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Freeway path travel time prediction based on heterogeneous traffic data through nonparametric model |
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| Authors: | Wenxin Qiao Ali Haghani Chun-Fu Shao Jun Liu |
| Institution: | 1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China;2. Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA;3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China |
| Abstract: | Providing reliable travel time prediction is very much needed for commuters for their upcoming trips to reduce travel time and relieve traffic congestion. This article proposes an integrated model for path and multi-step-ahead travel time prediction on freeways using both historical and real-time heterogeneous traffic and weather data. The model's performance is investigated in a case study under various traffic scenarios. Results indicate that the proposed model provides satisfactory prediction results in various performance tests. For practical purposes, general guidelines for selecting the model's parameter sets as well as the efficient size of historical data are also presented. |
| Keywords: | heterogeneous traffic data nonparametric model travel time prediction |