Optimal Variable Speed Limit Control in Connected Autonomous Vehicle Environment for Relieving Freeway CongestionSource: Journal of Transportation Engineering, Part A: Systems:;2019:;Volume ( 145 ):;issue: 004Author:Miao Yu; Wei “David” Fan
DOI: 10.1061/JTEPBS.0000227Publisher: American Society of Civil Engineers
Abstract: 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), vehicle-to-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.
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contributor author | Miao Yu; Wei “David” Fan | |
date accessioned | 2019-03-10T11:55:29Z | |
date available | 2019-03-10T11:55:29Z | |
date issued | 2019 | |
identifier other | JTEPBS.0000227.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4254504 | |
description abstract | 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), vehicle-to-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. | |
publisher | American Society of Civil Engineers | |
title | Optimal Variable Speed Limit Control in Connected Autonomous Vehicle Environment for Relieving Freeway Congestion | |
type | Journal Paper | |
journal volume | 145 | |
journal issue | 4 | |
journal title | Journal of Transportation Engineering, Part A: Systems | |
identifier doi | 10.1061/JTEPBS.0000227 | |
page | 04019007 | |
tree | Journal of Transportation Engineering, Part A: Systems:;2019:;Volume ( 145 ):;issue: 004 | |
contenttype | Fulltext |