A Collaborative Merging Strategy with Lane Changing in Multilane Freeway On-Ramp Area with V2X Network

Yanjun Shi, Hao Yu, Yijia Guo and Zhiheng Yuan
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Yanjun Shi: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Hao Yu: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Yijia Guo: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Zhiheng Yuan: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China

Future Internet, 2021, vol. 13, issue 5, 1-16

Abstract: The merging area of the freeway is an area with a high incidence of traffic accidents. With the development of connected and automated vehicles (CAVs) and V2X technology, the traffic efficiency of freeway ramp areas has been significantly improved. However, current research mostly focuses on merging a single mainline lane and ramp, and there are few cases of multiple lanes. In this paper, we present a collaborative merging model with a rule-based lane-changing strategy in a V2X environment. First, the vehicle selects the appropriate gap to change lanes safely without affecting other vehicles. Meanwhile, we established a linear time discrete model to optimize the trajectory of vehicles in real-time. Finally, the proposed model and strategy were implemented in SUMO and Python. The simulation results showed that the merging model we proposed based on the lane-changing strategy had good performance in terms of the number of stops, average delay, and average speed.

Keywords: freeway; on-ramp; lane-changing; connected and automated vehicles; trajectory optimization (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
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