Communication and coordination for urban intelligent transportation: architecture and algorithms

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2022-2-10
Atagoziev, Maksat
In the scope of Intelligent Transportation Systems (ITS), the automation and coordination of connected and autonomous vehicle (CAV) lane changes (LCs) have a strong impact on driving safety and traffic throughput. Accordingly, this thesis develops algorithms for the coordination of CAV LCs that are then used for controlling the traffic at intersections. First, this thesis focuses on the coordination of LCs of a group of CAVs to minimize the time when all LCs are completed, while keeping small inter-vehicle distances. The thesis first develops an algorithm for minimizing the LC time of a single CAV. This algorithm is then successively applied to compute trajectories for all lane changing CAVs. All computations can be carried out in real time and the CAV trajectories can be implemented using cooperative adaptive cruise control to ensure safe driving in a tight vehicle formation. Simulation experiments and a comparison to a benchmark method demonstrate the superior performance of our method. Then, the thesis concentrates on the coordination of traffic at an intersection based on the developed CAV LC coordination algorithm. The proposed method divides CAVs approaching the intersection into groups that pass the intersection successively. In each group, LCs are coordinated and the trajectories of CAVs are computed such that they travel in a tight formation. Interleaving the groups coming from different directions makes it possible to avoid stopping at the intersection. A detailed simulation study confirms that the proposed approach provides significant performance improvements in terms of average travel and delay times.

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Citation Formats
M. Atagoziev, “Communication and coordination for urban intelligent transportation: architecture and algorithms,” Ph.D. - Doctoral Program, Middle East Technical University, 2022.