IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i18p7827-d417356.html
   My bibliography  Save this article

Assessing the Relationship between Access Travel Time Estimation and the Accessibility to High Speed Railway Station by Different Travel Modes

Author

Listed:
  • Yuyang Zhou

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

  • Minhe Zhao

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

  • Songtao Tang

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
    CCCC Highway Consultants Co. Ltd., Beijing 100088, China)

  • William H. K. Lam

    (Department of Civil and Environmental Engineering, the Hong Kong Polytechnic University, Hong Kong)

  • Anthony Chen

    (Department of Civil and Environmental Engineering, the Hong Kong Polytechnic University, Hong Kong)

  • N. N. Sze

    (Department of Civil and Environmental Engineering, the Hong Kong Polytechnic University, Hong Kong)

  • Yanyan Chen

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

Abstract

This paper aims to fill the research gap of the relationship between the access travel time (ATT) estimation and the accessibility to high speed railway (HSR) station. A regression analysis was developed on the basis of risk-return model to analyze the access travel time estimation error (ATTEE). The data sources were 1595 valid interview survey data at Beijing South Railway Station (BSRS), China in October 2016. The factors and scenarios included travel mode, departure time, and travel date, etc. The coefficients of ATT estimation were obtained by different travel modes. The results showed that the expected access travel time (EATT) has positive linear correlation with the actual access travel time (AATT). Accessibility was calculated by the ratio of AATT to EATT. The accessibility coefficients ranged from 0.89 to 1.38 in different travel modes, departure time, and travel dates. A smaller coefficient indicates better travel time reliability and accessibility. This study not only provides a useful tool to estimate the travel time budget required for access to HSR station, but also establishes a connection with the accessibility and ATTEE. It offers an opportunity to estimate ATT to HSR stations by different modes of transport, which can help to better understand how the accessibility of the feeder transport changes at different time periods.

Suggested Citation

  • Yuyang Zhou & Minhe Zhao & Songtao Tang & William H. K. Lam & Anthony Chen & N. N. Sze & Yanyan Chen, 2020. "Assessing the Relationship between Access Travel Time Estimation and the Accessibility to High Speed Railway Station by Different Travel Modes," Sustainability, MDPI, vol. 12(18), pages 1-15, September.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7827-:d:417356
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/18/7827/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/18/7827/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carrion, Carlos & Levinson, David, 2012. "Value of travel time reliability: A review of current evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 720-741.
    2. Wang, Bobin & Shao, Chunfu & Ji, Xun, 2017. "Dynamic analysis of holiday travel behaviour with integrated multimodal travel information usage: A life-oriented approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 255-280.
    3. Chinh Ho & Corinne Mulley, 2013. "Tour-based mode choice of joint household travel patterns on weekend and weekday," Transportation, Springer, vol. 40(4), pages 789-811, July.
    4. Graziano Abrate & Giampaolo Viglia & Javier Sanchez García & Santiago Forgas-Coll, 2016. "Price Competition within and between Airlines and High-Speed Trains: The Case of the Milan—Rome Route," Tourism Economics, , vol. 22(2), pages 311-323, April.
    5. Jia, Shanming & Zhou, Chunyu & Qin, Chenglin, 2017. "No difference in effect of high-speed rail on regional economic growth based on match effect perspective?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 144-157.
    6. Yang, Hangjun & Zhang, Anming, 2012. "Effects of high-speed rail and air transport competition on prices, profits and welfare," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1322-1333.
    7. El-Geneidy, Ahmed & Levinson, David & Diab, Ehab & Boisjoly, Genevieve & Verbich, David & Loong, Charis, 2016. "The cost of equity: Assessing transit accessibility and social disparity using total travel cost," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 302-316.
    8. Li, Linbo & Ren, Huan & Zhao, Shanshan & Duan, Zhengyu & Zhang, Yahua & Zhang, Anming, 2017. "Two dimensional accessibility analysis of metro stations in Xi’an, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 414-426.
    9. Martínez Sánchez-Mateos, Héctor S. & Givoni, Moshe, 2012. "The accessibility impact of a new High-Speed Rail line in the UK – a preliminary analysis of winners and losers," Journal of Transport Geography, Elsevier, vol. 25(C), pages 105-114.
    10. Yang, Lixing & Zhou, Xuesong, 2014. "Constraint reformulation and a Lagrangian relaxation-based solution algorithm for a least expected time path problem," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 22-44.
    11. K M Atikur Rahman & Dunfu Zhang, 2018. "Analyzing the Level of Accessibility of Public Urban Green Spaces to Different Socially Vulnerable Groups of People," Sustainability, MDPI, vol. 10(11), pages 1-27, October.
    12. Zhang, Wenxin & Nian, Peihao & Lyu, Guowei, 2016. "A multimodal approach to assessing accessibility of a high-speed railway station," Journal of Transport Geography, Elsevier, vol. 54(C), pages 91-101.
    13. Hasnine, Md Sami & Graovac, Ana & Camargo, Felipe & Habib, Khandker Nurul, 2019. "A random utility maximization (RUM) based measure of accessibility to transit: Accurate capturing of the first-mile issue in urban transit," Journal of Transport Geography, Elsevier, vol. 74(C), pages 313-320.
    14. Moyano, Amparo & Moya-Gómez, Borja & Gutiérrez, Javier, 2018. "Access and egress times to high-speed rail stations: a spatiotemporal accessibility analysis," Journal of Transport Geography, Elsevier, vol. 73(C), pages 84-93.
    15. Yan Xu & Weixuan Song & Chunhui Liu, 2018. "Social-Spatial Accessibility to Urban Educational Resources under the School District System: A Case Study of Public Primary Schools in Nanjing, China," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
    16. Chen, Zhenhua & Xue, Junbo & Rose, Adam Z. & Haynes, Kingsley E., 2016. "The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 232-245.
    17. Fosgerau, Mogens, 2010. "On the relation between the mean and variance of delay in dynamic queues with random capacity and demand," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 598-603, April.
    18. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.
    19. Wang, Lvhua & Liu, Yongxue & Sun, Chao & Liu, Yahui, 2016. "Accessibility impact of the present and future high-speed rail network: A case study of Jiangsu Province, China," Journal of Transport Geography, Elsevier, vol. 54(C), pages 161-172.
    20. Koster, Paul & Kroes, Eric & Verhoef, Erik, 2011. "Travel time variability and airport accessibility," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1545-1559.
    21. Lu, Shyi-Min, 2016. "A low-carbon transport infrastructure in Taiwan based on the implementation of energy-saving measures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 499-509.
    22. Geng, Jichao & Long, Ruyin & Chen, Hong, 2016. "Impact of information intervention on travel mode choice of urban residents with different goal frames: A controlled trial in Xuzhou, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 134-147.
    23. Dominik Ziemke & Johan W. Joubert & Kai Nagel, 2018. "Accessibility in a Post-Apartheid City: Comparison of Two Approaches for Accessibility Computations," Networks and Spatial Economics, Springer, vol. 18(2), pages 241-271, June.
    24. Nassir, Neema & Hickman, Mark & Malekzadeh, Ali & Irannezhad, Elnaz, 2016. "A utility-based travel impedance measure for public transit network accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 26-39.
    25. Chen, Zhenhua, 2017. "Impacts of high-speed rail on domestic air transportation in China," Journal of Transport Geography, Elsevier, vol. 62(C), pages 184-196.
    26. Shaw, Shih-Lung & Fang, Zhixiang & Lu, Shiwei & Tao, Ran, 2014. "Impacts of high speed rail on railroad network accessibility in China," Journal of Transport Geography, Elsevier, vol. 40(C), pages 112-122.
    27. Ekko C. van Ierland, Robert G.J. Huiberts, 2001. "Transport and the environment in the Netherlands," International Journal of Environmental Technology and Management, Inderscience Enterprises Ltd, vol. 1(3), pages 269-273.
    28. Cheng, Yung-Hsiang & Chen, Ssu-Yun, 2015. "Perceived accessibility, mobility, and connectivity of public transportation systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 386-403.
    29. Can, Vo Van, 2013. "Estimation of travel mode choice for domestic tourists to Nha Trang using the multinomial probit model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 149-159.
    30. Zhao, Jian & Zhao, Yunyi & Li, Ying, 2015. "The variation in the value of travel-time savings and the dilemma of high-speed rail in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 130-140.
    31. Jinguang Zhang & Yingyi Cheng & Wei Wei & Bing Zhao, 2019. "Evaluating Spatial Disparity of Access to Public Parks in Gated and Open Communities with an Improved G2SFCA Model," Sustainability, MDPI, vol. 11(21), pages 1-19, October.
    32. Wang, Feng & Wei, Xianjin & Liu, Juan & He, Lingyun & Gao, Mengnan, 2019. "Impact of high-speed rail on population mobility and urbanisation: A case study on Yangtze River Delta urban agglomeration, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 99-114.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. (Ato) Xu, Wangtu & Zhou, Jiangping & Yang, Linchuan & Li, Ling, 2018. "The implications of high-speed rail for Chinese cities: Connectivity and accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 308-326.
    2. Mohsen Momenitabar & Raj Bridgelall & Zhila Dehdari Ebrahimi & Mohammad Arani, 2021. "Literature Review of Socioeconomic and Environmental Impacts of High-Speed Rail in the World," Sustainability, MDPI, vol. 13(21), pages 1-27, November.
    3. Lin, Jen-Jia & Xie, Ze-Xing, 2020. "The associations of newly launched high-speed rail stations with industrial gentrification," Journal of Transport Geography, Elsevier, vol. 83(C).
    4. Zhang, Hui & Cui, Houdun & Wang, Wei & Song, Wenbo, 2020. "Properties of Chinese railway network: Multilayer structures based on timetable data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    5. (Ato) Xu, Wangtu & Huang, Ying, 2019. "The correlation between HSR construction and economic development – Empirical study of Chinese cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 24-36.
    6. Xiaomin Wang & Wenxin Zhang, 2019. "Efficiency and Spatial Equity Impacts of High-Speed Rail on the Central Plains Economic Region of China," Sustainability, MDPI, vol. 11(9), pages 1-18, May.
    7. Mohsen Momenitabar & Zhila Dehdari Ebrahimi & Mohammad Arani, 2020. "A Systematic and Analytical Review of the Socioeconomic and Environmental Impact of the Deployed High-Speed Rail (HSR) Systems on the World," Papers 2003.04452, arXiv.org, revised Mar 2020.
    8. Junhui Shi & Fang Wang, 2022. "The Effect of High-Speed Rail on Cropland Abandonment in China," Land, MDPI, vol. 11(7), pages 1-16, July.
    9. Wu, Shuping & Han, Dan, 2022. "Accessibility of high-speed rail (HSR) stations and HSR–air competition: Evidence from China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 262-284.
    10. Zhao, Yun & Yu, Hongbo, 2018. "A door-to-door travel time approach for evaluating modal competition of intercity travel: A focus on the proposed Dallas-Houston HSR route," Journal of Transport Geography, Elsevier, vol. 72(C), pages 13-22.
    11. Chen, Fanglin & Hao, Xinyue & Chen, Zhongfei, 2021. "Can high-speed rail improve health and alleviate health inequality? Evidence from China," Transport Policy, Elsevier, vol. 114(C), pages 266-279.
    12. Li, Tao & Rong, Lili, 2021. "Impacts of service feature on vulnerability analysis of high-speed rail network," Transport Policy, Elsevier, vol. 110(C), pages 238-253.
    13. Tanaka, Koichi, 2023. "Impacts of the opening of the maglev railway on daily accessibility in Japan: A comparative analysis with that of the Shinkansen," Journal of Transport Geography, Elsevier, vol. 106(C).
    14. Asep Yayat Nurhidayat & Hera Widyastuti & Sutikno & Dwi Phalita Upahita, 2023. "Research on Passengers’ Preferences and Impact of High-Speed Rail on Air Transport Demand," Sustainability, MDPI, vol. 15(4), pages 1-26, February.
    15. Li, Tao & Rong, Lili, 2022. "Spatiotemporally complementary effect of high-speed rail network on robustness of aviation network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 95-114.
    16. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2021. "Comparative accessibility of Chinese airports and high-speed railway stations: A high-resolution, yet scalable framework based on open data," Journal of Air Transport Management, Elsevier, vol. 92(C).
    17. Liu, Mengsha & Jiang, Yan & Wei, Xiaokun & Ruan, Qingsong & Lv, Dayong, 2023. "Effect of high-speed rail on entrepreneurial activities: Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    18. Guo, Ying & Cao, Lingyan & Song, Ying & Wang, Yan & Li, Yongkui, 2022. "Understanding the formation of City-HSR network: A case study of Yangtze River Delta, China," Transport Policy, Elsevier, vol. 116(C), pages 315-326.
    19. Li, Yan & Chen, Zhenhua & Wang, Peng, 2020. "Impact of high-speed rail on urban economic efficiency in China," Transport Policy, Elsevier, vol. 97(C), pages 220-231.
    20. Yu, Danlin & Zhang, Yaojun & Wu, Xiwei & Li, Ding & Li, Guangdong, 2021. "The varying effects of accessing high-speed rail system on China’s county development: A geographically weighted panel regression analysis," Land Use Policy, Elsevier, vol. 100(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7827-:d:417356. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.