Citation

Zheng L, Li X. Comput. Aided Civil Infrastruct. Eng. 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, John Wiley and Sons)

DOI

10.1111/mice.12876

PMID

unavailable

Abstract

This paper proposes an arterial signal control stochastic simulation-based optimization model with traffic safety and efficiency as biobjectives and solves it by a biobjective surrogate-based promising area search (BOSPAS) method. In this model, traffic safety and efficiency are indexed by the average potential collision energy (APCE) and the vehicular throughput of the arterial road, respectively, and the arterial signal control plan is designed in a ring-and-barrier structure. In the BOSPAS method, each solution is evaluated by traffic simulation only once and stochastic evaluation noises of the sampled solutions are smoothed by a shrinking ball method to approximate their biobjective expectations. Based on the solutions and their estimated biobjective values, two surrogate models of biobjectives are constructed and optimized to obtain the nondominated solutions, which will guide the establishment of the joint promising area for sampling in the next iteration. In the numerical experiments, BOSPAS is first tested to outperform three other counterparts (i.e., nondominated sorting genetic algorithm II [NSGA-II], biobjective efficient global optimization [BOEGO], and biobjective promising area search [BOPAS]) by a stochastic FON function from the aspects of convergence and diversity. It is then applied to optimize the signal control plan of an arterial road with six four-leg signalized intersections in Changsha, China. The numerical results show that the nondominated solutions by BOSPAS perform better than those by NSGA-II, BOEGO, and BOPAS under limited simulation budgets, and also mostly outperform three solutions by Synchro, MAXBAND, and MULTIBAND, especially in reducing APCE. In contrast with the field-implemented signal plan, the optimized ones by BOSPAS improve the APCE and the vehicular throughput of the arterial road by at most 50.2% and 24.8%, respectively. Moreover, considering the vehicular throughput of arterial road as one objective may have a negative effect on the vehicular throughput of the overall road network. In conclusion, BOSPAS is promising to address biobjective optimization problems characterized by costly evaluation, high dimensions, and stochastic noises.

Language: en