To guarantee safe and efficient driving for automated vehicles in complicated traffic conditions, the motion planning module of automated vehicles are expected to generate collision-free driving policies as soon as possible in varying traffic environment. However, there always exist a tradeoff between efficiency and accuracy for the motion plann…

Codes for "Balancing Computation Speed and Quality: A Decentralized Motion Planning Method for Cooperative Lane Changes of Connected and Automated Vehicles"

Codes of "Cooperative Lane Change Motion Planning of Connected and Automated Vehicles: A Stepwise Computational Framework"

SwapTransformer: Highway Overtaking Tactical Planner Model via Imitation Learning on OSHA Dataset

A collaborative project for autonomous vehicles, focusing on cooperative lane changing by sharing route information among cars to enhance traffic flow and improve road safety.

Path planner that creates smooth, safe trajectories for an autonomous vehicle to follow along a 3 lane highway with traffic. The path planner is able to keep inside its lane, avoid hitting other cars, and pass slower moving traffic all by using localization, sensor fusion, and map data.

Cost function based lane selection, path planning and trajectory interpolation

Frontend of crowdsourced experiment on acceptance the AI-based lane changes of an automated car.