Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment
Abstract
We develop a multi-objective cooperative deep reinforcement learning based CAV car following control strategy for a mixed traffic. We embed the concept of equilibrium point inside deep reinforcement learning which facilitates algorithm convergence and stability of mixed traffic. We embed the HDV characteristic inside the environment of deep reinforcement learning to further improve the performance of control. We analyze the vehicle sequencing impact on the mixed traffic.
- Publication:
-
Transportation Research Part C: Emerging Technologies
- Pub Date:
- December 2021
- DOI:
- 10.1016/j.trc.2021.103421
- Bibcode:
- 2021TRPC..13303421S
- Keywords:
-
- Mixed connected automated traffic environment;
- Cooperative control;
- Deep reinforcement learning;
- Traffic oscillation dampening;
- Energy efficiency