Path Planning for Autonomous Vehicles

Path Planning for Autonomous Vehicles

Path planning for autonomous vehicles in dynamic environments is a challenging problem due to the constraints of vehicle dynamics and existence of surrounding vehicles. Typical trajectories of vehicles involve different modes of maneuvers, including lane keeping, lane change, ramp merging, and intersection crossing. Instead of using explicit rules, our work proposes a unified path planning approach using Model Predictive Control (MPC), which automatically decides the mode of maneuvers. To ensure safety, surrounding vehicles are modeled as polygons and corresponding constraints in MPC are enforced for collision avoidance. The results demonstrate the effectiveness of the proposed approach in automatically generating reasonable maneuvers while guaranteeing the safety.

Reference: https://media.wix.com/ugd/666bd6_d2e87360e40d4b0389b1877397c17d90.pdf

Distributed Bayesian Filters for Multi-Vehicle Network

Distributed Bayesian Filters for Multi-Vehicle Network

Autonomous Vehicle Control with Lidar

Autonomous Vehicle Control with Lidar