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Optimization of Adaptive Transit Signal Priority Using Parallel Genetic Algorithm 被引量:15
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作者 Guangwei Zhou Albert Gan L. David Shen 《Tsinghua Science and Technology》 SCIE EI CAS 2007年第2期131-140,共10页
Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This paper presents an adaptive transit signal priority (TSP) strategy that applies the parallel genetic... Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This paper presents an adaptive transit signal priority (TSP) strategy that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of TSP. The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. A VISSIM (VISual SIMulation) simulation testbed was developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer can produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. 展开更多
关键词 adaptive traffic signal control transit signal priority parallel genetic algorithm traffic simulation traffic delay
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