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Optimal Variable Speed Limit Control in Connected Autonomous Vehicle Environment for Relieving Freeway Congestion
| 题名： | Optimal Variable Speed Limit Control in Connected Autonomous Vehicle Environment for Relieving Freeway Congestion |
| 正文语种： | 英文 |
| 作者： | Miao Yu1; Wei “David” Fan, Ph.D., P.E., M.ASCE2 |
| 作者单位： | 1INES Ph.D. Research Assistant, Dept. of Civil and Environmental Engineering, USDOT Center for Advanced Multimodal Mobility Solutions and Education, Univ. of North Carolina at Charlotte, EPIC Bldg., Room 3366, 9201 University City Blvd., Charlotte, NC 28223. 2Director, USDOT Center for Advanced Multimodal Mobility Solutions and Education, Univ. of North Carolina at Charlotte, Charlotte, NC 28223; Professor, Dept. of Civil and Environmental Engineering, Univ. of North Carolina at Charlotte, EPIC Bldg., Room 3261, 9201 University City Blvd., Charlotte, NC 28223 (corresponding author). |
| 关键词： | Variable speed limit; Connected autonomous vehicle; Optimization; Multiple bottlenecks |
| 摘要： | This study presents an optimal variable speed limit (VSL) strategy in a connected autonomous vehicle (CAV) environment for a freeway corridor with multiple bottlenecks. The VSL control was developed by using an extended cell transmission model (CTM) which takes into account capacity decrease and mixed traffic flow, including traditional human-driven cars and heavy vehicles, and autonomous vehicles (AVs). A multiple-objective function was formulated which aims to improve the operational efficiency and smooth the speed transition. A genetic algorithm (GA) was adopted to solve the integrated VSL control problem. A real-world freeway stretch was selected to test the designed control framework. Sensitivity analyses were performed to investigate impacts of both the penetration rate of CAVs and communication range. Simulation performances demonstrated that the developed VSL control not only improves the overall efficiency but also reduces tailpipe emission rate. Simulation results also showed that the VSL control integrating vehicle-to-vehicle (V2V), vehicleto- infrastructure (V2I), and infrastructure-to-vehicle (I2V) communication outperforms the VSL control only. In addition, as the penetration rate of CAVs increases, better performance can be achieved. |
| 出版年： | 2019 |
| 期刊名称： | Journal of Transportation Engineering |
| 卷： | 145 |
| 期： | 4 |
| 页码： | 1-16 |
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