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Stochastic Network Vehicular Origin-Destination Demand Using Multi-Sensor Information Fusion Approaches
| 题名： | Stochastic Network Vehicular Origin-Destination Demand Using Multi-Sensor Information Fusion Approaches |
| 作者： | Liou, H.; Hu, S.; Peeta, S. |
| 关键词： | Vehicular origin-destination##Multi-sensor information##Traffic sensors##Traffic information##Traffic flow data## |
| 摘要： | This study proposes an integrated two-stage optimization model for the HSDP-OD problem. The first stage is the heterogeneous traffic sensors deployment model, which seeks to determine the sensor deployment strategy that optimizes the traffic information available to the second-stage O-D matrix estimation problem. The weights of the objective function terms in this model are functions of the errors between the observed and estimated link and path/O-D flow data determined in the second-stage model. The second stage is the O-D matrix estimation model that leverages the traffic information obtained in the first-stage model to determine the O-D matrix that minimizes the errors between the observed and estimated traffic flow data. The traffic information from the first stage and the traffic flow data errors from the second stage integrate this two-stage optimization model. The two-stage model for the HSDP-OD problem is described hereafter. |
| 总页数： | 24 |
| 报告类型： | 科技报告 |
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