期刊
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
卷 11, 期 1, 页码 -出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/21680566.2023.2231158
关键词
Construction work zone; bi-level model; stochastic user equilibrium; genetic algorithm; variational inequality; >
This study introduces an innovative bi-level model to address the challenges of managing traffic flow in construction work zones in urban transportation networks. The model integrates ramp closure, lane reorganization, and signal timing strategies within a network-level framework, thereby capturing the interdependencies between these strategies and enhancing the overall performance of the transportation network. A Genetic Algorithm (GA)-based heuristic method is proposed to solve the optimization problem, and a case study demonstrates the effectiveness of the proposed approach. This study offers a comprehensive and innovative solution to mitigate the negative impacts of detour traffic on urban transportation networks, assist transportation agencies in effectively managing traffic flow, and improve the overall system performance.
This study introduces an innovative bi-level model to address the challenges of managing traffic flow in construction work zones in urban transportation networks. The model integrates ramp closure, lane reorganization, and signal timing strategies within a network-level framework, thereby capturing the interdependencies between these strategies and enhancing the overall performance of the transportation network. The upper level optimizes the ramp closure locations, traffic control timing at signalized intersections and lane reorganization plans, whereas the lower level determines the optimal routing choice and traffic detour based on a Stochastic User Equilibrium (SUE) model. A Genetic Algorithm (GA)-based heuristic method is proposed to solve the optimization problem, and a case study demonstrates the effectiveness of the proposed approach. This study offers a comprehensive and innovative solution to mitigate the negative impacts of detour traffic on urban transportation networks, assist transportation agencies in effectively managing traffic flow and improve the overall system performance.
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