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Metaheuristic approach for designing robust traffic signal timings to effectively serve varying traffic demand
| 题名： | Metaheuristic approach for designing robust traffic signal timings to effectively serve varying traffic demand |
| 正文语种： | eng |
| 作者： | Chaitrali Shirke;Nasser Sabar;Edward Chung;Ashish Bhaskar |
| 作者单位： | Civil and Environment Engineering Queensland University of Technology;Department of Computer Science and Information Technology La Trobe University;Department of Electrical Engineering Hong Kong Polytechnic University;Civil and Environment Engineering Queensland University of Technology |
| 关键词： | Day to day variation;fixed time traffic signals;metaheuristic approach;robust traffic signal;varying traffic demand |
| 摘要： | Abstract Traffic demands at intersections vary across various periods of a day and from day to day. Generally, fixed time traffic signals are designed considering the average traffic flows across multiple days over a predetermined time interval. This approach overlooks the day to day variability in traffic demand, leading to inefficient and unreliable signal control performance. A signal plan should be robust such that it is less sensitive to demand variations and can maintain near-optimal performance during varying traffic demand. To address this need, the paper presents a new offline scenario-based framework, named Metaheuristic Robust plan Approach (MHRA), that identifies a robust plan for fixed time signals. MHRA includes a heuristic that considers optimum signal plan for various demand scenarios and corresponding costs to find a robust solution. The numerical experiments are performed using realistic traffic demand scenarios on an arterial corridor to verify the MHRA framework. The outcomes concluded that the framework produces a robust signal plan that outperforms a nominal signal plan based on average traffic demand and maintains stable performance under varying demand. Benchmarking MHRA with other scenario-based approaches proposed in the literature such as mean-variance optimization and conditional value at risk minimization confirms better efficiency for MHRA. |
| 出版年： | 2022 |
| 期刊名称： | Journal of Intelligent Transportation Systems |
| 卷： | 26 |
| 期： | 1/6 |
| 页码： | 348-360 |
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