Intercity Travel Research Articles

Analysis of the inter-city shared mobility system based on autonomous electric vehicles

While autonomous electric vehicles (AEVs) have been preliminarily implemented in shared travel services from both technical and theoretical perspectives, challenges such as dispersed fleets, limited service quality, and travel safety concerns have confined existing research to intra-city shared mobility, with few studies focusing on inter-city shared mobility for AEVs. With China’s metropolitan regions expanding and intercity travel rapidly increasing, examining the use of shared autonomous electric vehicles (SAEVs) for intercity travel is essential for future transportation systems. To address this issue, this study models the inter-city shared mobility problem utilizing mixed integer linear programming. The problem is defined on a directed graph and addressed using a variable neighborhood search algorithm. Numerical experiments are designed based on the actual shared mobility data between Yinchuan and Shizuishan, Ningxia Province, China. From the perspective of the operating platform, the potential influencing factors of the inter-city shared mobility system are analyzed, including passenger travel demand, fleet size, vehicle range, and the number of charging stations. The results demonstrate that increasing temporal and spatial imbalance in passenger travel demand and excessive fleet size will lead to lower total revenue of the operation platform. Conversely, within certain thresholds, increasing the number of charging stations, vehicle range, and fleet size will increase the total revenue. Continuing to increase the number of charging stations and vehicle range has no significant effect on total revenue and service rate but will lead to a waste of basic resources. The study is expected to provide a solution for building an inter-city shared mobility system based on SAEVs. By fully understanding the system’s limitations and advantages, we aim to provide a reference template for constructing future inter-city shared mobility systems.

Leveraging Battery-to-Battery In-motion Charging Technology to Support Intercity Travel for Electric Vehicles

Leveraging Battery-to-Battery In-motion Charging Technology to Support Intercity Travel for Electric Vehicles

Modeling Passengers’ Reserved Time Before High-Speed Rail Departure

The pre-departure reserved time (PDRV) for high-speed railway (HSR) passengers, which encompasses all the time between passengers leaving their origin and the departure of the HSR train they are going to take, is a crucial factor in planning intercity travel. Understanding how passengers select their PDRV is not only important for developing effective strategies to improve HSR efficiency but also for optimizing the integration between HSR hubs and urban transportation networks. However, analyzing passenger choice behavior regarding PDRV is complex due to numerous influencing factors. Despite this, few studies have explored how HSR passengers make their PDRV choices. This paper, using Nanjingnan Railway Station as a case study, presents a novel investigation into the PDRV choice behavior of HSR passengers. An integrated latent class model (LCM) and ordered probit model (OPM) are applied to identify the factors affecting passengers’ PDRV choices. The sample data are segmented based on individual characteristics using the LCM, and OPM models are then constructed for each segment to analyze PDRV choice behavior. The results reveal that several factors—such as travel purpose, the number of times passengers used HSR at Nanjingnan Station in the previous year, the duration of HSR travel, the number of companions, feeder trip duration, and departure time—significantly impact PDRV choices. The integrated LCM and OPM approach also uncovers choice heterogeneity among different passenger groups. These insights can serve as a valuable reference for forecasting HSR passenger demand and for designing integrated HSR hubs and urban transport systems.

Deciphering long-term evolutionary patterns in inter-city travel networks in South Korea: Growth and decline of cities in association with inter-city connections

This study delves into the long-term dynamics of inter-city travel networks in South Korea by scrutinizing forty years of origin-destination data from both railway and highway systems. We uncover a pattern of increasing disparity in travel demand, concentrating more within certain hub cities over time. This trend points to an escalation in the prominence of these hubs, which have strengthened their connections with each other, emerging as critical nodes in the travel network. Meanwhile, non-hub cities have witnessed a decline in both population size and travel demand. Interestingly, while both railways and highways share a common trajectory toward centralization around hubs, they serve distinct roles. Highways have primarily expanded to connect neighboring cities, enhancing regional accessibility. Conversely, railways have evolved to cater to the long-distance connectivity of widely dispersed hub cities, reinforcing the role of these cities as key inter-regional links. These findings carry important implications for urban development and spatial planning. The evidence suggests a shift toward the formation of mega-regions, defined by a network of interconnected hub cities. Understanding the growth patterns and evolving connections of these expansive urban areas provides critical insights for informed urban planning and policy-making, ensuring that future developments align with the shifting landscape of urban connectivity and growth.

Road Traffic Infrastructure Construction and Air Pollution Based on the Perspective of Spatial Spillover

Road traffic infrastructure construction is widely regarded as a solution to urban congestion and air pollution. Given the frequent use of non-highway roads for inter-city travel, it is plausible that such infrastructure projects could also improve air quality in neighboring regions. However, the spatial spillover effects of these projects on air pollution remain underexplored. This paper investigates the spatial impacts of road traffic infrastructure construction on urban air pollution. Using a spatial panel regression model, we analyze data from 273 cities in a period spanning 2008 to 2021. Our findings show that road infrastructure construction significantly reduces local air pollution, with results robust to concerns about endogeneity. Furthermore, we identify notable spatial spillover effects, primarily concentrated in adjacent cities. These findings suggest that the accessibility between central cities and their neighboring areas plays a critical role in shaping traffic patterns, air quality, and sustainable urban development. As a result, coordinated regional planning for road infrastructure could serve as an effective strategy to mitigate urban air pollution and promote sustainable growth.

Intercity travel mode choice behavior based on the extended theory of planned behavior

Intercity travel mode choice behavior based on the extended theory of planned behavior

Analyzing Operational Dynamics: Centralized Load Distribution and Suspended Wagons in Self‐Propelled Trains

ABSTRACTThis paper primarily focuses on the distribution of axial loads in railway networks. The analysis assesses the advantages and disadvantages of articulated trains. In addition, the perspectives and proposed solutions of academicians are analyzed. Simpack accurately models all aspects of this articulated train model. Subsequently, the program emulates the control system of the train. This study demonstrates a control system that utilizes a hydraulic actuator. The proposed model and control system actuator's dynamic response are evaluated according to EN14363 and UIC518 standards to validate the functionality of the component. The stability of a railway train, particularly when making turns, relies on the proper allocation of weight on the wheels and axles. This research investigates the hazards associated with the uneven distribution of loads in train wagons, particularly when navigating curving tracks. A train designed for intercity travel was constructed utilizing a specific control system. The discrepancy in axle load is mitigated by implementing a straightforward control method. The train's carriage, which is suspended without bogies, resulted in fluctuating axle load. A disparity in axle load was established by an actuator positioned between the wagons. The control mechanism minimized load disparity and regulated axle load.

Connect to green: High-speed rail network and firms’ environmental performance

High-speed rail (HSR) has completely revolutionized intercity travel, significantly impacting economic activities. Recent studies have increasingly focused on how HSR affects environmental pollution. Given China’s extensive HSR policy in recent years, we extend this discussion in the context of China, introducing several new dimensions. Firstly, by manually collecting the daily operating routes of each HSR line in China, we construct a dynamic, directed, and weighted HSR network and provide a detailed description of the topological evolution of Chinese HSR from 2007 to 2014. Secondly, by employing network theory algorithms, we develop a city-level HSR strength index. This approach diverges from the commonly used multi-period difference-in-differences (DID) specification, allowing us to better address heterogeneity and discontinuity issues in identifying HSR effects. Thirdly, by leveraging the specific structure of the HSR network, we analyze how cities are interconnected and, for the first time, discuss the impact of “HSR-catalyzed supervision pressure” on firms’ pollution performance. Our findings show that firms exposed to higher HSR service intensity are more likely to reduce their SO2 emissions, a result that remains robust across various checks and other pollutants. We propose an intercity interaction story, predicting that HSR facilitates spillovers among city groups, thereby increasing environmental supervision pressure from neighboring cities in the HSR network. In further empirical analysis, we identify three specific sources of supervision pressure: peer pressure, vertical pressure, and public pressure.

Discovering temporal-spatial features of jobs-housing relationship from a regional perspective: A nationwide study

The recent developments in regionalization have redefined the concept of jobs-housing relationship, calling for reexaminations from the regional perspective. This paper studies the temporal and spatial features of jobs-housing relationship and their relations with regional mobility and regional structure in 2258 Quxians (urban districts or rural counties) across China based on 49 months of cellular signaling data. Results show that jobs-housing relationship differ between city types and have seasonal cycles and yearly trends reflecting the rhythm and development of human activity. The temporal variations in jobs-housing relationship are affected by regional mobility, and larger intercity travel volume leads to lower balance level. The spatial variations in jobs-housing relationship are influenced by the form of regional structure, as measured using the Zipf scaling exponent. More polarized regions are less balanced with exceptions in underdeveloped regions. There is an underlying inflection point in jobs-housing relationship that is similar to its long-term average value and reflects regional market equilibrium. This paper contributes to existing literature by providing a big-data driven nationwide jobs-housing study fully aware of the theoretical and practical needs of a regionalizing world. Findings advances our understanding of macroscopic jobs-housing relationship, and offers policy suggestions for governments across the globe.

Effects of high-speed rail on intercity travels, utility and social welfare in urban agglomerations: A game-theoretic perspective

This paper investigates the effects of newly built high-speed rail on urban performances in terms of intercity travels, utility and social welfare by extending the two-city system into a representative urban agglomeration system consisting of a hub city and two peripheral cities. A framework based on the Cournot model with three interacted games is developed to characterize competitions among HSR operators in the system. Introducing HSR between peripheral cities decentralizes the intercity travel demands from the hub city to peripheral cities, and it does not always induce more that for the urban agglomeration. We find that “weight” on social welfare, substitutability, gross benefits ratio, HSR accessibility and frequency would differentially impact the hub and peripheral cities. Numerical examples and a case study incorporating all factors based on Central Plains Urban Agglomeration in China are conducted to illustrate the model, together with some policy implications.

Exploring intercity travel decision-making in a developing country: Insights from COVID-19 impacts in Iran

This study examines the impact of COVID-19 on intercity travel mode choices in Mazandaran province, Iran, addressing critical gaps in understanding how pandemics affect travel behavior in developing countries. The research focuses on how socio-economic factors, perceived health risks, and travel time influence individuals’ choice of transportation modes during the pandemic. Using a stated preference survey method with 669 participants, the study assessed how concerns about virus transmission and adherence to health protocols shape travel decisions. Discrete choice modeling was employed to predict travel mode shares between public transport and personal vehicles. The findings reveal that COVID-19 risk perception, socio-economic factors, and travel time significantly impact travel behavior. Specifically, heightened perceived risk of infection resulted in a 25% reduction in public transportation use, with individuals increasingly opting for personal vehicles. Additionally, strict adherence to health protocols, such as mask-wearing and vehicle cleaning, improved safety perception, leading to a 40% increase in confidence in public transport. The study also found that socio-economic factors like age, income, and education significantly shaped travel preferences. These insights provide valuable guidance for public health policymakers and transportation authorities to enhance the safety and management of intercity travel during ongoing and future pandemics.

Multimodal Transportation Planning for Intercity Travel Between Alexandria and Borg Al Arab Cities

Multimodal Transportation Planning for Intercity Travel Between Alexandria and Borg Al Arab Cities

The Role of Smart Travel Service in Intercity Travel Satisfaction: Does Traveler Heterogeneity Matter?

With the increasing intercity communications and the widespread application of smart travel technologies, it is of great significance to understand the mechanism of how the attributes of smart travel service affect the travel satisfaction among intercity travelers and the potential heterogeneity. This paper establishes a conceptual model with hypotheses from two paths: smart travel service and smart travel experience. Based on the intercity travel survey data of the Guanzhong Plain urban agglomeration in China, a latent class structural equation model is employed to divide the samples into “cold”, “rational”, and “enthusiastic” potential groups based on the use and attitude of smart travel services. From the model estimation results, this study confirms that smart travel service and travel experience satisfaction have significant positive impacts on the overall intercity travel satisfaction of travelers. However, the impact of smart travel satisfaction varies due to group heterogeneity. For the “cold” group, the impact of smart travel service satisfaction on the overall satisfaction of intercity travel is not significant, and smart travel service satisfaction only has a significant impact on the smart travel experience satisfaction of “enthusiastic” travelers. This study puts forward the importance of enhancing the quality of smart travel services and promoting travel experience through smart travel technologies and proposes measures for different groups from the perspective of market segmentation, which provides theoretical and practical value for the promotion of sustainable development of intercity transportation.

Analysis of Travel Mode Choice Behavior between High-Speed Rail and Air Transport Utilizing Large-Scale Ticketing Data

As essential infrastructure, high-speed rail (HSR) and air transport (AT) play crucial roles in socioeconomic development. With their continuous expansion in China, the overlap of HSR and AT networks has increased, providing travelers with more choices for intercity travel. Because fierce competition in the medium-to-long-distance segment affects the market share and transport capacity dispatching, the travel choice between HSR and AT has been of intense interest. This study utilized a unique fusion dataset collected from two separate organizations to conduct an empirical analysis of the travel mode choice behaviors of individuals when choosing between HSR and AT. A multinomial logit (MNL) model was adopted to examine the influences of key factors on passenger choice preferences. The results showed that the fitting effect of the MNL model was satisfactory, and the parameters were strongly interpretable. The McFadden Pseudo R2 with a city-pair fixed effect in the MNL model increased by 17.3% compared with that without the city-pair fixed effect. All the related explanatory variables, including the trip distance by high-speed train, demography, ticket purchasing, and travel behavior characteristics, had significant positive effects on the passengers’ choice of AT, with trip distance having the largest effect. According to the parameter estimation, 1,160 km was the division for individual choice between HSR and AT. This study also compared the prediction accuracies of the MNL model and eight classical machine-learning models and found that random forest had the best performance. This study provides a new framework for analyzing travel choice modeling when choosing between HSR and AT.

Collaboration between High-Speed Rail and Urban Transportation to Improve Urban Air Quality in Green Travel

Although high-speed rail (HSR) can reduce the total pollutant emission in intercity travel by replacing road travel, the scope of air pollution caused by vehicles is narrow, suggesting that HSR operation has limited impact on improving urban air quality. However, many studies have confirmed that the opening of HSR does significantly improve air quality in urban districts where HSR stations are located, and the improvements occur in real time. To study the real-time pathways through which this effect arises, this paper discovered the relationship between the opening of HSR, urban transportation, and urban air quality using mediation effect theory. The results showed that HSR has no significant direct impact on improving urban air quality, but mainly affected urban air quality indirectly and in real-time through urban transportation. This paper has identified and confirmed the real-time impact path of HSR on urban air quality, and provided some suggestions related to intercity travel and green tourism to promote the development of green consumption.

Design of intelligent cruise control system using fuzzy-PID control on autonomous electric vehicles prototypes

Electric vehicles provide a solution for using alternative fuels, namely, electricity. Electric vehicles are used for short distances and intercity travel over long distances, increasing the risk of accidents. Cruise Control is a technology embedded in vehicles to maintain stable speeds; this system will automatically adjust the vehicle's speed when motion changes cause changes in vehicle speed. This study aims to apply lidar sensors to detect distance in the Intelligent Cruise Control (ICC) system using the Fuzzy-PID control method. Testing results were obtained at safe distance inputs of 5, 6, and 7 meters with various object distances. All the tests were carried out; the response systems were obtained with an average settling time of 5 seconds and an average overshoot of 1.53%. Therefore, the proposed Fuzzy-PID method works well for controlling Intelligent Cruise Control systems in autonomous electric vehicle prototypes.

Road–Rail Intermodal Travel Mode Choice Behavior Considering Attitude Factors

Road–rail intermodal transportation (RRIT) leverages the advantages of multiple transport modes and is crucial for addressing the current issue of imbalanced development in the transportation sector. However, passengers’ behavior in choosing RRIT remains unclear, and it is necessary to optimize travel service quality through analyzing RRIT choice behavior based on user perceptions. This study designed a stated preference experiment that included both direct and multi-modal travel options. A hybrid choice model considering attitude variables was constructed, and four latent attitude variables—convenience, economy, comfort, and riskiness—were extracted to analyze their impact on intercity travel mode choice behavior under conditions of ticket booking uncertainty. The results revealed that the ticket booking success rate is a critical factor in travelers’ decision-making. Passengers tend to choose travel options with higher ticket booking success rates, even if it entails a slight increase in the ticket prices for the high-speed rail to high-speed rail transfer option. The attitude variables significantly influence intercity travel mode choice behavior, with travelers generally exhibiting a preference for risk avoidance in their travel options. Moreover, there are differences among various groups of travelers in their preferences and demands for the convenience, economy, and comfort aspects of travel options. These research findings can enhance our understanding of the key factors influencing the selection of RRIT services, thereby supporting RRIT designers and planners in improving service quality and facilitating the future growth of RRIT.

Exploring reference-dependency in route switching behavior on intercity travel: Endowment effect and disparities between willingness to pay and willingness to accept

This study explores asymmetric preferences in route switching behavior on intercity travel. A reference-dependent travel choice model reflecting the endowment effect is empirically compared with the classical symmetric travel choice model to investigate the significance of the reference-dependency. Based on the application to stated preference data, our results reveal that the reference-dependent travel choice model outperforms the classical symmetric travel choice model in route switching decision, indicating the significant disparities between WTA and WTP. It implies that policy making based on the results of the classical symmetric model assuming equivalent WTA and WTP could lead to the overestimation of switching demand. Furthermore, our results show that drivers are more heterogeneous in terms of WTA than WTP. Moreover, our applications of the latent class mixed logit structure indicate that most of the responded drivers show reference-dependency in route switching decision. Our findings in this study are essential in transport network policy making.

Spatiotemporal characteristics of residents' intercity travel in China under the impact of COVID-19 pandemic

Investigating the spatiotemporal characteristics of residents' intercity travel affected by the coronavirus disease (COVID-19) pandemic is of great significance to understanding and extending the impact of major public health affairs on intercity travelers, urban management policies, and intercity cooperative interactions. Taking 366 cities in China as an example, this study proposed a novel research framework for analyzing the spatiotemporal characteristics of intercity population flows. Using AutoNavi population migration big data sets from web crawling, the spatiotemporal structure patterns of intercity travel in China from January 1st to June 30th, 2020 were extracted by using the singular value decomposition (SVD) method. Then the spatial organization patterns of intercity travel networks in China and its five major urban agglomerations were identified by the weighted stochastic block model (WSBM). The results showed that the total volume of intercity travel in China and its five major urban agglomerations experienced a process of rapid decline followed by a slow recovery, presenting a “V-shaped” distribution since the outbreak of the COVID-19 pandemic. Three distinctive intercity travel patterns, namely the stable, holiday, and weekday-weekend intercity trip patterns, were extracted from the spatiotemporal OD matrix of intercity travel. Strong intercity travels were mainly distributed in eastern and central China, forming an intercity travel pattern in which core cities pushed and pulled each other within the national urban agglomerations. However, intercity migration flows were dominated by weak-intensity flows. Intercity trips during the holidays had a phenomenon of “escaping from the metropolis”. Meanwhile, it had significant spatial proximity and directionality. The daily intercity trips were characterized by a remarkable periodicity with seven days as a repeat. A more interesting finding is that when weekends overlap with holidays, intercity travel on the 1–2 days before the vacations has presented an effect of “suppression travel”. Furthermore, at the national scale, the stable intercity travel network has formed a polycentric core-periphery structure of “Three Cores-Six Semi-peripheries-Five Peripheries”. At the urban agglomeration scale, they formed respectively distinguished monocentric, bicentric, and polycentric core-periphery structures.

Proposed Service Quality Improvement at Aya Travel using SERVQUAL Method and Importance Performance Analysis

Intercity travel is a transportation service that facilitates movement between cities and cities. Aya Travel is here to facilitate transportation between Bandung and Depok. Aya Travel was established in 2005 with a fleet of 16 units. As time passes, there are travel competitors whose presence makes the sales of Aya travel departure tickets decline in 2016. This can be caused by the quality of other travel services being better than Aya Travel, so lately, people have switched from Aya Travel. The phenomenon is that what Aya travel consumers expect is not what they receive. Service quality measurement is carried out to respond to the above phenomenon using SERVQUAL. In the process, initial attributes from literature studies and Critical Incident Techniques were collected. After the attributes are collected, the questionnaire is distributed. The Factoring process is carried out to produce factors that are formed so that it is easier for Aya Travel to find out in which dimension it turns out that the quality of the service is inferior. After the SEVQUAL measurement process, an important Performance Analysis process was carried out to find improvement priorities from Aya Travel. The IPA method will map attributes into quadrants to produce priorities ranging from those that must be improved immediately to those that do not add value to the quality of Aya Travel's services. A Factor Analysis was produced from 22 attributes grouped into four factors, and it turned out that the display factor had the worst idea. The measurement of Aya travel service quality produces six attributes that need to be improved, which are those in the second quadrant (Consternate here) in the IPA diagram. For the proposed improvement, a discussion was carried out with Aya Travel so that the improvement proposal could be under the opinions and input of Aya Travel.