Scheduling-Based Optimization for Motion Coordination of Autonomous Vehicles at Multilane Intersections
This paper considers the motion coordination problem of autonomous vehicles in an intersection of a traffic network. The featured challenge is the design of an intersection traffic manager, in the form of a supervisory control algorithm, that regulates the motion of the autonomous vehicles in the in...
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Veröffentlicht in: | Journal of Robotics 2020, Vol.2020 (2020), p.1-22 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper considers the motion coordination problem of autonomous vehicles in an intersection of a traffic network. The featured challenge is the design of an intersection traffic manager, in the form of a supervisory control algorithm, that regulates the motion of the autonomous vehicles in the intersection. We cast the multivehicle coordination task as an optimization problem, with a one-dimensional search-space. A model- and optimization-based heuristic method is employed to compute the control policy that results in the collision-free motion of the vehicles at the intersection and, at the same time, minimizes their delay. Our approach depends on a computation framework that makes the need for complex analytical derivations obsolete. A complete account of the computational complexity of the algorithm, parameterized by the configuration parameters of the problem, is provided. Extensive numerical simulations validate the applicability and performance of the proposed autonomous intersection traffic manager. |
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ISSN: | 1687-9600 1687-9619 |
DOI: | 10.1155/2020/6217409 |