ITSC 2024 Paper Abstract

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Paper WeAT4.5

Yang, Yuanxiang (Aalto University), Liu, Yu (Aalto University), Roncoli, Claudio (Aalto University)

A Macro-Micro Lane Changing Strategy for Congestion Mitigation in Mixed Traffic

Scheduled for presentation during the Invited Session "Traffic Control and Connected Autonomous Vehicles: benefits for efficiency, safety and beyond (2 edition) I" (WeAT4), Wednesday, September 25, 2024, 11:50−12:10, Salon 8

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Keywords Road Traffic Control, Multi-autonomous Vehicle Studies, Models, Techniques and Simulations

Abstract

This paper presents an integrated approach to mitigate congestion and improve road utilization near bottlenecks in mixed traffic environments with human-driven vehicles and connected automated vehicles (CAVs). This approach integrates two core elements: a macroscopic tactical lane controller and a microscopic trajectory planner. The objective of the tactical lane controller is to proactively redistribute traffic flow into the designed optimal configuration before reaching congestion bottlenecks, thereby minimizing disruptions to CAVs movements. Bézier curves are employed within the trajectory planner to define both lateral and longitudinal trajectories during the lane-changing process. Additionally, diverse models of game theory are utilized to anticipate interactions between vehicles in various scenarios. The proposed approach's effectiveness is validated through numerical simulation in a lane-drop scenario, demonstrating significant improvements in congestion mitigation.

 

 

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