Robust Optimization of Signal Control Parameters for Unsaturated Intersection Based on Tabu Search-Artificial Bee Colony Algorithm | Zendy

Wei Hao | Zendy; Changxi Ma | Zendy; Bahman Moghimi | Zendy; Yuanyuan Fan | Zendy; Zhibo Gao | Zendy

Open Access

Robust Optimization of Signal Control Parameters for Unsaturated Intersection Based on Tabu Search-Artificial Bee Colony Algorithm

Author(s) -

Wei Hao,

Changxi Ma,

Bahman Moghimi,

Yuanyuan Fan,

Zhibo Gao

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2845673

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In order to overcome the drawback of the conventional signal timing optimization, a robust optimization algorithm for signal control parameters based on Tabu search-artificial bee colony algorithm is proposed under unsaturated flow condition. Based on the analysis of the characteristics of traffic signal control, a robust optimization model of signal control parameters is constructed by considering the minimum the average delay and the mean square error of average delay. As a consequence, the formation process of the initial solution to the bee colony is improved and the robust optimization model is solved by using the Tabu search-artificial bee colony algorithm. The proposed robust optimization model is validated by using an intersection in Zhangye City of China. The simulation results have shown that the robust optimization model and the algorithm are feasible and practicable. This robust model and algorithm can effectively deal with the volatility of traffic flow and reduce traffic delays.

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