Work towards MSc degree under the supervision of Assoc. Prof. Jack Hadad
When: 2.9.2021 at 15:00
Abstract: Autonomous vehicles traveling without considering the lane marks and utilizing all road width have an opportunity to maximize the 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. This research focuses on path and trajectory planning for fully autonomous vehicles without considering the lane marks by a proposed controller. This cooperative controller uses the nonlinear model predictive control (NMPC) approach for dozens of autonomous vehicles in the existing road infrastructure. The controller maximizes vehicles’ progress on the road with minimal control efforts while complying with the design constraints imposed by the road geometry, distances between vehicles, and vehicle dynamics. As a result, the controller generates the longitudinal acceleration and the steering rate inputs. The controller was tested on several case study simulations. The tests were done on closed-loop tracks and straight roads with different numbers of vehicles with identical vehicles’ parameters and different vehicles’ parameters to examine the advantages of the lane-free road concept. As part of the simulations, a comparison of the lane-free concept and the “traditional” lane concept showed that the lane-free concept proved to be better in the examined case studies. In addition, lab experiments were conducted on three robots performing several case studies.
You can watch the seminar here