HighwayEnv provides a collection of minimalist simulation environments for autonomous driving and tactical decision-making tasks. It is built on the Gymnasium (formerly Gym) framework, making it compatible with standard RL toolkits like Stable-Baselines3 and RLlib. The environments simulate highway traffic scenarios where agents learn to navigate, avoid collisions, and optimize driving behavior through reinforcement learning.