IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v178y2023ics0965856423002574.html
   My bibliography  Save this article

Demand-responsive transport for students in rural areas: A case study in Vulkaneifel, Germany

Author

Listed:
  • Lu, Chengqi
  • Maciejewski, Michal
  • Wu, Hao
  • Nagel, Kai

Abstract

In rural areas with low population density, demand-responsive transport (DRT) is considered a promising alternative to conventional public transport (PT). With a fleet of smaller vehicles, DRT provides a much more flexible and convenient service. This characteristic makes DRT also a potential mode of transport to serve students in rural areas. If DRT vehicles are used to serve students, then the funding for conventional school buses (or adapted public transport schedules) can be reinvested in the DRT system. This may help to relieve the financial burden experienced by DRT operators and enable the operation of a large-scale DRT service in rural areas. In this study, a demand model for school commutes based on real-world, open-source data for Landkreis Vulkaneifel, a rural region in Germany, is built. Then a feasibility study is carried out using an agent-based transport simulation framework. In the feasibility study, various setups and operational schemes are explored, which are followed by a systematic cost analysis. Based on a conservative estimation, an annual budget of around 1600 Euro per student will be needed to maintain and operate a fleet of DRT vehicles that can transport all the students in the region from home to school on time in the morning. During the remaining time of the day and on school holidays, the vehicles can be used for conventional DRT service for the public.

Suggested Citation

  • Lu, Chengqi & Maciejewski, Michal & Wu, Hao & Nagel, Kai, 2023. "Demand-responsive transport for students in rural areas: A case study in Vulkaneifel, Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:transa:v:178:y:2023:i:c:s0965856423002574
    DOI: 10.1016/j.tra.2023.103837
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856423002574
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2023.103837?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mohring, Herbert, 1972. "Optimization and Scale Economies in Urban Bus Transportation," American Economic Review, American Economic Association, vol. 62(4), pages 591-604, September.
    2. Stiglic, M. & Agatz, N.A.H. & Savelsbergh, M.W.P. & Gradisar, M., 2015. "The Benefits of Meeting Points in Ride-sharing Systems," ERIM Report Series Research in Management ERS-2015-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Park, Junhyuk & Kim, Byung-In, 2010. "The school bus routing problem: A review," European Journal of Operational Research, Elsevier, vol. 202(2), pages 311-319, April.
    4. L Y O Li & Z Fu, 2002. "The school bus routing problem: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(5), pages 552-558, May.
    5. Hai Yang & Yan Lau & Sze Wong & Hong Lo, 2000. "A macroscopic taxi model for passenger demand, taxi utilization and level of services," Transportation, Springer, vol. 27(3), pages 317-340, June.
    6. Stiglic, Mitja & Agatz, Niels & Savelsbergh, Martin & Gradisar, Mirko, 2015. "The benefits of meeting points in ride-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 36-53.
    7. T Bektaş & Seda Elmastaş, 2007. "Solving school bus routing problems through integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1599-1604, December.
    8. Tirachini, Alejandro & Antoniou, Constantinos, 2020. "The economics of automated public transport: Effects on operator cost, travel time, fare and subsidy," Economics of Transportation, Elsevier, vol. 21(C).
    9. Schittekat, Patrick & Kinable, Joris & Sörensen, Kenneth & Sevaux, Marc & Spieksma, Frits & Springael, Johan, 2013. "A metaheuristic for the school bus routing problem with bus stop selection," European Journal of Operational Research, Elsevier, vol. 229(2), pages 518-528.
    10. Sieber, L. & Ruch, C. & Hörl, S. & Axhausen, K.W. & Frazzoli, E., 2020. "Improved public transportation in rural areas with self-driving cars: A study on the operation of Swiss train lines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 35-51.
    11. Bar-Yosef, Asaf & Martens, Karel & Benenson, Itzhak, 2013. "A model of the vicious cycle of a bus line," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 37-50.
    12. Bösch, Patrick M. & Becker, Felix & Becker, Henrik & Axhausen, Kay W., 2018. "Cost-based analysis of autonomous mobility services," Transport Policy, Elsevier, vol. 64(C), pages 76-91.
    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. Fielbaum, Andrés & Tirachini, Alejandro & Alonso-Mora, Javier, 2023. "Economies and diseconomies of scale in on-demand ridepooling systems," Economics of Transportation, Elsevier, vol. 34(C).
    2. Andres Fielbaum & Alejandro Tirachini & Javier Alonso-Mora, 2021. "New sources of economies and diseconomies of scale in on-demand ridepooling systems and comparison with public transport," Papers 2106.15270, arXiv.org, revised Jul 2021.
    3. Ma, Tai-Yu & Fang, Yumeng & Connors, Richard D. & Viti, Francesco & Nakao, Haruko, 2024. "A hybrid metaheuristic to optimize electric first-mile feeder services with charging synchronization constraints and customer rejections," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    4. Han Zheng & Junhua Chen & Xingchen Zhang & Zixian Yang, 2019. "Designing a New Shuttle Service to Meet Large-Scale Instantaneous Peak Demands for Passenger Transportation in a Metropolitan Context: A Green, Low-Cost Mass Transport Option," Sustainability, MDPI, vol. 11(18), pages 1-28, September.
    5. Ansari, Azadeh & Farrokhvar, Leily & Kamali, Behrooz, 2021. "Integrated student to school assignment and school bus routing problem for special needs students," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    6. Ezquerro Eguizábal, Sara & Moura Berodia, José Luis & Ibeas Portilla, Ángel & Benavente Ponce, Juan, 2018. "Optimization model for school transportation design based on economic and social efficiency," Transport Policy, Elsevier, vol. 67(C), pages 93-101.
    7. Shafahi, Ali & Wang, Zhongxiang & Haghani, Ali, 2018. "SpeedRoute: Fast, efficient solutions for school bus routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 473-493.
    8. Militão, Aitan M. & Tirachini, Alejandro, 2021. "Optimal fleet size for a shared demand-responsive transport system with human-driven vs automated vehicles: A total cost minimization approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 52-80.
    9. Ellegood, William A. & Solomon, Stanislaus & North, Jeremy & Campbell, James F., 2020. "School bus routing problem: Contemporary trends and research directions," Omega, Elsevier, vol. 95(C).
    10. Dasdemir, Erdi & Testik, Murat Caner & Öztürk, Diclehan Tezcaner & Şakar, Ceren Tuncer & Güleryüz, Güldal & Testik, Özlem Müge, 2022. "A multi-objective open vehicle routing problem with overbooking: Exact and heuristic solution approaches for an employee transportation problem," Omega, Elsevier, vol. 108(C).
    11. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.
    12. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    13. Agyeman, Stephen & Cheng, Lin, 2020. "Analysis of barriers to perceived service quality in Ghana: Students’ perspectives on bus mobility attributes," Transport Policy, Elsevier, vol. 99(C), pages 63-85.
    14. Shichao Sun & Zhengyu Duan & Qi Xu, 2018. "School bus routing problem in the stochastic and time-dependent transportation network," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-17, August.
    15. Fielbaum, Andres, 2024. "On the relationship between free public transport, stop spacing, and optimal frequencies," Transportation Research Part B: Methodological, Elsevier, vol. 183(C).
    16. Collins, Mor & Etzioni, Shelly & Ben-Elia, Eran, 2024. "Travel behavior and system dynamics in a simple gamified automated multimodal network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    17. Markov, Iliya & Guglielmetti, Rafael & Laumanns, Marco & Fernández-Antolín, Anna & de Souza, Ravin, 2021. "Simulation-based design and analysis of on-demand mobility services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 170-205.
    18. Meng Li & Guowei Hua & Haijun Huang, 2018. "A Multi-Modal Route Choice Model with Ridesharing and Public Transit," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
    19. Boyacı, Burak & Zografos, Konstantinos G., 2019. "Investigating the effect of temporal and spatial flexibility on the performance of one-way electric carsharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 244-272.
    20. Yu Wang & Shanyong Wang & Jing Wang & Jiuchang Wei & Chenglin Wang, 2020. "An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model," Transportation, Springer, vol. 47(1), pages 397-415, February.

    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:eee:transa:v:178:y:2023:i:c:s0965856423002574. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.