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A Unified Demand-Diversion Prediction Approach to Real-Time Group Route Guidance

  • Transportation Engineering
  • Published:
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Abstract

Dynamic origin-destination (OD) demand estimation and prediction (DODE) and drivers’ route diversion behavior (DRDB) are two fundamental determinants in the development of effective group route guidance (GRG) strategies for balancing traffic loads and enhancing system performance. This work presents a unified approach to incorporate DRDB into a DODE model. This model accounts for the influence of route diversion on DODE and predicts the OD demand in information provision environment. This study also develops a dynamic aggregate DRDB model based on the traffic data obtained through online detection and integrates this model with the DODE model. The test results of the case study show that the maximum deviation between the real OD volumes and the proposed DODE model under information provision, mean absolute percentage error, and normalized root mean square error is approximately 11.46%, 4.53%, and 5.29%, respectively. The integrated demand-diversion prediction model can accurately estimate and predict possible DRDB and the effect of traffic information on OD demand prediction using real-time traffic detected data. The model can also enhance the accuracy of OD demand and traffic state prediction under information provision, consequently increasing the effectiveness of the proposed GRG strategies.

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Acknowledgements

This research was supported in part by the National Natural Science Foundation of China 71671109, and National Natural Science Foundation of China 51308508. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the sponsors.

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Authors and Affiliations

  1. College of Transport and Communications, Shanghai Maritime University, Shanghai, 201306, China

    Tiandong Xu

  2. University of Florida, Gainesville, FL, 32611, USA

    Tiandong Xu

  3. Urban Transport Institute, China Academy of Urban Planning and Design, Beijing, 100044, China

    Yuan Hao

Authors
  1. Tiandong Xu
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  2. Yuan Hao
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Correspondence to Tiandong Xu.

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Xu, T., Hao, Y. A Unified Demand-Diversion Prediction Approach to Real-Time Group Route Guidance. KSCE J Civ Eng 24, 2214–2223 (2020). https://doi.org/10.1007/s12205-020-2091-x

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  • DOI: https://doi.org/10.1007/s12205-020-2091-x

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