IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v157y2022ics1366554521003148.html
   My bibliography  Save this article

A novel model and algorithm for designing an eco-oriented demand responsive transit (DRT) system

Author

Listed:
  • Li, Xin
  • Wang, Tianqi
  • Xu, Weihan
  • Li, Huaiyue
  • Yuan, Yun

Abstract

Since the flexibility and adaptability of demand responsive transit (DRT) give more potentials and spaces of embracing eco-routing strategy, this study develops a novel framework of embedding eco-routing technology into DRT service, in which module of vehicle dynamics and module of fuel consumption/emission are specifically integrated in response to varied traffic conditions and road types when designing of DRT system. To this end, a mix-integer model and the customized DP-based heuristic are proposed to determine eco-oriented DRT routes and schedules. A series of numerical cases based on realistic road networks are designed to unfold the comparison of the performance of eco-oriented DRT against the traditional one. The results demonstrate that introduction of eco-routing is able to significantly reduce the energy consumption and emissions by up to 37% in companying with a slight increase of total travel time and routing distance. The well-developed models and algorithm make the study is ready for real-world applications.

Suggested Citation

  • Li, Xin & Wang, Tianqi & Xu, Weihan & Li, Huaiyue & Yuan, Yun, 2022. "A novel model and algorithm for designing an eco-oriented demand responsive transit (DRT) system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:transe:v:157:y:2022:i:c:s1366554521003148
    DOI: 10.1016/j.tre.2021.102556
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554521003148
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2021.102556?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. Tscharaktschiew, Stefan & Hirte, Georg, 2012. "Should subsidies to urban passenger transport be increased? A spatial CGE analysis for a German metropolitan area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 285-309.
    2. Xie, Shaobo & Hu, Xiaosong & Xin, Zongke & Brighton, James, 2019. "Pontryagin’s Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 236(C), pages 893-905.
    3. Chandra, Shailesh & Quadrifoglio, Luca, 2013. "A model for estimating the optimal cycle length of demand responsive feeder transit services," Transportation Research Part B: Methodological, Elsevier, vol. 51(C), pages 1-16.
    4. Tian, He & Li, Shengbo Eben & Wang, Xu & Huang, Yong & Tian, Guangyu, 2018. "Data-driven hierarchical control for online energy management of plug-in hybrid electric city bus," Energy, Elsevier, vol. 142(C), pages 55-67.
    5. Shaobo Xie & Huiling Li & Zongke Xin & Tong Liu & Lang Wei, 2017. "A Pontryagin Minimum Principle-Based Adaptive Equivalent Consumption Minimum Strategy for a Plug-in Hybrid Electric Bus on a Fixed Route," Energies, MDPI, vol. 10(9), pages 1-22, September.
    6. Bektas, Tolga, 2006. "The multiple traveling salesman problem: an overview of formulations and solution procedures," Omega, Elsevier, vol. 34(3), pages 209-219, June.
    7. Quadrifoglio, Luca & Dessouky, Maged M. & Ordóñez, Fernando, 2008. "A simulation study of demand responsive transit system design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 718-737, May.
    8. Chen, Peng Will & Nie, Yu Marco, 2017. "Analysis of an idealized system of demand adaptive paired-line hybrid transit," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 38-54.
    9. Quirion-Blais, Olivier & Chen, Lu, 2021. "A case-based reasoning approach to solve the vehicle routing problem with time windows and drivers’ experience," Omega, Elsevier, vol. 102(C).
    10. Li, Wenjie & Yang, Lixing & Wang, Li & Zhou, Xuesong & Liu, Ronghui & Gao, Ziyou, 2017. "Eco-reliable path finding in time-variant and stochastic networks," Energy, Elsevier, vol. 121(C), pages 372-387.
    11. Dai, Zhuang & Liu, Xiaoyue Cathy & Chen, Zhuo & Guo, Renyong & Ma, Xiaolei, 2019. "A predictive headway-based bus-holding strategy with dynamic control point selection: A cooperative game theory approach," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 29-51.
    12. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    13. Sivak, Michael & Schoettle, Brandon, 2012. "Eco-driving: Strategic, tactical, and operational decisions of the driver that influence vehicle fuel economy," Transport Policy, Elsevier, vol. 22(C), pages 96-99.
    14. Li, Xin & Luo, Yue & Wang, Tianqi & Jia, Peng & Kuang, Haibo, 2020. "An integrated approach for optimizing bi-modal transit networks fed by shared bikes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    15. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    16. Xi, Jiaqi & Li, Mian & Xu, Min, 2014. "Optimal energy management strategy for battery powered electric vehicles," Applied Energy, Elsevier, vol. 134(C), pages 332-341.
    17. Quadrifoglio, Luca & Li, Xiugang, 2009. "A methodology to derive the critical demand density for designing and operating feeder transit services," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 922-935, December.
    18. Samuel Eilon, 1971. "Goals And Constraints," Journal of Management Studies, Wiley Blackwell, vol. 8(3), pages 292-303, October.
    19. Santos, Georgina & Behrendt, Hannah & Maconi, Laura & Shirvani, Tara & Teytelboym, Alexander, 2010. "Part I: Externalities and economic policies in road transport," Research in Transportation Economics, Elsevier, vol. 28(1), pages 2-45.
    20. Donald L. Miller, 1995. "A Matching Based Exact Algorithm for Capacitated Vehicle Routing Problems," INFORMS Journal on Computing, INFORMS, vol. 7(1), pages 1-9, February.
    21. Fatnassi, Ezzeddine & Chaouachi, Jouhaina & Klibi, Walid, 2015. "Planning and operating a shared goods and passengers on-demand rapid transit system for sustainable city-logistics," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 440-460.
    22. Wang, Yong & Peng, Shouguo & Zhou, Xuesong & Mahmoudi, Monirehalsadat & Zhen, Lu, 2020. "Green logistics location-routing problem with eco-packages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    23. Daganzo, Carlos F. & Ouyang, Yanfeng, 2019. "A general model of demand-responsive transportation services: From taxi to ridesharing to dial-a-ride," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 213-224.
    24. Mahmoudi, Monirehalsadat & Zhou, Xuesong, 2016. "Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: A dynamic programming approach based on state–space–time network representations," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 19-42.
    25. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rahman, Md Hishamur & Chen, Shijie & Sun, Yanshuo & Siddiqui, Muhammad Imran Younus & Mohebbi, Matthew & Marković, Nikola, 2023. "Integrating dial-a-ride with transportation network companies for cost efficiency: A Maryland case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    2. Ming Wei & Congxin Yang & Tao Liu, 2022. "An Integrated Multi-Objective Optimization for Dynamic Airport Shuttle Bus Location, Route Design and Departure Frequency Setting Problem," IJERPH, MDPI, vol. 19(21), pages 1-20, November.

    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. Badia, Hugo & Jenelius, Erik, 2021. "Design and operation of feeder systems in the era of automated and electric buses," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 146-172.
    2. Xin Li & Wanying Liu & Jingyuan Qiao & Yanhao Li & Jia Hu, 2023. "An Enhanced Semi-Flexible Transit Service with Introducing Meeting Points," Networks and Spatial Economics, Springer, vol. 23(3), pages 487-527, September.
    3. Kim, Myungseob (Edward) & Schonfeld, Paul, 2015. "Maximizing net benefits for conventional and flexible bus services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 116-133.
    4. Rich, Jeppe & Seshadri, Ravi & Jomeh, Ali Jamal & Clausen, Sofus Rasmus, 2023. "Fixed routing or demand-responsive? Agent-based modelling of autonomous first and last mile services in light-rail systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    5. Tang, Xindi & Yang, Jie & Lin, Xi & He, Fang & Si, Jinhua, 2023. "Dynamic operations of an integrated mobility service system of fixed-route transits and flexible electric buses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    6. Shixiong Jiang & Wei Guan & Liu Yang & Wenyi Zhang, 2020. "Feeder Bus Accessibility Modeling and Evaluation," Sustainability, MDPI, vol. 12(21), pages 1-17, October.
    7. Qiu, Feng & Shen, Jinxing & Zhang, Xuechi & An, Chengchuan, 2015. "Demi-flexible operating policies to promote the performance of public transit in low-demand areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 215-230.
    8. Daganzo, Carlos F. & Ouyang, Yanfeng & Yang, Haolin, 2020. "Analysis of ride-sharing with service time and detour guarantees," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 130-150.
    9. R. Baldacci & E. Hadjiconstantinou & A. Mingozzi, 2004. "An Exact Algorithm for the Capacitated Vehicle Routing Problem Based on a Two-Commodity Network Flow Formulation," Operations Research, INFORMS, vol. 52(5), pages 723-738, October.
    10. Guan, Yunlin & Xiang, Wang & Wang, Yun & Yan, Xuedong & Zhao, Yi, 2023. "Bi-level optimization for customized bus routing serving passengers with multiple-trips based on state–space–time network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    11. Zahra Navidi & Nicole Ronald & Stephan Winter, 2018. "Comparison between ad-hoc demand responsive and conventional transit: a simulation study," Public Transport, Springer, vol. 10(1), pages 147-167, May.
    12. Nicole Ronald & Russell Thompson & Stephan Winter, 2015. "Simulating Demand-responsive Transportation: A Review of Agent-based Approaches," Transport Reviews, Taylor & Francis Journals, vol. 35(4), pages 404-421, July.
    13. Chen, Z. & Liu, Y. & Ye, M. & Zhang, Y. & Chen, Z. & Li, G., 2021. "A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    14. Li, Siqiao & Zhu, Xiaoning & Shang, Pan & Li, Tianqi & Liu, Wenqian, 2023. "Optimizing a shared freight and passenger high-speed railway system: A multi-commodity flow formulation with Benders decomposition solution approach," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 1-31.
    15. Schneider, M., 2016. "The vehicle-routing problem with time windows and driver-specific times," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65941, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    16. Jure Soldo & Branimir Škugor & Joško Deur, 2021. "Online Synthesis of an Optimal Battery State-of-Charge Reference Trajectory for a Plug-in Hybrid Electric City Bus," Energies, MDPI, vol. 14(11), pages 1-24, May.
    17. Fengqi Zhang & Lihua Wang & Serdar Coskun & Hui Pang & Yahui Cui & Junqiang Xi, 2020. "Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook," Energies, MDPI, vol. 13(13), pages 1-35, June.
    18. Jure Soldo & Branimir Škugor & Joško Deur, 2019. "Synthesis of Optimal Battery State-of-Charge Trajectory for Blended Regime of Plug-in Hybrid Electric Vehicles in the Presence of Low-Emission Zones and Varying Road Grades," Energies, MDPI, vol. 12(22), pages 1-21, November.
    19. Lu, Jiawei & Nie, Qinghui & Mahmoudi, Monirehalsadat & Ou, Jishun & Li, Chongnan & Zhou, Xuesong Simon, 2022. "Rich arc routing problem in city logistics: Models and solution algorithms using a fluid queue-based time-dependent travel time representation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 143-182.
    20. Xie, Shaobo & Hu, Xiaosong & Qi, Shanwei & Lang, Kun, 2018. "An artificial neural network-enhanced energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 163(C), pages 837-848.

    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:transe:v:157:y:2022:i:c:s1366554521003148. 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/600244/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.