M.Sc Thesis


M.Sc StudentLevy Rotem
SubjectAutonomous Vehicles Motion Planning and Control without
Lanes
DepartmentDepartment of Autonomous Systems and Robotics
Supervisor ASSOCIATE PROF. Jack Haddad


Abstract

Autonomous vehicles that travel without considering the lane marks and utilizing all road width have an opportunity to maximize the use of vehicles’ performance. By taking advantage of the entire width of curvy roads and the cooperative behavior of connected autonomous vehicles, new options for path planning can be implemented while utilizing the existing infrastructure.

The proposed cooperative controller uses a nonlinear model predictive control (NMPC) approach for dozens of autonomous vehicles without considering lane marks. This controller maximizes vehicles’ progress on the road with minimal control efforts while complying with design constraints imposed by road geometry, distances between vehicles, and vehicle dynamics. As a result, the controller generates longitudinal acceleration and steering rate inputs utilizing a kinematic bicycle model.

The controller is tested in five simulation case studies and three laboratory experiments for several homogeneous and heterogeneous robots. The first simulation compares the lap times between the lane-free roads concept and the “traditional” lane roads concept for two vehicles. The second simulation considers three vehicles and examines the change in the vehicle formation along the road with multiple curves. Unlike examples one and two, where the vehicles are assumed to be identical, example three tests the NMPC controller for heterogeneous vehicles on a straight road. The fourth simulation study examines the controller performance under two different plant models (reality), i.e., (i) the same kinematic bicycle model of the controller and (ii) a dynamic bicycle model. The fifth simulation case study considers dozens of vehicles on a closed two-lane road track, and compares the objective function values and the traffic flow characteristics between the lane-free concept and the lane-based concept.

Finally, the simulation results are supported by laboratory experiments, as the proposed controller is tested in three different experiments with three robots: (i) homogeneous robots on a curvy track, (ii) heterogeneous robots on a straight track, and (iii) heterogeneous robots on a curvy track.

Both simulation and laboratory experiments results show that the lane free concept can improve the traffic flow performance compared with the lane-based road concept, i.e., reducing passengers’ time on the road, reducing energy consumption, and increasing road capacity. These improvements depend on the road density and track layout. Furthermore, the results show also that the proposed controller is feasible and robust for real future applications.