Integrated Path Planning and Lateral-Longitudinal Control for Autonomous Electric Vehicles

In this paper, an integrated path planning and tracking algorithm are presented. The proposed cascade structure consists of two parts. The outer loop is a predictive, optimization-based yaw rate reference planner that uses a path-based coordinate system handling the reference track as boundary constraints, seeking to find the maneuver with the possible minimal control effort. The inner loop is responsible for the lateral and longitudinal movement ensuring robustness against parameter changes and disturbances, using the Internal Model Control structure. The algorithm includes a minimal number of tuning parameters as the lateral planner path uses a physical phenomenon as a cost function. The effectiveness of the proposed structure is illustrated by simulation results. The algorithm was implemented in a real-time environment, and the tests performed on the Lotus Evora test vehicle developed by ThyssenKrupp are examined and evaluated.