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Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona

Author

Listed:
  • Bassolas, Aleix
  • Ramasco, José J.
  • Herranz, Ricardo
  • Cantú-Ros, Oliva G.

Abstract

Activity-based models appeared as an answer to the limitations of the traditional trip-based and tour-based four-stage models. The fundamental assumption of activity-based models is that travel demand is originated from people performing their daily activities. This is why they include a consistent representation of time, of the persons and households, time-dependent routing, and microsimulation of travel demand and traffic. In spite of their potential to simulate traffic demand management policies, their practical application is still limited. One of the main reasons is that these models require a huge amount of very detailed input data hard to get with surveys. However, the pervasive use of mobile devices has brought a valuable new source of data. The work presented here has a twofold objective: first, to demonstrate the capability of mobile phone records to feed activity-based transport models, and, second, to assert the advantages of using activity-based models to estimate the effects of traffic demand management policies. Activity diaries for the metropolitan area of Barcelona are reconstructed from mobile phone records. This information is then employed as input for building a transport MATSim model of the city. The model calibration and validation process proves the quality of the activity diaries obtained. The possible impacts of a cordon toll policy applied to two different areas of the city and at different times of the day are then studied. Our results show the way in which the modal share is modified in each of the considered scenarios. The possibility of evaluating the effects of the policy at both aggregated and traveller level, together with the ability of the model to capture policy impacts beyond the cordon toll area confirm the advantages of activity-based models for the evaluation of traffic demand management policies.

Suggested Citation

  • Bassolas, Aleix & Ramasco, José J. & Herranz, Ricardo & Cantú-Ros, Oliva G., 2019. "Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 56-74.
  • Handle: RePEc:eee:transa:v:121:y:2019:i:c:p:56-74
    DOI: 10.1016/j.tra.2018.12.024
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    References listed on IDEAS

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    Cited by:

    1. Andreas Dypvik Landmark & Petter Arnesen & Carl-Johan Södersten & Odd André Hjelkrem, 2021. "Mobile phone data in transportation research: methods for benchmarking against other data sources," Transportation, Springer, vol. 48(5), pages 2883-2905, October.
    2. Nicholas Fournier & Eleni Christofa & Arun Prakash Akkinepally & Carlos Lima Azevedo, 2021. "Integrated population synthesis and workplace assignment using an efficient optimization-based person-household matching method," Transportation, Springer, vol. 48(2), pages 1061-1087, April.
    3. Jiri Horak & Jan Tesla & David Fojtik & Vit Vozenilek, 2019. "Modelling Public Transport Accessibility with Monte Carlo Stochastic Simulations: A Case Study of Ostrava," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    4. Yu Han & Changjie Chen & Zhong-Ren Peng & Pallab Mozumder, 2022. "Evaluating impacts of coastal flooding on the transportation system using an activity-based travel demand model: a case study in Miami-Dade County, FL," Transportation, Springer, vol. 49(1), pages 163-184, February.
    5. Jinjun Tang & Fan Gao & Fang Liu & Wenhui Zhang & Yong Qi, 2019. "Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM," Sustainability, MDPI, vol. 11(19), pages 1-19, October.

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