Dynamic Control Method for CAV-Shared Lanes at Intersections in Mixed Traffic Flow

Xiyuan Hu, Mengying Li and Xiancai Jiang ()
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Xiyuan Hu: China Academy of Transportation Sciences, Beijing 100019, China
Mengying Li: School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China
Xiancai Jiang: School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China

Sustainability, 2024, vol. 16, issue 22, 1-20

Abstract: The existing signal control methods for mixed traffic related to connected automated vehicles (CAVs) and connected human-driven vehicles (CHVs) at intersections fail to tap the traffic potential of CAV-dedicated lanes. Accordingly, a dynamic allocation method of CAV-shared lanes is proposed, and the method of traffic flow scheduling and CAV trajectory optimization for multilane intersections with CAV-shared lanes is constructed to improve the traffic performance. The simulation results show that the optimization strategy proposed in this study can reduce the average delay at the intersection to varying degrees compared with the control strategy, using (a) the dynamic CAV-dedicated lane allocation method and (b) the shared-phase dedicated-lane method. Although the stops of CAVs will increase, the time utilization rate of most approach lanes is considerably improved, particularly CAV-shared lanes that can effectively improve the intersection performance. Further analysis shows that the number of CAV-shared lanes is closely dependent on the CAV penetration rate. The method proposed in this study is suitable for multilane intersections with a high CAV penetration rate.

Keywords: shared scheduling method; CAV-shared lane; trajectory optimization; mixed traffic (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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