Research

Autonomous Vehicle

Path planning

  • Global path planning in K-City(1) (2019)

  • Global path planning in K-City(2) (2019)

  • HD map based local path planning (2018)

Introduction of Research

The autonomous vehicles use path planning algorithms to arrive at the destination and avoid collision when obstacles appear ahead while driving.

We have conducted global path planning that determines the fastest path between the start point and the goal point on the HD map, and local path planning that avoids collision situation.

Research Achievements

Global path planning considers the maximum steer angle of the vehicle and creates the safest path to the center of the lane with an HD map.

Local path planning identifies the location and direction of ego vehicle and surrounding objects using the output of perception and localization and creates the optimal path in real-time to avoid the collision.