Cooperative path and trajectory planning for autonomous vehicles on roads without lanes: A laboratory experimental demonstration
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. The controller is tested in two simulation case studies. The first examines the performance under two different plant (reality) models. The second considers dozens of vehicles and compares the traffic flow characteristics between the lane-free concept and the lane-based concept within different vehicle densities. The simulation 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. In order to demonstrate the proposed controller, three laboratory experiments with several homogeneous and heterogeneous robots were conducted.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
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Supplemental Notes:
- © 2022 Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
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Authors:
- Levy, Rotem
- Haddad, Jack
- Publication Date: 2022-11
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References; Tables;
- Pagination: 103813
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Serial:
- Transportation Research Part C: Emerging Technologies
- Volume: 144
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0968-090X
- Serial URL: http://www.sciencedirect.com/science/journal/0968090X
Subject/Index Terms
- TRT Terms: Automatic controllers; Autonomous vehicles; Road markings; Traffic flow; Traffic lanes; Trajectory control
- Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;
Filing Info
- Accession Number: 01861013
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 13 2022 9:25AM