IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i10p4117-d359546.html
   My bibliography  Save this article

An Agent-Based Simulation Approach for Evaluating the Performance of On-Demand Bus Services

Author

Listed:
  • Sohani Liyanage

    (Department of Civil and Construction Engineering, Swinburne University of Technology, Hawthorn 3122, Australia)

  • Hussein Dia

    (Department of Civil and Construction Engineering, Swinburne University of Technology, Hawthorn 3122, Australia)

Abstract

On-demand multi-passenger shared transport options are increasingly being promoted as an influential strategy to reduce traffic congestion and emissions and improve the convenience and travel experience for passengers. These services, often referred to as on-demand public transport, are aimed at meeting personal travel demands through the use of shared vehicles that run on flexible routes using advanced tools for dynamic scheduling. This paper presents an agent-based traffic simulation model that was developed to evaluate the performance of on-demand public transport and compare it with existing scheduled bus services using a case study of the inner city of Melbourne in Australia. The key performance measures used in the comparative evaluation included quality of service and passenger experience in terms of waiting times, the efficiency of service and operations in terms of hourly vehicle utilization, and system efficiency in terms of trip completion rates, passenger kilometers travelled and total passenger trip times. The results showed significant benefits for passengers who use on-demand bus services compared to scheduled bus services. The on-demand bus service was found to reduce average total passenger waiting times by 89% during the Morning Peak; by 78% during the Mid-Day period; by 81% during the Afternoon Peak; and by more than 95% during other periods of the day. From an operator’s perspective, the on-demand services were found to achieve around 70% vehicle utilization rates during peak hours compared to a utilization rate not exceeding 16% for the scheduled bus services. Even during off-peak periods, the occupancies for on-demand services were almost twice the vehicle occupancies for scheduled bus services. In terms of system efficiency, the on-demand services achieved a trip completion rate of 85% compared to a trip completion rate of 67% for the scheduled bus services. The total passenger-kilometers travelled was similar for both scheduled and on-demand bus services, which refutes claims that on-demand bus services induce more kilometers of travel. The trip completion times were around 55% shorter for on-demand bus services compared to scheduled services, which represents a significant saving in travel time for users. Finally, the paper presents average emissions per completed trip for both types of services and shows a significant reduction in emissions for on-demand services compared to conventional bus services. These include, on average, a 48% reduction in CO 2 emissions per trip; 82% reduction in NO emissions per trip; and 41% reduction in p.m.10 emissions per trip. These findings clearly demonstrate the superior benefits of on-demand bus services compared to scheduled bus services.

Suggested Citation

  • Sohani Liyanage & Hussein Dia, 2020. "An Agent-Based Simulation Approach for Evaluating the Performance of On-Demand Bus Services," Sustainability, MDPI, vol. 12(10), pages 1-20, May.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:4117-:d:359546
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/10/4117/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/10/4117/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ioannis Bellos & Mark Ferguson & L. Beril Toktay, 2017. "The Car Sharing Economy: Interaction of Business Model Choice and Product Line Design," Manufacturing & Service Operations Management, INFORMS, vol. 19(2), pages 185-201, May.
    2. Namazu, Michiko & Dowlatabadi, Hadi, 2018. "Vehicle ownership reduction: A comparison of one-way and two-way carsharing systems," Transport Policy, Elsevier, vol. 64(C), pages 38-50.
    3. Dowling, Robyn & Kent, Jennifer, 2015. "Practice and public–private partnerships in sustainable transport governance: The case of car sharing in Sydney, Australia," Transport Policy, Elsevier, vol. 40(C), pages 58-64.
    4. repec:cdl:itsrrp:qt8dq801g7 is not listed on IDEAS
    5. repec:cdl:itsrrp:qt23r1h80t is not listed on IDEAS
    6. Nelson, John D. & Wright, Steve & Masson, Brian & Ambrosino, Giorgio & Naniopoulos, Aristotelis, 2010. "Recent developments in Flexible Transport Services," Research in Transportation Economics, Elsevier, vol. 29(1), pages 243-248.
    7. repec:cdl:itsrrp:qt6wr90040 is not listed on IDEAS
    8. Cláudia A. Soares Machado & Nicolas Patrick Marie De Salles Hue & Fernando Tobal Berssaneti & José Alberto Quintanilha, 2018. "An Overview of Shared Mobility," Sustainability, MDPI, vol. 10(12), pages 1-21, November.
    9. Dia, Hussein, 2001. "An object-oriented neural network approach to short-term traffic forecasting," European Journal of Operational Research, Elsevier, vol. 131(2), pages 253-261, June.
    10. Sohani Liyanage & Hussein Dia & Rusul Abduljabbar & Saeed Asadi Bagloee, 2019. "Flexible Mobility On-Demand: An Environmental Scan," Sustainability, MDPI, vol. 11(5), pages 1-39, February.
    11. Mulley, Corinne & Nelson, John D., 2009. "Flexible transport services: A new market opportunity for public transport," Research in Transportation Economics, Elsevier, vol. 25(1), pages 39-45.
    12. repec:cdl:itsrrp:qt2zv240pp is not listed on IDEAS
    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. Phattarasuda Witchayaphong & Surachet Pravinvongvuth & Kunnawee Kanitpong & Kazushi Sano & Suksun Horpibulsuk, 2020. "Influential Factors Affecting Travelers’ Mode Choice Behavior on Mass Transit in Bangkok, Thailand," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    2. Chinnawat Hoonsiri & Siriluk Chiarakorn & Vasin Kiattikomol, 2021. "Using Combined Bus Rapid Transit and Buses in a Dedicated Bus Lane to Enhance Urban Transportation Sustainability," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    3. Radfar, Shariat & Koosha, Hamidreza & Gholami, Ali & Amindoust, Atefeh, 2025. "A neuro-fuzzy and deep learning framework for accurate public transport demand forecasting: Leveraging spatial and temporal factors," Journal of Transport Geography, Elsevier, vol. 126(C).

    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. Sohani Liyanage & Hussein Dia & Rusul Abduljabbar & Saeed Asadi Bagloee, 2019. "Flexible Mobility On-Demand: An Environmental Scan," Sustainability, MDPI, vol. 11(5), pages 1-39, February.
    2. Jokinen, Jani-Pekka & Sihvola, Teemu & Mladenovic, Milos N., 2019. "Policy lessons from the flexible transport service pilot Kutsuplus in the Helsinki Capital Region," Transport Policy, Elsevier, vol. 76(C), pages 123-133.
    3. Mariana de Oliveira Lage & Cláudia Aparecida Soares Machado & Cristiano Martins Monteiro & Clodoveu Augusto Davis & Charles Lincoln Kenji Yamamura & Fernando Tobal Berssaneti & José Alberto Quintanilh, 2021. "Using Hierarchical Facility Location, Single Facility Approach, and GIS in Carsharing Services," Sustainability, MDPI, vol. 13(22), pages 1-13, November.
    4. Dikas, G. & Minis, I., 2014. "Scheduled paratransit transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 18-34.
    5. Tomasz Kwarcinski, 2020. "Transport on Demand in the Opinion of Users: A Case Study for Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 462-475.
    6. Ana María Arbeláez Vélez & Andrius Plepys, 2021. "Car Sharing as a Strategy to Address GHG Emissions in the Transport System: Evaluation of Effects of Car Sharing in Amsterdam," Sustainability, MDPI, vol. 13(4), pages 1-15, February.
    7. van Engelen, Matti & Cats, Oded & Post, Henk & Aardal, Karen, 2018. "Enhancing flexible transport services with demand-anticipatory insertion heuristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 110-121.
    8. José Alberto Molina & J. Ignacio Giménez-Nadal & Jorge Velilla, 2020. "Sustainable Commuting: Results from a Social Approach and International Evidence on Carpooling," Sustainability, MDPI, vol. 12(22), pages 1-12, November.
    9. Ryley, Tim J. & A. Stanley, Peter & P. Enoch, Marcus & M. Zanni, Alberto & A. Quddus, Mohammed, 2014. "Investigating the contribution of Demand Responsive Transport to a sustainable local public transport system," Research in Transportation Economics, Elsevier, vol. 48(C), pages 364-372.
    10. Papaix, Claire & Eranova, Mariya & Zhou, Li, 2023. "Shared mobility research: Looking through a paradox lens," Transport Policy, Elsevier, vol. 133(C), pages 156-167.
    11. Alan Lee & Martin Savelsbergh, 2017. "An extended demand responsive connector," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 25-50, March.
    12. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    13. Lucia Rotaris, 2021. "Carsharing Services in Italy: Trends and Innovations," Sustainability, MDPI, vol. 13(2), pages 1-18, January.
    14. Golalikhani, Masoud & Oliveira, Beatriz Brito & Carravilla, Maria Antónia & Oliveira, José Fernando & Antunes, António Pais, 2021. "Carsharing: A review of academic literature and business practices toward an integrated decision-support framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    15. Hao, Wu & Martin, Layla, 2022. "Prohibiting cherry-picking: Regulating vehicle sharing services who determine fleet and service structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    16. Kaffash, Sepideh & Nguyen, An Truong & Zhu, Joe, 2021. "Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 231(C).
    17. Nataša Glišović & Miloš Milenković & Nebojša Bojović & Libor Švadlenka & Zoran Avramović, 2016. "A hybrid model for forecasting the volume of passenger flows on Serbian railways," Operational Research, Springer, vol. 16(2), pages 271-285, July.
    18. Maria Rosa De Giacomo & Raimund Bleischwitz, 2020. "Business models for environmental sustainability: Contemporary shortcomings and some perspectives," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3352-3369, December.
    19. Abdul Rais Abdul Latiff & Saidatulakmal Mohd, 2023. "Transport, Mobility and the Wellbeing of Older Adults: An Exploration of Private Chauffeuring and Companionship Services in Malaysia," IJERPH, MDPI, vol. 20(3), pages 1-17, February.
    20. Yang Yue & Anthony Gar-On Yeh, 2008. "Spatiotemporal Traffic-Flow Dependency and Short-Term Traffic Forecasting," Environment and Planning B, , vol. 35(5), pages 762-771, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:10:p:4117-:d:359546. 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.