Combining Event-Based Maneuver Selection and MPC Based Trajectory Generation in Autonomous Driving

Abstract

Maneuver planning, which plays a key role in selecting desired lanes and speeds, is an essential element of autonomous driving. Generally, for a vehicle driving on a multilane road, there are several potential maneuvers in both longitudinal and lateral directions. Selecting the best maneuver from the various options represents a significant challenge. In this paper, we propose a maneuver selection algorithm and combine it with a trajectory generation algorithm, which is based on model predictive control (MPC). The maneuver selection method is a higher-level planner, which selects only one maneuver from all possible maneuvers based on the current situation and delivers it to a lower-level MPC-based trajectory tracking controller. The effectiveness of the proposed algorithm is validated by simulating an overtaking scenario on a multilane highway.