vehicle-platoon-gym
A gym-compatible reinforcement learning environment for longitudinal vehicle platoon control and fuel efficiency optimization.
A Python reinforcement learning environment built on the OpenAI Gym API that simulates longitudinal vehicle platoon dynamics. The agent learns to optimize fuel efficiency by switching between Adaptive Cruise Control (ACC) parameters in the presence of a stochastic jammer vehicle.
Key features:
- OpenAI Gym-compatible API
- Models a 1D platoon with stochastic disturbances (jammer vehicle)
- Designed to reproduce and extend the results from (Cunha et al., 2022) and (Gonçalves et al., 2023)