Ego-efficient lane changes of connected and automated vehicles with impacts on traffic flow
Abstract
Background & Significance: connected and automated vehicles (CAVs) with wireless communication and vehicle automation will transform road transport. Impacts of CAVs on traffic flow are still uncertain, but it is vital to understand the impacts as early as possible. Aim & purpose: This paper addresses lane-changing impacts of CAVs on traffic flow of human-driven vehicles and CAVs, and focuses on three important perspective questions. Methods & solutions: Machine learning methods and large-scale microscopic traffic simulation were based on for the answers. Results & Conclusions: Interesting and inspiring results were obtained, indicating that CAVs may not simply be a magic cure for the current traffic problems, unless some upper-level coordination may be proposed for CAVs to benefit not only themselves but also the entire traffic flow.
- Publication:
-
Transportation Research Part C: Emerging Technologies
- Pub Date:
- May 2022
- DOI:
- 10.1016/j.trc.2021.103478
- Bibcode:
- 2022TRPC..13803478W
- Keywords:
-
- Connected and Automated Vehicles;
- Ego-efficient Lane Changes;
- Traffic Flow Impacts;
- Microscopic Simulation;
- Reinforcement Learning