Path and Trajectory Planning for Autonomous Vehicles on Roads without Lanes

Abstract

Compared to typical drivers of human-driven vehicles, autonomous vehicles can maximize the use of vehicle performance by utilizing a full road width without tracking the center of the road lanes. Exploiting the full width allows new path planning options while using the existing road infrastructure. This research focuses on trajectory planning and control for fully autonomous vehicles without considering the lane marks. In this paper, a controller is designed using the nonlinear Model Predictive Control approach for the movements of autonomous vehicles group on roads without lanes. After ensuring that the vehicles avoid collisions, the controller generates the desired longitudinal acceleration and steering rate inputs. The goal is to maximize vehicles' progress on the road with minimum control efforts, where the constraints are the road geometry layouts and vehicle dynamics. The proposed controller was tested on three case study simulations for several vehicles to examine the advantages of the lane-free road concept for path and trajectory planning of autonomous vehicles.