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Demand responsive transport: Generation of activity patterns from mobile phone network data to support the operation of new mobility services

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  • Franco, Patrizia
  • Johnston, Ryan
  • McCormick, Ecaterina

Abstract

Demand Responsive Transport (DRT), covering the first/last mile of a journey, plays a pivotal role in the delivery of a seamless integrated door-to-door service, which is a fundamental requirement for the implementation of Mobility as a Service (MaaS). Business models currently in use do not deliver sustainable and durable DRT in urban areas. This can be minimised using transport modelling tools ahead of the operation phase. However, transport models are not fit for purpose when it comes to model on-demand shared mobility services and the integration of these services in a complex public transport ecosystem. This paper focuses on how to model demand for ride-shared mobility services and how to plan for these services when running in integration with mass transit. An Agent Based Model (ABM), built in the open-source Multi-Agent Transport Simulation (MatSim) platform for Bristol (UK), has used an activity-based approach to model demand for two New Mobility Services (NMS). This was then generated using anonymised and aggregated Mobile phone Network Dataset (MND), both as a trip-based and trip chains dataset to assess the capabilities of MND. Results show that the simulations built using the trip chains MND datasets (722,752 agents generated) lead to better insights in users’ travel patterns. An advanced method using additional data sources covering land-use (location of business, services and transport facilities) was used to infer purpose and mode of transport during the multimodal journeys. The output of the ABM predicts demand for two flexible on-demand services, identifying best routes to maximise the number of users served and quantifying the benefits in the integration with public transport services and in modal shift from private cars. This is expected to be useful either for Local Authorities for transport planning purposes, and for operators looking at financially sustainable DRT.

Suggested Citation

  • Franco, Patrizia & Johnston, Ryan & McCormick, Ecaterina, 2020. "Demand responsive transport: Generation of activity patterns from mobile phone network data to support the operation of new mobility services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 244-266.
    • Handle: RePEc:eee:transa:v:131:y:2020:i:c:p:244-266
    DOI: 10.1016/j.tra.2019.09.038
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    References listed on IDEAS

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    1. Luis Ferreira & Phil Charles & Clara Tether, 2007. "Evaluating Flexible Transport Solutions," Transportation Planning and Technology, Taylor & Francis Journals, vol. 30(2-3), pages 249-269.
    2. Davison, Lisa & Enoch, Marcus & Ryley, Tim & Quddus, Mohammed & Wang, Chao, 2014. "A survey of Demand Responsive Transport in Great Britain," Transport Policy, Elsevier, vol. 31(C), pages 47-54.
    3. Ambrosino, Giorgio & Nelson, John D. & Boero, Marco & Pettinelli, Irene, 2016. "Enabling intermodal urban transport through complementary services: From Flexible Mobility Services to the Shared Use Mobility Agency," Research in Transportation Economics, Elsevier, vol. 59(C), pages 179-184.
    4. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    5. Daisy, Naznin Sultana & Millward, Hugh & Liu, Lei, 2018. "Trip chaining and tour mode choice of non-workers grouped by daily activity patterns," Journal of Transport Geography, Elsevier, vol. 69(C), pages 150-162.
    6. Mark Bradley & Peter Vovsha, 2005. "A model for joint choice of daily activity pattern types of household members," Transportation, Springer, vol. 32(5), pages 545-571, September.
    7. 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.
    8. 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.
    9. Horn, M. E. T., 2002. "Multi-modal and demand-responsive passenger transport systems: a modelling framework with embedded control systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(2), pages 167-188, February.
    10. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
    11. Peraphan Jittrapirom & Valeria Caiati & Anna-Maria Feneri & Shima Ebrahimigharehbaghi & María J. Alonso González & Jishnu Narayan, 2017. "Mobility as a Service: A Critical Review of Definitions, Assessments of Schemes, and Key Challenges," Urban Planning, Cogitatio Press, vol. 2(2), pages 13-25.
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