘s-Hertogenbosch)
• Des Moines, IA
• Desenzano del Garda
• Desert Hot Springs, CA
• Detroit Lakes, MN
• Detroit, MI
• Dharamshala
• Diano Marina
• Dickinson, ND
• Differdange
• Dimitrovgrad
• Discovery Bay, WA
• Disneyland Paris
• Dobrinishte
• Doktor Yosifovo
• Dolný Kubín
• Donaueschingen
• Donja Budičina
• Donja Dubrava
• Donja Koritnica
• Donja Velešnja
• Donja Zelina
• Donji Andrijevci
• Donji Kukuruzari
• Donji Meljani
• Donji Mihaljevec
• Donji Miholjac
• Donji Pustakovec
• Donji Striževac
• Donji Vakuf
• Donji Vidovec
• Donji Vukojevac
• Donnelly, ID
• Douglas, WY
• Doylestown, PA
• Drammen Bangeløkka
• Drensteinfurt
• Drewsey, OR
• Drobeta-Turnu Severin
• Druskininkai
• Dublin Airport
• Dubuque, IA
• Duchesne, UT
• Dunfermline
• Duque de Caxias, RJ
• Durango, Durango
• Duszniki-Zdrój
• Eagle Pass, TX
• East Lansing, MI
• Eau Claire, WI
• Ebensburg, PA
• Edenton, NC
• Edgewater, FL
• Edgewood, MD
• Edgeworthstown
• Edinboro, PA
• Edinburg, TX
• Edmonds, WA
• Edmonton, AB
• Effingham, IL
• Ehrenberg, AZ
• Eindhoven Airport
• El Barco de Avila
• El Centro, CA
• El Dorado, KS
• El Mante, Tamaulipas
• El Monte-Baldwin Park, CA
• El Monte, CA
• El Paso, TX
• El Portal, CA
• El Reno, OK
• Elizabeth City, NC
• Elkhart, IN
• Ellensburg, WA
• Ellicottville, NY
• Elmalık (Bolu)
• Embu das Artes, SP
• Emmerich am Rhein
• Empalme, Sonora
• Enniscorthy
• Ensenada, Baja California
• Eraclea Mare
• Erechim, RS
• Ereğli-Konya
• Erskine, MN
• Escaldes-Engordany
• Esch-sur-Alzette
• Escondido, CA
• Eskişehir TCDD Gar
• Evans Mills, NY
• Evanston, WY
• Evansville, IN
• Everett, WA
• Evergreen, AL
• Fabrizio G.
• Fairfield, IA
• Fairmont, MN
• Fairmont, WV
• Falerna Marina
• Falfurrias, TX
• Faribault, MN
• Farmington, UT
• Faro Airport
• Fayetteville, AR
• Fayetteville, NC
• Feda terminal
• Feira de Santana, BA
• Fergus Falls, MN
• Fernley, NV
• Fetești-Gară
• Fiera di Primiero
• Figueira da Foz
• Fillmore, CA
• Fillmore, UT
• Finale Ligure
• Fiordimonte
• Fiumefreddo
• Flagstaff, AZ
• Fleischmanns, NY
• Flekkefjord rutebilstasjon
• Florence, AL
• Florence, OR
• Florence, SC
• Florianópolis, SC
• Fokserød (Sandefjord)
• Forest City, NC
• Forest Lake, MN
• Formosa, GO
• Forrest City, AR
• Fort Collins, CO
• Fort Dodge, IA
• Fort Jackson, SC
• Fort Lauderdale, FL
• Fort Macleod
• Fort Madison, IA
• Fort Myers, FL
• Fort Pierce, FL
• Fort Scott, KS
• Fort Stockton, TX
• Fort Walton Beach, FL
• Fort Wayne, IN
• Fort Worth, TX
• Fort Yates, ND
• Fortaleza, CE
• Fosston, MN
• Framingham, MA
• Francavilla Fontana
• Francisco Sá Carneiro Airport
• Francisco Sá, MG
• Frankfurt Airport
• Frankfurt an der Oder
• Franklin, IN
• Františkovy Lázně
• Frederick, MD
• Fredericksburg, TX
• Fredericksburg, VA
• Fredrikstad
• Freilassing
• Fremont, NE
• Fresnillo, Zacatecas
• Freudenstadt
• Friedrichshafen
• Frostburg, MD
• Frýdek-Místek
• Ft Hunter Liggett, CA
• Gadsden, AL
• Gadsden, AZ
• Gainesville, FL
• Gainesville, GA
• Gainesville, TX
• Galesburg, IL
• Gällivare Resecentrum
• Gambier, OH
• Garberville, CA
• Garešnički Brestovac
• Garmisch-Partenkirchen
• Gasquet, CA
• Gastonia, NC
• Gdansk Lech Walesa Airport
• Gelsenkirchen
• Geneseo, NY
• Geneva Airport
• George West, TX
• Georgetown, TX
• Gettysburg, SD
• Giddings, TX
• Gilchrist, OR
• Gillette, WY
• Gioia Tauro
• Girona Airport
• Gizzeria Lido
• Glasgow Airport
• Glastonbury
• Glavina Donja
• Glendale, CA
• Glendive, MT
• Glenns Ferry, ID
• Glens Falls, NY
• Glenwood Spgs, CO
• Glenwood Springs, CO
• Globe-Miami, AZ
• Goiânia, GO
• Gold Beach, OR
• Golden Sands
• Goldsboro, NC
• Golubovac Divuški
• Gómez Palacio, Durango
• Gonzales, LA
• Goodland, KS
• Gornja Koritnica
• Gornja Vrba
• Gornji Daruvar
• Gornji Draganec
• Gornji Kneginec
• Gornji Milanovac
• Gornji Striževac
• Gornji Vakuf
• Gorzów Wielkopolski
• Gothenburg airport
• Gotse Delchev
• Gouverneur, NY
• Graal-Müritz
• Graberje Ivanićko
• Grambling, LA
• Grand Canyon (South Rim), AZ
• Grand Canyon (West Rim), AZ
• Grand Canyon Village, AZ
• Grand Forks, ND
• Grand Gorge, NY
• Grand Island, NE
• Grand Junction, CO
• Grand Rapids, MI
• Grand Rapids, MN
• Grange (Sligo)
• Grangeville, ID
• Granite Falls, MN
• Grants Pass, OR
• Grantsville, MD
• Gravina in Puglia
• Great Falls, MT
• Greeley, CO
• Green Bay, WI
• Green Forest, AR
• Green River, UT
• Greenbrier, AR
• Greeneville, TN
• Greenfield, CA
• Greenfield, IN
• Greenfield, MA
• Greensboro, AL
• Greensboro, GA
• Greensboro, NC
• Greensburg, IN
• Greensburg, PA
• Greenville, MS
• Greenville, NC
• Greenville, SC
• Greenville, TX
• Greenwood, IN
• Greybull, WY
• Grimstad (Øygårdsdalen)
• Grinnell, IA
• Grodzisk Wielkopolski
• Grottaminarda
• Grottammare
• Grover Beach, CA
• Grubišno Polje
• Guadalajara, Jalisco
• Guanajuato, Guanajuato
• Guardia Piemontese
• Guarulhos, SP
• Guasave, Sinaloa
• Guaymas, Sonora
• Gümüldür Atatürk
• Gura Humorului
• Güvercinlik
• Hackensack, MN
• Hackettstown, NJ
• Hagerstown, MD
• Haines Falls, NY
• Hamburg Airport
• Hamilton, ON
• Hampton, VA
• Hamptonville, NC
• Hancock, MD
• Hanford, CA
• Hannibal, MO
• Hanover, NH
• Harlingen, TX
• Harpersfield, NY
• Harrisburg, PA
• Harrisonville, MO
• Hartford, CT
• Hastings, FL
• Havre De Grace, MD
• Hawthorne, FL
• Hawthorne, NV
• Hayward, CA
• Hazleton, PA
• Heathrow Airport
• Heber City, UT
• Heiligenhafen
• Helleland (Skjerpeveien) Eigersund, Rogaland
• Helsingborg
• Hempstead, NY
• Henderson, NC
• Henderson, TX
• Hensonville, NY
• Herceg Novi
• Hereford, TX
• Heringsdorf
• Herkimer, NY
• Hermiston, OR
• Hermosillo, Sonora
• Hibbing, MN
• Hickory, NC
• Hicksville, NY
• Hidalgo, Durango
• Hidalgo, TX
• High Point, NC
• Highmount, NY
• Hillsboro, OR
• Hinckley, MN
• Hinesville, GA
• Hliník nad Hronom
• Holbrook, AZ
• Holland, MI
• Hollister, MO
• Hollywood, FL
• Hood River, OR
• Hořice na Šumavě
• Horné Chlebany
• Horní Vltavice
• Horseshoe Bend, ID
• Houston Southeast, TX
• Houston, TX
• Hradec Kralove
• Hrvatska Kostajnica
• Huejutla De Reyes, Hidalgo
• Huercal Overa
• Huetamo, Michoacan
• Hughesville, PA
• Humansville, MO
• Humphrey, NE
• Huntingdon (Cambridgeshire)
• Huntington, WV
• Huntsville, AL
• Huntsville, TX
• Hurricane, WV
• Husum (Sweden)
• Hutchinson, KS
• Ibotirama, BA
• Idaho Falls, ID
• Idaho Springs, CO
• Igea Marina
• Iguala De La Independencia, Guerrero
• Imst-Pitztal
• Indiana, PA
• Indianapolis, IN
• Indianola, MS
• Interlachen, FL
• Iowa City, IA
• Irapuato, Guanajuato
• Isla Vista, CA
• Islamorada, FL
• Island Park, ID
• Itaberaba, BA
• Itapema, SC
• Ivanić Grad
• Ivano-Frankivsk
• Ivanovo Polje
• Jablonec nad Nisou
• Jackson, MI
• Jackson, MN
• Jackson, MS
• Jackson, OH
• Jackson, TN
• Jackson, WY
• Jacksonville, AL
• Jacksonville, FL
• Jacksonville, NC
• Jamestown, ND
• Janos, Chihuahua
• Janów Lubelski
• Jaraguá do Sul, SC
• Jarosławiec
• Jastrzębia Góra
• Jastrzębie-Zdrój
• Jefferson City, MO
• Jelenia Góra
• Jerez de la Frontera
• Jezera (Murter)
• Jim Thorpe, PA
• Jiménez, Chihuahua
• Jindrichuv Hradec
• João Pessoa, PB
• João Pinheiro, MG
• Johnsonburg, PA
• Johnstown, PA
• Joinville, SC
• Jonesboro, AR
• Jonesboro, LA
• Jug Bogdanovac
• Jugovo Polje
• Juiz de Fora, MG
• Junction City, KS
• Junction, TX
• Jundiaí, SP
• Juntura, OR
• Jupiter, FL
• Kaatsheuvel (Efteling)
• Kahramanmaraş
• Kaiserslautern
• Kalamazoo, MI
• Kale (Denizli)
• Kalispell, MT
• Kalisz Pomorski
• Kamień Pomorski
• Kamienna Góra
• Kaniža Gospićka
• Kankakee, IL
• Kansas City, KS
• Kansas City, MO
• Kargalıyeniköy
• Karjatnurme
• Karksi-Nuia
• Karlovy Vary
• Karnes City, TX
• Katowice Airport
• Kąty Rybackie
• Kaynarca (Bursa)
• Kazimierz Dolny
• Kearney, NE
• Kebnats Saltoluokta VSK, Gällivare
• Keene Valley, NY
• Kellogg, ID
• Kenosha, WI
• Kent Island, MD
• Kerpen-Horrem
• Kerrville, TX
• Ketchum, ID
• Kettle Falls, WA
• Key Largo, FL
• Key West, FL
• Khmelnytskyi
• Kilgore, TX
• Kilingi-Nõmme
• Kimberly, ID
• King City, CA
• King of Prussia, PA
• Kingman, AZ
• Kingston, NY
• Kingston, ON
• Kingston, WA
• Kingsville, TX
• Kinston, NC
• Kissimmee, FL
• Kitchener, ON
• Kivi-Vigala
• Klamath Falls (Running Y), OR
• Klamath Falls, OR
• Klamath Glen, CA
• Klamath, CA
• Klášterec nad Ohří
• Klausen (Chiusa)
• Kloštar Ivanic
• Kloštar Podravski
• Knezovljani
• Knoxville, TN
• Kohtla-Järve
• Koprivshtitsa
• Kõrgessaare
• Kozarska Dubica
• Kraków Airport
• Kristiansand
• Kristinehamn
• Krivaj Voloder
• Krościenko nad Dunajcem
• Krosno Odrzańskie
• Krynica Morska
• Krynica-Zdrój
• Kudowa-Zdrój
• Kühlungsborn
• Kurukshetra
• Kutinska Slatina
• L'Aldea
• L'Aquila
• L'Hospitalet
• La Croix-Valmer
• La Crosse, WI
• La Grande, OR
• La Grange, GA
• La Grange, TX
• La Jonquera
• La Piedad, Michoacan
• La Pine, OR
• La Porte, IN
• La Roche-sur-Foron
• La Roche-sur-Yon
• La Rochelle
• La Seu d'Urgell
• Lääne-Nigula
• Lafayette, IN
• Lafayette, LA
• LaGrange, IN
• Lake Charles, LA
• Lake City, FL
• Lake George, NY
• Lake Hill, NY
• Lake Placid, FL
• Lake Placid, NY
• Lake Point, UT
• Lake Wales, FL
• Lakeland, FL
• Lakeland, MN
• Lakeside, AZ
• Lakeside, MT
• Lakewood, CO
• Lamezia Terme
• Lamezia Terme Airport
• Lancaster, OH
• Langen am Arlberg
• Lansing, MI
• Lantz Corners, PA
• Laramie, WY
• Larvik (Farriseidet)
• Las Cruces, NM
• Las Vegas, NV
• Latimer, IA
• Latrobe, PA
• Laurinburg, NC
• Lawrence, KS
• Le Lavandou
• Le Mont Saint-Michel
• Leavenworth, KS
• Leavenworth, WA
• Leighlinbridge
• Leipzig/Halle Airport
• Lemoore, CA
• León, Guanajuato
• Lethbridge, AB
• Letterkenny
• Lewisburg, PA
• Lewiston, ID
• Lewiston, ME
• Lewistown, PA
• Lewisville, TX
• Lexington, KY
• Lexington, NC
• Lexington, NE
• Liberty Hill, TX
• Liberty, IN
• Lido di Classe
• Lido di Savio
• Lignano Sabbiadoro
• Ligonier, IN
• Lille Airport
• Lillesand (Gaupemyr bussterminal)
• Limburg an der Lahn
• Limeira, SP
• Limerick Junction
• Linares, Nuevo Leon
• Lincoln, NE
• Lincolnton, NC
• Lindsborg, KS
• Lipno nad Vltavou
• Liptovský Mikuláš
• Lisbon Airport
• Litchfield, MN
• Little Falls, MN
• Little Rock, AR
• Live Oak, FL
• Liverpool, PA
• Livingston, AL
• Livingston, MT
• Livingston, TX
• Lloret de Mar
• Lock Haven, PA
• Lockesburg, AR
• Lockhart, TX
• Locorotondo
• London Gatwick Airport
• Londrina, PR
• Long Beach, CA
• Longobardi Marina
• Longueuil, QC
• Longview, TX
• Loon Lake, WA
• Lordsburg, NM
• Los Angeles, CA
• Los Angeles, CA (Airport)
• Los Mochis, Sinaloa
• Loudonville, OH
• Louisville, KY
• Loveland, CO
• Lovelock, NV
• Lubbock, TX
• Lublin Airport
• Lucena del Puerto
• Luis Eduardo Magalhães, BA
• Lumberton, NC
• Luverne, MN
• Luziânia, GO
• Lynchburg, VA
• Lyngdal (Rom terminal)
• Lyon Saint-Exupéry Airport
• Lysaker stasjon
• Macclenny, FL
• Macedo de Cavaleiros
• Mačvanska Mitrovica
• Madera, Chihuahua
• Madison, GA
• Madison, NE
• Madison, WI
• Madisonville, KY
• Madonna di Campiglio
• Madrid Barajas Airport
• Makedonski Brod
• Mala Gorica
• Mala Pisanica
• Mala Subotica
• Malad City, ID
• Malgrat de Mar
• Mali Zdenci
• Malvern, AR
• Manchester Airport
• Manchester, NH
• Manchester, TN
• Manchester, VT
• Mandal (Marnarkrysset)
• Mandatoriccio
• Manfredonia
• Manhattan, KS
• Manitowoc, WI
• Mansfield, OH
• Manzanillo, Colima
• Maple Grove, MN
• Mapleton, OR
• Marathon, FL
• Marble Falls, TX
• Margaretville, NY
• Marietta, GA
• Marietta, OH
• Marijampolė
• Marília, SP
• Marina di Camerota
• Maringá, PR
• Marinha Grande
• Mariposa, CA
• Marked Tree, AR
• Markham, IL
• Markkleeberg
• Markovac Križevački
• Marktredwitz
• Marling (Marlengo)
• Marseille Airport
• Marshall, MN
• Marshall, TX
• Marshalls Creek, PA
• Martina Franca
• Martinsburg, OH
• Martinsicuro
• Martinsville, IN
• Marysville, CA
• Marysville, MI
• Marysville, OH
• Maryville, MO
• Massena, NY
• Matamoros, MX
• Matozinhos, MG
• Mazatlán, Sinaloa
• Mc Camey, TX
• Mcalester, OK
• Mcallen, TX
• McCammon, ID
• McGregor, MN
• Mckinney, TX
• McLaughlin, SD
• McPherson, KS
• Meadville, PA
• Medford Airport, OR
• Medford-Ashland, OR
• Medford, OR
• Medina Sidonia
• Melrose, MT
• Memmingen Airport
• Memphis, TN
• Meran (Merano)
• Mercogliano
• Meridale, NY
• Meridian, MS
• Merrillville, IN
• Mesa-Apache Junction, AZ
• Mesquite, NV
• Mexicali, MX
• Mexico City
• Michigan City, IN
• Middlebury, VT
• Middlesbrough
• Middletown, PA
• Midland, TX
• Midpines, CA
• Międzyrzec Podlaski
• Międzyrzecz
• Międzywodzie
• Miedzyzdroje
• Miejsce Piastowe
• Miercurea Ciuc
• Milan Linate Airport
• Milan Malpensa Airport
• Milano Marittima
• Miles City, MT
• Milford, NY
• Milwaukee, WI
• Minneapolis, MN
• Mirabilandia
• Miranda de Ebro
• Mirto Crosia
• Misano Adriatico
• Mississauga, ON
• Missoula, MT
• Mitchell, SD
• Mladá Boleslav
• Mobridge, SD
• Modesto, CA
• Mohyliv-Podilskyi
• Moi busstasjon
• Moita da Serra
• Mola di Bari
• Molina di Fiemme
• Mönchengladbach
• Mongrassano
• Monmouth, IL
• Monroeville, PA
• Montallegro
• Montbéliard
• Monte Gordo
• Montecassiano
• Montecatini Terme
• Montecorice
• Montecosaro
• Montemarano
• Monterrey, MX
• Montes Claros, MG
• Montgomery Creek, CA
• Montgomery, AL
• Monticello, UT
• Montoursville, PA
• Montpelier, VT
• Montpellier
• Montreal, QC
• Monument, CO
• Moorhead, MN
• Moose Lake, MN
• Moravský Krumlov
• Morelia, Michoacan
• Morgan City, LA
• Morgantown, WV
• Morra de Sanctis
• Moses Lake, WA
• Mossoró, RN
• Moultrie, GA
• Moundville, AL
• Mount Clemens, MI
• Mount Gilead, OH
• Mount Laurel, NJ
• Mount Morris, NY
• Mount Pleasant, IA
• Mount Pleasant, TX
• Mount Pocono, PA
• Mount Tremper, NY
• Mount Vernon, IL
• Mount Vernon, OH
• Mount Vernon, WA
• Mountain Home, ID
• Mrkonjić Grad
• Mt Eaton, OH
• Mühldorf am Inn
• Munich International Airport
• Muñogalindo
• Münster / Osnabrück Airport
• Murfreesboro, TN
• Muscatine, IA
• Muskegon, MI
• Mustafakemalpaşa
• Muzaffarnagar
• Myrtle Beach, SC
• Mysłakowice
• Nacogdoches, TX
• Nagykanizsa
• Nakło nad Notecią
• Naperville, IL
• Naples Airport
• Naranjos Amatlán, Veracruz
• Nashville, TN
• Natchez, MS
• Naturum Laponia, Gällivare
• Nauheim (b. Groß-Gerau)
• Navamorales
• Navasota, TX
• Navojoa, Sonora
• Neckargemünd
• Neheim-Hüsten
• Nelsonville, OH
• Neuenburg am Rhein
• Neumarkt am Wallersee
• Neunkirchen
• Neustrelitz
• New Baltimore, MI
• New Bern, NC
• New Britain, CT
• New Brunswick, NJ
• New Carrollton, MD
• New Castle, PA
• New Haven, CT
• New Iberia, LA
• New London, CT
• New Meadows, ID
• New Orleans, LA
• New Paltz, NY
• New Philadelphia, OH
• New Smyrna Beach, FL
• New York, NY
• Newburgh, NY
• Newcastle upon Tyne
• Newcomerstown, OH
• Newport (South Wales)
• Newport, AR
• Newtown Forbes
• Niagara Falls, NY
• Niagara Falls, ON
• Nitrianske Pravno
• Nocera Inferiore
• Nocera marina
• Nocera Terinese
• Norcross, GA
• Nordkirchen-Capelle
• Norfolk-Virginia Beach, VA
• Norfolk, NE
• Norfolk, VA
• Norristown, PA
• North Augusta, SC
• North Bend, NE
• North Bend, WA
• North Branch, MN
• North Charleston, SC
• North East, MD
• North Elba, NY
• North Hollywood, CA
• North Petherton
• North Plains, OR
• North Platte, NE
• Northampton
• Northampton, MA
• Nova Gradiška
• Nova Pazova
• Nova Topola
• Novi Senkovac
• Novi Travnik
• Novi Vinodolski
• Novo Selište
• Novohrad-Volyns'kyi
• Novoseljani
• Novoselo Trnovačko
• Noyelles-Godault
• Nuevo Ideal, Durango
• Nuevo Laredo, MX
• Nykøbing Falster
• Nykøbing Mors
• o'Rourke's Cross
• O'Brien, OR
• Oak Hall, VA
• Oakland / Berkeley / East Bay, CA
• Oberboihingen
• Ocampo, Durango
• Oceanside, CA
• Odorheiu Secuiesc
• Ogallala, NE
• Oglesby, IL
• Ogliastretti
• Okanogan, WA
• Oklahoma City, OK
• Olive Township, OH
• Oliveira do Hospital
• Olympia, WA
• Oneonta, NY
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Exploring temporal heterogeneity in an intercity travel network: A comparative study between weekdays and holidays in China

• Research Article
• Published: 26 December 2020
• Volume 30 , pages 1943–1962, ( 2020 )

Cite this article

• Tao Li 1 , 2 ,
• Jiaoe Wang 2 , 3 ,
• Jie Huang 2 &
• Xingchuan Gao 2  

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25 Citations

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A largely unexplored application of “Big Data” in urban contexts is using human mobility data to study temporal heterogeneity in intercity travel networks. Hence, this paper explores China’s intercity travel patterns and their dynamics, with a comparison between weekdays and holidays, to contribute to our understanding of these phenomena. Using passenger travel data inferred from Tencent Location Big Data during weekdays (April 11–15, 2016) and National Golden Week (October 1–7, 2016), we compare the spatial patterns of Chinese intercity travel on weekdays and during Golden Week. The results show that the average daily intercity travel during Golden Week is significantly higher than that during weekdays, but the travel distance and degree of network clustering are significantly lower. This indicates temporal heterogeneity in mapping the intercity travel network. On weekdays, the three major cities of Beijing, Shanghai, and Guangzhou take prominent core positions, while cities that are tourism destinations or transportation hubs are more attractive during Golden Week. The reasons behind these findings can be explained by geographical proximity, administrative division (proximity of cultural and policy systems), travel distance, and travel purposes.

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Northwest Land and Resource Research Center, Shaanxi Normal University, Xi’an, 710119, China

Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China

Tao Li, Jiaoe Wang, Jie Huang & Xingchuan Gao

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Foundation: National Natural Science Foundation of China, No. 41501120, No. 41722103; The Fundamental Research Funds for the Central Universities, SNNU, No. 18SZYB01; China Postdoctoral Science Foundation, No. 2020M670429

Author: Li Tao, PhD and Associate Professor, specialized in transport geography.

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Li, T., Wang, J., Huang, J. et al. Exploring temporal heterogeneity in an intercity travel network: A comparative study between weekdays and holidays in China. J. Geogr. Sci. 30 , 1943–1962 (2020). https://doi.org/10.1007/s11442-020-1821-9

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Issue Date : December 2020

DOI : https://doi.org/10.1007/s11442-020-1821-9

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France's SNCF to offer high-speed passenger links in Italy

French national rail operator SNCF said Wednesday it planned to offer high-speed passenger services in neighbouring Italy from 2026, competing with rival Trenitalia on its home turf.

"Italy is a natural market for high speed, with 56 million passengers per year," said Alain Krakovitch, head of intercity TGV (high-speed train) services at SNCF Voyageurs.

"But it's a market that's yet to mature, with many passengers still to bring in."

SNCF plans eventually to offer nine daily return services between Turin, Milan, Rome and Naples, as well as four Turin-Venice trains.

The French heavyweight moved into Spain with intercity services in 2021, and has seen Trenitalia itself look to pick up business in France on the profitable Paris-Lyon line.

SNCF hopes to claim 15 percent of the Italian high-speed market within a decade, or 10 million passengers per year.

In Spain, it has built its passenger base to 20 percent with its low-cost Ouigo service.

European business already accounts for one-third of SNCF's annual high-speed revenues, or three billion euros ($3.2 billion).

The publicly owned firm is also responding to explosive demand for rail travel at home in France.

agu/tgb/sjw/jj

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An easy guide to European train travel

H ere’s a fun fact for anyone looking to be more eco in their explorations to the continent this summer: taking the train instead of flying can cut the carbon footprint of your foray by up to 90 per cent. What’s more, if you follow our headache-free hacks, it needn’t be as costly or complicated as you’d imagine – and we guarantee that your trip will be all the more magical for it.

Trust us, it’s easy 

A world away from the queues and stresses of airports, travelling by train in Europe is a breeze by comparison. After a speedy, centre-to-centre Eurostar from London to Brussels, Paris or Amsterdam, the continent’s rail lines are a map of possibilities, making their way to the north of Norway, the banks of the Bosphorus in Istanbul, the far south of Spain and thousands of exciting stops in between. Convenient online booking, fast trains, reasonably priced fares and incredible landscapes await — as does a journey with no carbon conscience.   

Book in advance 

Booking is one area where you have to think the same as when you’re flying. For the broadest availability and cheapest fares, book early. Most services open three to four months before travel, with Eurostar bookable six to eight months ahead. While restrictions vary, seat reservations are always a good idea and mandatory on high-speed and premium services in many countries. Peak season sees many popular trains, such as TGV Lyria trains from Paris to Swiss cities and Nightjet sleepers, sell out well ahead. Advance bookings will also cut the cost of many inter-city and regional trains on which you can’t reserve seats. Trainline.com is handy for many international journeys, but compare the booking sites for the national carriers, too. 

Pass us a pass 

An Interrail pass to explore Europe as a continent, or individual countries, still works as a system largely as it has done for generations, offering flexible, unlimited travel for the duration of the pass. Usually, it is easiest to access via apps on your phone but they’re not always the best option: point-to-point fares can work out cheaper than a pass, especially if booked far in advance, and some fast trains have prohibitive supplements and restricted availability, especially in high season, so check whether a pass will even grant you access if you're travelling at peak times on popular routes. But, in addition to the unbeatable sense of freedom, Interrail does also offer free or discounted travel on many ferries, cable cars, museum entry fees and more.  

Try a night on the rails 

The new generation of night trains has transformed cross-continent travel. Nightjet routes, radiating out of Austria and run by its national railway (ÖBB), offer up-to-date, comfy couchettes and swanky sleepers, some of which come with showers. Newer trains running between Hamburg and Vienna offer innovative private mini-suites — cabins for one — with more coming soon on other routes. There are other fantastic sleeper trains across Europe — try Zurich in Switzerland to Ljubljana in Slovenia for a nighttime odyssey of moonlit rivers and snowy peaks, or our very own Caledonian Sleeper from London Euston to the Scottish Highlands. 

Dining cars and in-carriage picnics 

In addition to their excellent network of comfortable, affordable trains, Czech Railjet services are among Europe’s best bets for meals in a well-stocked dining car. Sirloin, dumplings and cranberries washed down with a draft Czech beer or Bohemian sparkling wine sound nice? Look for good value happy hour prices. Polish, Swiss and Austrian inter-city trains and Spanish start-up Iryo are also reliable choices for eating well on the rails. There’s always the option for in-seat picnics: considerate passengers might like to avoid particularly fragrant cheeses and scattering those baguette crumbs. 

Allow extra time 

Delays happen, so plan for them and allow plenty of time when connecting. They’re rarely a big drama: most key routes offer many services daily, so you’re unlikely to fall far behind in your plans. Night trains, with their complex journeys and addition or removal of carriages along the route, can be especially prone to slowness. Wherever you are, if your connection hits the buffers, track down the guard on your train to get advice on whether you can travel on the next service or if you need a new ticket. Make sure you have travel insurance, just in case. A lot of the apps, such as Rail Planner or Omio, will let you reconfigure cascading connections in no time. 

Branch out and gaze out 

One of the loveliest parts of travelling by train is finding yourself on a quiet branch line and seeing unexpectedly beautiful scenery. Little-known treats are everywhere — the slower route from Florence to Rome via Perugia passes a succession of Umbrian hill towns. In contrast, the route from Barcelona to the French border at Latour de Carol is three hours of rolling Pyrenean scenery. Travelling down the Moselle in Germany from Koblenz to Trier is a delicious detour into this corner of Europe’s spellbinding wine country. Try detouring off the main line in Slovenia to enjoy views of the Julian Alps, the Soča River and glimpses of Lake Bled on the lovely trundler from Jesenice to Nova Gorica on the Italian frontier.   

Pack light on clothes, heavy on gadgetry 

The best packing strategy remains to pack as light as possible — lugging bulky bags on to crowded trains is never fun — but make sure you have everything you need to stay connected. Wifi is increasingly common, if often unreliable. While many trains come with power points, a battery pack is a helpful back-up and sound-cancelling headphones can double as earplugs if you share a couchette. For an extra-rewarding experience, take them off to chat with friendly fellow passengers; they are probably as happy as you not to be on a crowded plane. 

Tom Hall is a writer and rail obsessive at Lonely Planet . His happy place is pulling into Zurich Hauptbahnhof in summer, knowing a dip in the Limmat River is but a few minutes’ stroll away. He has written and contributed to many Lonely Planet titles, including Flight-Free Europe, Guide to Train Travel in Europe and Best in Travel . He has also contributed to the forthcoming Lonely Planet’s Amazing Train Journeys of the World .   

Register now for one of the Evening Standard’s newsletters. From a daily news briefing to Homes & Property insights, plus lifestyle, going out, offers and more. For the best stories in your inbox, click here .

South Korea Travel Guide

Last Updated: July 17, 2023

Though South Korea is small (about the size of the US state of Indiana), it punches well above its weight in terms of things to see and do. Boasting a vibrant culture, incredible history, natural beauty, delicious food, and a wild nightlife, it’s home to both major cities and untouched nature, offering something for every traveler.

Seoul, the capital city and fourth-largest metropolitan area in the world (over half the country’s population of 50 million is concentrated here), is a lively hub for food lovers and partying. But while it gets all the attention, there is much more to explore, including 22 national parks, lush Jeju Island, and the infamous Demilitarized Zone (DMZ) bordering North Korea.

Best of all, since South Korea is a manageable size, you can see a good portion of it in a limited amount of time. The transportation here is modern, clean, and efficient, so it’s easy to get around quickly.

The country is also a foodie’s paradise, with cheap street food and delicious dishes like bibimbap, kimchi, and the famed Korean barbecue.

It’s one of my favorite countries in the world and one that I think is super under the radar and often overlooked by travelers. You never see the tourist crowds found in other Asian countries.

This travel guide to South Korea can help you plan your trip, save money, and make the most of your visit.

Table of Contents

• Things to See and Do
• Typical Costs
• Suggested Budget
• Money-Saving Tips
• Where to Stay
• How to Get Around
• How to Stay Safe
• Best Places to Book Your Trip
• Related Blogs on South Korea

Top 5 Things to See and Do in South Korea

1. Explore Seoul

Korea’s capital has a little bit of everything. It’s a bustling metropolis and global technology hub, with sleek and modern neighborhoods like Gangnam and iconic sights like the Lotte World Tower, the sixth-tallest building in the world. Yet there is a lot of history here too, including many museums, palaces, and temples, among them five UNESCO World Heritage Sites. When you’re done exploring for the day, Seoul has a robust street food scene, countless trendy restaurants, and fast-paced, soju-driven nightlife. You could easily spend weeks here and never get bored.

2. Tour the DMZ

The Demilitarized Zone (DMZ) separates North and South Korea and, despite the name, is the most militarized border in the world. You can only visit the Joint Security Area (JSA), which has military personnel from both sides, on a guided tour, but it’s a unique experience and an important way to learn about this ongoing conflict (the war started in 1950 and has not officially ended). On the tour, you’ll be able to actually stand in North Korea, visit the Third Tunnel of Aggression (which North Korea dug to sneak soldiers across the border), see the Freedom Bridge, and catch glimpses of North Korea from the Unification Observatory. Guided tours of the DMZ start from 80,000 KRW.

3. Visit Jeju Island

This volcanic, semitropical island is a popular domestic vacation spot. It’s accessible via cheap daily flights from Seoul that take just one hour. Known as “the Hawaii of Korea,” it’s a natural paradise, home to the tallest mountain in Korea (Mount Hallasan), lava tubes, beautiful beaches, and countless hiking and walking trails. Other attractions include visiting mythic Jeju Stone Park, wandering the Yeomiji Botanical Gardens, and watching the haenyeo divers — women who dive without any protective equipment to gather underwater treasures like shellfish and seaweed, which they then sell on the beaches. You can visit the Jeju Haenyeo Museum as well to learn more about this cultural practice that dates back centuries.

4. Sing karaoke

Known as noraebang , this is a cultural phenomenon and something worth experiencing at least once while visiting Korea. While the karaoke machine was originally invented in Japan, Koreans have adopted the pastime and made it their own. Here, you rent out a private room with a group of friends (instead of singing in a public bar, as is often the case in Western countries). Pricing is determined by the hour, with rates varying wildly depending on the number of people, time of day, day of the week, and whether snacks and drinks are included. Average group karaoke rates range from 5,000 to 15,000 KRW.

5. Step back in time at a hanok village

Other things to see and do in south korea, 1. visit changdeokgung palace.

One of the Joseon dynasty’s Five Grand Palaces, this 15th-century complex in Seoul was built in harmony with the natural environment at the foot of Bugaksan Mountain. Changdeokgung, or “Palace of Prospering Virtue,” was the main royal residence for 13 kings over the course of three centuries. The complex sprawls over 110 acres, 60% of which is taken up by the beautiful Huwon Secret Garden, home to over a hundred species of trees, flowers, and other plants (some of the trees here are over 300 years old!). The main draw is wandering around the exterior, with its restored buildings and gates, though you can also go inside Injeongjeon Hall, the palace’s throne room. Admission to the complex is 3,000 KRW; the Secret Garden is an additional 5,000 KRW. There are guided tours in English as well.

2. Explore Busan

Korea’s second-largest city is located just two hours from Seoul on the KTX high-speed bullet train. A coastal city, Busan boasts great beaches, such as Haeundae Beach, with its miles of sand, and Gwangalli Beach, known for its sunsets. Gamcheon Culture Village, the “mural village of Korea,” is a hillside neighborhood rich in street art and covered in murals, and nearly all the houses are painted bright colors. It’s a great place to wander around for a few hours, popping into the unique shops, cafés, and restaurants.

3. See the National Museum of Korea

If you visit only one museum in Korea, make it this one. Located in Seoul, it covers all aspects of Korean culture, art, and history, from prehistory to the early modern era. It also contains many national treasures and artifacts that have been designated as having special importance and value in Korean culture and history. Some of the most important ones include the sixth-century inscribed Bukhansan Monument, detailing military expansions; sixth-century gilt-bronze Buddhist statues; and the 10-story Gyeongcheonsa Pagoda, which dates to the 14th century. Don’t miss the exterior gardens, which feature indigenous plants, reflecting pools, and traditional Korean sculptures and lanterns. Admission to the main exhibitions and children’s museum is free.

4. Take a food tour

As a foodie, learning about a culture through its food is one of my favorite things to do while traveling. Korea has an incredible variety of amazing dishes to try, as well as a bustling (and delicious) street food scene. Taking a food tour with an experienced guide is one of the best ways to gain a deeper understanding of Korean cuisine. O’ngo Food offers a variety of tours in Seoul, Busan, Jeonju, and Jeju, with prices starting from 70,000 KRW per person.

5. Visit Gyeongbokgung Palace

Originally built in the 14th century by the kings of the Joseon dynasty, this palace in Seoul served as the seat of the government for two hundred years until it was destroyed by a fire and abandoned for centuries. Since the 19th century (and still today), it has been undergoing renovations to restore the complex to its former glory. It is considered the most stunning of all five royal palaces in Seoul, featuring grand gates, open courtyards, and terracotta-topped buildings set against the backdrop of Mount Bugak. In addition to wandering through the complex, you can also go into the many administrative halls and residential chambers set up to resemble the palace’s heyday. You can watch the changing-of-the-guard ceremony as well, every day except Monday. The National Palace Museum and the National Folk Museum are also located in the complex. Admission is 3,000 KRW.

6. See the cherry blossoms

While cherry blossoms are often associated with Japan, festivities surrounding the blooms are incredibly popular in Korea as well. Here, the season runs from late March to late April, with many festivals throughout the country. Just be prepared for crowds at the more popular ones, like the Yeouido Cherry Blossom Festival in Seoul.

7. Try taekwondo

Korean’s native martial art, taekwondo, is characterized by high kicks and punches and, like all such disciplines, emphasizes mental training. An Olympic event since 2000, taekwondo has only grown in popularity in recent years and is a point of pride in Korean culture. Kang’s Global Taekwondo in Seoul offers classes to adults and foreigners that cost around 43,000 KRW for one hour.

8. Learn to cook classic Korean foods

If you’d like to take your knowledge of Korean food one step further, take a cooking class, where you’ll learn to prepare classics like bibimbap, kimchi, bulgogi, and Korean pancakes. Hello K Cooking in Seoul offers a class where you’ll learn how to cook three main dishes and one stew — recipes and skills that you can bring home with you. Classes are 107,000 KRW.

9. Go hiking

Korea is an incredibly mountainous country, so hiking is a favorite pastime for locals. Be sure to immerse yourself in nature while visiting this lush land. There are even hiking spots near the bigger cities if you don’t have enough time or don’t want to venture too far afield. Bukhansan National Park, just outside Seoul, is a popular place to go hiking, offering panoramic views over the capital (expect crowds due to its proximity to the city, though). Yet with 22 national parks spread across the country, there are plenty of opportunities to escape the crowds (including lots of guided hikes if you don’t want to organize one yourself). For a multiday hike, the Jirisan Ridge Trek in Jirisan National Park is one of the most famous — a four-day walk from mountain shelter to mountain shelter.

10. Wander around Seoul Olympic Park

In 1988, Seoul hosted the Summer Olympics, which was only the second time the summer games had been held in Asia (the first was in Tokyo in 1964). Today, you can visit the massive park where the games were staged, and while Olympic Park does have many sports facilities, there’s much more to explore here as well. The park is divided into four sections, focusing on the arts, history, nature, and sports. In the arts section, you’ll find the SOMA Museum of Art and a park with over 200 sculptures, while in the history section, you can see the third-century defensive Mongchontoseong Earthen Fortifications, excavated dugout huts and storage pits left in the state in which they were uncovered. You can easily spend an entire afternoon here. Admission to the park is free.

11. Discover Jirisan National Park

Located in the southern part of the country (Namwon is the nearest city), this park is named after Jirisan (Mt. Jiri for short), the tallest mountain on mainland Korea. As it’s South Korea’s first national park (as well as its largest), hiking trails and cultural sites abound. You can visit seven major Buddhist temples and see several of Korea’s national treasures of ancient carved stonework from the seventh to the tenth centuries. One of the most important sites here is Samseonggung, or Three Sages Palace, a mountainside shrine dedicated to the legendary founders of Korea. Admission to the park is 1,600 KRW.

South Korea Travel Costs

Cheap hotel rooms start at 28,000 KRW for a room that sleeps one, while a double room generally costs at least 40,000 KRW. Expect basic amenities like Wi-Fi, a TV, air conditioning, and an electric teapot. Breakfast is usually not included at budget hotels.

Airbnb is available around the country, with private rooms starting at 25,000-30,000 KRW. For an entire home or apartment, expect to pay at least 50,000-70,000 KRW per night.

While wild camping is illegal in Korea, there are plenty of campgrounds should you want to pitch a tent. Expect to pay 7,000-20,000 KRW for a plot with access to bathroom and shower facilities, and usually even Wi-Fi.

Food – Korean cuisine has developed its own traditions and flavors over the centuries, with a unique emphasis on using uncooked, fermented, and pickled vegetables. Traditional Korean meals are often composed of a variety of side dishes, eaten with short-grain rice. A meal isn’t considered complete unless there’s kimchi on the table.

Common dishes include bulgogi (marinated, grilled beef), samgye-tang (chicken and ginseng soup), bibimbap (a mixed rice bowl), chap chae (a glass noodle dish), and many other noodle and rice dishes. Popular street foods include hotteok (a sweet, filled pancake), tteokbokki (spicy cylindrical rice cakes), and bungeo-ppang (a fish-shaped pastry filled with red bean paste).

Dining out in South Korea is relatively inexpensive. A meal at a casual restaurant serving traditional Korean food is around 9,000-15,000 KRW, while a three-course meal at a mid-range restaurant is around 25,000-30,000 KRW. Expect higher prices in larger cities.

Western food is more expensive. Expect to pay at least 20,000 KRW for a pasta dish at an Italian restaurant.

In terms of fast food, a combo meal (think McDonald’s) is around 7,000 KRW, while a burger is around 4,500 KRW. A typical Korean street food dish is 1,500-3,000 KRW.

A pint of beer is 4,000-5,000 KRW, a glass of wine is 6,000 KRW and up, and a cocktail is 7,000 KRW and up. A latte or cappuccino is 5,000 KRW.

If you cook your own food, expect to pay 50,000-70,000 KRW per week for basic staples like rice, pasta, vegetables, and some meat. Shopping at local markets is the best way to get great fresh produce for cheap.

Backpacking South Korea: Suggested Budgets

On a backpacking budget of 75,000 KRW per day, you can stay in a hostel dorm, cook all your meals, use public transportation and intercity buses to get around, skip the alcohol, and do mostly free activities like walking tours and hiking.

On a mid-range budget of 135,000 KRW per day, you can stay in a private Airbnb or cheap hotel, eat out for most meals at casual restaurants, enjoy a few drinks, take the occasional taxi as well as trains between cities, and do more paid activities like museum visits and food tours.

On a “luxury” budget of 255,000 KRW or more per day, you can stay in a nicer hotel or entire Airbnb apartment, eat out pretty much anywhere you want, drink at the bar, get a high-speed rail pass, and do as many guided tours and activities as you want. This is just the ground floor for luxury, though. The sky is the limit!

You can use the chart below to get an idea of how much you need to budget daily. Keep in mind these are daily averages — some days you’ll spend more, some days less (you might spend less every day). We just want to give you a general idea of how to make your budget. Prices are in KRW.

South Korea Travel Guide: Money-Saving Tips

I find South Korea to be one of the best value countries out there. It’s a really affordable place to visit. Accommodation can add up but food and drinks are generally cheap. Here are some ways to save money when you travel around South Korea:

• Visit the free attractions – With countless museums, shrines, temples, historic neighborhoods, and parks, Korea is filled with opportunities to become immersed in its culture. Many of the nation’s museums and cultural attractions are free, so don’t pass them up!
• Purchase a KORAIL Pass – If you want to travel by train, getting a rail pass is the most economical way to do so. You’ll get unlimited train travel for the time period you choose (2-5-day increments). Prices start at 121,000 KRW.
• Get a transit pass – Most major cities in Korea offer a day pass for public transit, which means great savings if you plan to hop around using buses and subways. Seoul’s day pass costs 15,000 KRW, though the longer you stay, the more you’ll save (a seven-day pass is 64,500 KRW).
• Buy a city pass – If you plan on visiting a lot of attractions, buy a city pass . Seoul and Busan both offer ones that include admission to popular sights, a transit pass, and discounts to restaurants and other attractions. A one-day pass starts at 33,000 KRW.
• Eat from the convenience stores – Convenience stores in Korea offer not only snacks and drinks but prepared boxed meals and cheap alcohol. If you’re on a tight budget, shop in those.
• Take the bus – While the trains are fun, the cheapest way to get around Korea is by bus. They take longer but are much cheaper, so if you have the time, opt for long-distance buses. Just show up at the bus station to reserve your tickets in advance, as most websites and apps are in Korean.
• Stay with a local – Couchsurfing lets you stay with a local for free, cutting your accommodation costs drastically. You’ll get to spend time with someone who can share their tips and advice in exchange for your own travel stories and culture. You can also use the app to meet people for activities (coffee, museum visits, etc.) if you don’t feel comfortable staying with a stranger.
• Drink like the locals – Soju, the national alcohol of Korea, is incredibly cheap, as is domestic beer. Just be careful to not let it sneak up on you — both monetarily and physically. Korea’s drinking culture is infamous!
• Stay in capsule hotels – If you don’t want to Couchsurf or stay in hostels but still want to save money, capsule or pod hotels are great options. These offer just what you need to sleep (a small, basic pod) yet can be surprisingly comfy and much more affordable than a traditional hotel. Prices start as low as 45,000 KRW per night.
• Bring a water bottle – The tap water here is safe to drink, so bring a reusable water bottle to save money and reduce your plastic use. LifeStraw is my go-to brand, as its bottles have built-in filters to ensure that your water is always clean and safe.

Where to Stay in South Korea

South Korea has plenty of budget-friendly hostels and guesthouses. Here are some of my recommended places to stay when you visit:

• Time Travelers Relax Guesthouse (Seoul)
• Zzzip Guesthouse (Seoul)
• Time Travelers party Hostel (Seoul)
• INSIDE Busan (Busan)
• Jeju Hiking Inn (Jeju)
• Backpacker’s Home (Jeju)

How to Get Around South Korea

Bus – Taking a long-distance bus is the cheapest and most popular way to get around the country. There are two types: express (which makes few to no stops) and intercity (which travels between smaller destinations and makes more stops).

Your best bet for reserving tickets in advance is to go directly to the bus terminal, as most bus websites and booking apps are in Korean and only accept Korean credit or debit cards.

Pricing depends on what class ticket you choose: standard, luxury, or premium. The four-hour bus ride from Seoul to Busan costs around 36,000 KRW for a standard ticket, Incheon to Busan takes just over four hours and costs 38,000 KRW, and Seoul to Daegu is 29,000 KRW and takes just under four hours.

Train – South Korea has a robust train system that can take you all over the country. Korean Train Express (KTX) is the country’s bullet train, regularly running at speeds up to 305 kilometers (190 miles) per hour. However, these only go between major cities, have limited schedules, and are more expensive, so KTX may not always be the most convenient choice.

KORAIL (the national railway service) operates slower-speed, intercity trains that offer a wider range of schedules and destination choices. You can also get the unlimited KORAIL Pass, which is offered exclusively to international tourists. A two-day adult pass is 121,000 KRW; a five-day adult pass is 210,000 KRW.

As a comparison of the two train types: the journey from Seoul to Busan on a KRX train costs around 90,000 KRW and takes 2.5 hours, while on a regular intercity train, it takes 5.5 hours and costs 47,500 KRW.

The further out you book, the cheaper KTX train prices get, while intercity prices stay about the same. You can book up to a year in advance.

Flying – South Korea is so small that flying around the country doesn’t really make sense. Trains can get you anywhere pretty quickly. However, if you’re very pressed for time and have cash to burn, there are a few budget airlines offering domestic flights between major cities. Most are around one hour long.

The flight from Seoul to Busan is around 30,500 KRW, Seoul to Jeju is 55,000 KRW, and Busan to Jeju is 22,000 KRW. However, you can find flights even cheaper when you book further in advance.

Low-cost airlines in South Korea include the following:

Car rental – Renting a car isn’t incredibly cheap in South Korea. However, it is one of the best ways to explore all the natural wonders that the country has to offer, many of which are inaccessible by public transportation. Expect to pay around 50,000-55,000 KRW per day on a multiday rental. Drivers need to be at least 21 years old.

When to Go to South Korea

Generally, the best times to visit South Korea are March-May and September-November. During these periods, the weather is mild, with temperatures of 10-24°C (50-75°F); prices for accommodation and transportation are lower; and there are fewer crowds.

In the spring, the cherry blossoms are in bloom all over the country, while the fall brings the beautiful colors of the changing leaves. Also, if you plan on doing a lot of hiking, the fall is the best time to visit.

The summer starts with monsoon season, from June through mid-July, and the rest of the summer is hot and humid in the cities (though it cools down in the mountains and along the coasts). Prices for accommodation are also very high during this time.

Winters in South Korea get very cold, with temperatures dipping as low as -6°C (21°F), so unless you plan on skiing, visiting from December through February might not be the best option (though the temples and landscapes look beautiful covered in snow).

How to Stay Safe in South Korea

South Korea is an incredibly safe place to backpack and travel around. Petty crime is rare here, though it never hurts to be cautious on public transportation and around popular tourist landmarks. Always keep your wallet and valuables secure and out of reach, just in case. Violent crime is even more rare.

Solo female travelers should feel safe here. However, the standard safety precautions apply as always. For specific tips, consult one of the many solo female travel blogs on the web.

While scams are super rare in South Korea, to avoid getting ripped off, you can check out this list of common travel scams to avoid .

When hiking, always bring water and sunscreen. Be sure to check the weather before you depart and dress accordingly.

Earthquakes occur regularly in the region, so it’s best to be prepared and download the Emergency Ready app, which the Korean government developed to provide information in English to foreign residents and tourists. It has all kinds of advice and tips for natural disasters, shows you where nearby emergency shelters are, and sends out warnings and notifications should a disaster occur.

If you do experience an emergency, dial 112 for assistance.

Always trust your gut instinct. Make copies of your personal documents, including your passport and ID, and forward your itinerary along to loved ones so they’ll know where you are.

South Korea Travel Guide: The Best Booking Resources

These are my favorite companies to use when I travel. They consistently have the best deals, offer world-class customer service and great value, and overall, are better than their competitors. They are the companies I use the most and are always the starting point in my search for travel deals.

• Skyscanner – Skyscanner is my favorite flight search engine. They search small websites and budget airlines that larger search sites tend to miss. They are hands down the number one place to start.
• Hostelworld – This is the best hostel accommodation site out there with the largest inventory, best search interface, and widest availability.
• Booking.com – The best all around booking site that constantly provides the cheapest and lowest rates. They have the widest selection of budget accommodation. In all my tests, they’ve always had the cheapest rates out of all the booking websites.
• Get Your Guide – Get Your Guide is a huge online marketplace for tours and excursions. They have tons of tour options available in cities all around the world, including everything from cooking classes, walking tours, street art lessons, and more!
• SafetyWing – Safety Wing offers convenient and affordable plans tailored to digital nomads and long-term travelers. They have cheap monthly plans, great customer service, and an easy-to-use claims process that makes it perfect for those on the road.
• LifeStraw – My go-to company for reusable water bottles with built-in filters so you can ensure your drinking water is always clean and safe.
• Unbound Merino – They make lightweight, durable, easy-to-clean travel clothing.
• Top Travel Credit Cards – Points are the best way to cut down travel expenses. Here’s my favorite point earning credit cards so you can get free travel!

South Korea Travel Guide: Related Articles

Want more info? Check out all the articles I’ve written on Asia travel and continue planning your trip:

The 5 Best Hotels in Singapore

The 7 Best Hotels in Bangkok

The 4 Best Hostels in Singapore

Where to Stay in Singapore: The Best Neighborhoods for Your Visit

The 13 Best Things to See and Do in Taipei

The 23 Best Things to Do in Hong Kong

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June 4, 2024

Amtrak celebrates accessibility upgrades at bay area stations.

Customers will benefit from Congressional investments

MARTINEZ, CALIF. – In partnership with the cities of Martinez, Hayward, Fremont and Oakland, Amtrak has completed accessibility improvements at its Bay Area stations. Customers can now enjoy a more accessible and comfortable experience at the Martinez , Hayward , Fremont , and Oakland-Coliseum Stations following the completion of $20.8 million in upgrades.

“We’re delivering a new era of rail while bringing greater accessibility to stations nationwide,” said Amtrak Vice President of Accessibility Dr. David Handera. “As we prioritize station accessibility throughout Amtrak, we are thrilled that these Bay Area stations can provide a welcoming and comfortable experience for all customers.”

Due largely to Federal investments, the improvements are part of Amtrak’s commitment to creating safer, more accessible facilities across its National Network through its ADA Stations Program. Since 2011, Amtrak has invested more than $870 million in upgrades at 124 stations across the country, providing a better travel experience for customers with disabilities.

Current Bay Area station upgrades include:

• Martinez Station : Investments of $8.5 million were made to the Martinez Station which serves the Capitol Corridor , Amtrak San Joaquins , Coast Starlight and California Zephyr . Updates include a resurfaced platform with tactile warning surfaces along the platform edge so passengers with vision disabilities can safely navigate public spaces. The Martinez Station also offers an accessible path from the bus drop off, through the station and onto the platform. Customers can also leverage renovated restrooms, a new ticket counter, and other modifications that better serve the community.
• Hayward Station : Investments of $5.6 million were made to the Hayward Station which serves Capitol Corridor trains. The station now offers a new platform with increased space and a crossing to connect the platforms. The station also offers energy efficient LED light fixtures and new station signage that improves accessibility.
• Fremont Station : Investments of $4.2 million were made to the Fremont Station which serves Capitol Corridor trains. The new design provides a new platform and additional space on the station-side platform where customers can access the track in both directions. The station also offers energy efficient LED light fixtures and new station signage that improves accessibility.
• Oakland-Coliseum Station : Investments of $2.5 million were made to the Oakland-Coliseum Station, which serves Capitol Corridor trains. The design includes a resurfaced platform with tactile warning so passengers with vision disabilities can safely navigate public spaces. Signage, trash receptacles and pedestrian pathways also provide better access to the local community.

“As a senior member of the Transportation and Infrastructure Committee, I was proud to be an original cosponsor of the Infrastructure Investment and Jobs Act of 2021,” said California Congressman John Garamendi (D). “The Biden Administration and congressional Democrats have made a generational investment to create good-paying union jobs, build more resilient infrastructure that will address the climate crisis, and modernizing our crumbling infrastructure with American materials and workers. I am thrilled that these funds have improved the Martinez Amtrak station for all residents of California’s 8 th Congressional District.”

“I applaud Amtrak for leading the way in ensuring our public transit is inclusive for everyone,” said U.S. Senator Laphonza Butler (CA – D). “Federal investments like this demonstrate that rail travel is safe and accessible for Californians.”

“We applaud Amtrak’s ADA Project initiative to improve accessibility along the Capitol Corridor route,” said Capitol Corridor Managing Director Robert Padgette. “These efforts make it easier for passengers to navigate stations and platforms prior to boarding our trains and allows for a more inclusive travel experience.”

Accessibility upgrades and improvement projects across the National Network aim to provide a safe, efficient, and comfortable travel experience for customers with disabilities. The improvements include repairs and upgrades to platforms, ramps and sidewalks, and renovations to entranceways and restrooms, with 20 stations brought into compliance with the Americans with Disabilities Act last year. Another 35 stations are targeted for completion this fiscal year as Amtrak works toward 100% completion by 2029 .

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Managed by the Capitol Corridor Joint Powers Authority (CCJPA), the Capitol Corridor is an intercity rail service connecting the most economically vibrant urban centers in Northern California – from Sacramento to Silicon Valley, and including San Francisco, Oakland, and Berkeley. With free Wi-Fi on board, Capitol Corridor trains provide a convenient, reliable, and comfortable alternative to the congested I-80, I-680, and I-880 freeways for more than 700,000 passengers a year. For more information, visit www.capitolcorridor.org .

About the San Joaquin Joint Powers Authority (SJJPA)

Since July 2015, SJJPA has been responsible for the management and administration of Amtrak San Joaquins. SJJPA is governed by Board Members representing each of the ten (10) Member Agencies along the 365-mile San Joaquins Corridor. For more information on SJJPA see www.sjjpa.com .

Amtrak San Joaquins is Amtrak’s 6th busiest route with 18 train stations throughout the Central Valley and Bay Area, providing a safe, comfortable and reliable way to travel throughout California. Amtrak San Joaquins is currently running six daily round-trips. In addition to the train service, Amtrak San Joaquins Thruway buses provide connecting service to 135 destinations in California and Nevada including Los Angeles, Santa Barbara, San Diego, Napa Valley, Las Vegas and Reno.

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President Biden Announces $8.2 Billion in New Grants for High-Speed Rail and Pipeline of Projects Nationwide

Announcement includes 10 projects in 9 states ready for construction and 69 corridors across 44 states identified for future development through two grant programs funded by the Bipartisan Infrastructure Law

WASHINGTON, D.C. – The U.S. Department of Transportation’s Federal Railroad Administration (FRA) today announced that it has awarded $8.2 billion for 10 passenger rail projects across the country while announcing corridor planning activities that will impact every region nationwide. This unprecedented investment in America’s nationwide intercity passenger rail network builds on a $16.4 billion investment announced last month for 25 projects of national significance along America’s busiest rail corridor. To date, the Biden-Harris Administration has announced nearly $30 billion in investments for our nation’s rail system. 

Projects announced through the Federal State Partnership for Intercity Passenger Rail (Fed-State National) Program will advance two high-speed rail corridors and fund improvements to existing rail corridors for expanded service and performance. These investments will:  

• Help deliver high-speed rail service in California's Central Valley
• Create a brand-new high-speed rail corridor between Las Vegas, Nevada, and southern California, serving an estimated 11 million passengers annually 
• Make major upgrades to existing conventional rail corridors to better connect Northern Virginia and the Southeast with the Northeast Corridor
• Expand and add frequencies to the Pennsylvania Keystone Corridor between Philadelphia and Pittsburgh
• Extend the Piedmont Corridor in North Carolina north, as part of a higher-speed connection between Raleigh and Richmond, Virginia 
• Invest in Chicago Union Station, as an initial step toward future improvements to the critical Midwest corridors hub
• Improve service in Maine, Montana, and Alaska

“Today, the Biden-Harris Administration takes another historic step to deliver the passenger rail system that Americans have been calling for – with $8.2 billion for faster, more reliable, expanded train service across the country,” said U.S. Transportation Secretary Pete Buttigieg . “With this funding, we’ll deliver America’s first high-speed rail on a route between Southern California and Las Vegas, complete major upgrades for riders in Virginia, North Carolina, Illinois, Pennsylvania, Maine, Montana, and Alaska, and announce a comprehensive plan that makes it easier to expand passenger rail lines in 44 states.”

At the same time, FRA is announcing 69 corridor selections across 44 states through the Corridor Identification and Development (Corridor ID) Program , which will drive future passenger rail expansion. 

Corridor ID, a new planning program made possible by President Biden’s Bipartisan Infrastructure Law, will help guide intercity passenger rail development throughout the country. This inaugural round of selections aims to upgrade 15 existing rail routes, add or extend service on 47 new routes, and advance 7 new high-speed rail projects, creating a pipeline of intercity passenger rail projects ready for implementation and future investment. FRA will work closely with states, transportation agencies, host and operating railroads, and local governments to develop and build passenger rail projects faster than ever before.

“President Biden’s Bipartisan Infrastructure Law gave us a once-in-a-generation opportunity to think smart and think big about the future of rail in America, and we are taking full advantage of the resources we have to advance world-class passenger rail services nationwide,” said FRA Administrator Amit Bose . “Today’s announcement is another step forward as we advance transformative projects that will carry Americans for decades to come and provide them with convenient, climate-friendly alternatives to congested roads and airports. We’re thinking about the future too with comprehensive and systematic planning efforts to transform the U.S. intercity passenger rail network now and in the years to come.”

Examples of planning and development activities selected through the Corridor ID program include:

• New high-speed rail service in the Cascadia High-Speed Rail Corridor between Oregon, Washington, and British Columbia
• New high-speed rail service between Dallas and Houston
• Daily, multi-frequency service from Chicago to Indianapolis 
• Increased frequencies from Chicago to Milwaukee to the Twin Cities, with an extension to Madison, Wisconsin
• Improved service and increased frequencies from Chicago to Detroit, with an extension to Windsor, providing a direct connection to Canada’s high-speed rail network 
• A comprehensive plan for the Chicago terminal and service chokepoints south of Lake Michigan benefiting all corridors and long-distance trains south and east of Chicago 
• New service between the Twin Cities and Duluth, Minnesota
• New service from Fort Collins to Pueblo, Colorado, with intermediate stops at Boulder, Denver, and Colorado Springs  
• New service between Phoenix and Tucson, Arizona, with multiple daily frequencies 
• New service connecting Baton Rouge and New Orleans, Louisiana  
• New connections between the Northeast Corridor and Northern Delaware and Reading and Scranton, Pennsylvania  
• Expanded connections and increased frequencies within California’s extensive conventional rail network  
• Expanded connections and service in Florida’s intercity rail network between the key travel markets of Tampa, Jacksonville, Orlando, and Miami 
• New service between Atlanta and Savannah, and from Atlanta to Nashville and Memphis via Chattanooga  
• Restoration of service between Chicago and Seattle, Washington, through multiple rural communities in North Dakota and Montana that are currently not served by passenger rail

Two years after signing the Bipartisan Infrastructure Law, President Biden has already announced the most significant investment in passenger rail since the creation of Amtrak, including billions in Federal-State Partnership for Intercity Passenger Rail grants for projects on America’s busiest rail corridor in the Northeast and for others nationwide. Coupled with rail investments announced earlier this year, including the new Railroad Crossing Elimination (RCE) program grants and Consolidated Rail Infrastructure and Safety Improvements (CRISI) grants, President Biden’s Investing in America Agenda is laying the foundation for the safe and modern rail network Americans need and deserve.

To view the full list of Fed-State National project selections and Corridor ID selections, please click here and here . 

Additional information about the Federal-State Partnership for Intercity Passenger Rail Program can be found here , while further information on the Corridor ID Program is available here .