Incident Detection and Incident-Impacted Traffic Prediction for Urban Road Networks, Application to GrandLyon

نویسندگان

  • Laura Wynter
  • Sebastien Blandin
  • Barry M Trager
  • Yichong Yu
چکیده

This paper describes joint work done by IBM Research (development of the solution) and GrandLyon (assessment of the solution) for real-time incident detection and traffic prediction on an urban road network in the presence of incidents. The detection and prediction methods are integrated and tested in a pilot study on live real-time traffic data in Lyon Metropolis, France. Numerical results and analysis are provided. The benefits of faster and more accurate incident detection include faster incident clearing times and more accurate and timely information to the public so as to avoid affected areas on the road network.

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تاریخ انتشار 2015