Unified strategy for cooperative optimization of pedestrian control patterns and signal timing plans at intersections

IF 2.8 3区 工程技术 Q3 TRANSPORTATION Journal of Intelligent Transportation Systems Pub Date : 2025-03-04 DOI:10.1080/15472450.2024.2307026
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Abstract

Pedestrian traffic management and control at intersections is crucial for ensuring traffic safety and efficiency while promoting green transportation development. Numerous studies have been conducted on optimizing signal timing of various pedestrian control patterns, such as exclusive pedestrian phases (EPPs) and leading pedestrian intervals (LPIs). However, cooperative optimization of these patterns and the corresponding signal timing is lacking. Hence, this study proposes a unified strategy for the cooperative optimization of pedestrian control patterns and signal timing plans to improve the efficiency and safety of pedestrian–vehicle mixed traffic flow. The existing control patterns, such as EPPs, LPIs, and two-way crossing (TWC), are unified. The safety and efficiency costs are monetized, and the minimization of average costs per traffic participant is taken as the optimization objective. Additionally, decision variables for diagonal crossing at intersections and pedestrian–vehicle priority are introduced to achieve cooperative optimization of the pedestrian control patterns and signal timing plans. The proposed model parameters were calibrated and validated using a real-world case study, and the applicable boundaries of different pedestrian control patterns under different pedestrian and vehicle flow scenarios were identified based on cost difference analysis. The results indicate that the vehicle turn ratio, average vehicle carrying rate, and unit cost ratio dynamically change the applicable boundaries. On average, the proposed method reduced the cost by 2.62% compared with separately optimized EPPs, LPIs, and TWC across various scenarios.
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交叉口行人控制模式和信号配时计划合作优化的统一策略
交叉口的行人交通管理和控制对于确保交通安全和效率,同时促进绿色交通发展至关重要。已有大量研究表明,在交叉路口进行行人交通管理和控制,不仅能确保交通安全和效率,还能促进绿色交通发展。
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来源期刊
CiteScore
8.80
自引率
19.40%
发文量
51
审稿时长
15 months
期刊介绍: The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new. The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption. The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.
期刊最新文献
Exploring traffic breakdown with vehicle-level data A cooperative longitudinal lane-changing distributions advisory for a freeway weaving segment Reliability-based journey time prediction via two-stream deep learning with multi-source data Unified strategy for cooperative optimization of pedestrian control patterns and signal timing plans at intersections Optimal lane allocation strategy for shared autonomous vehicles mixed with regular vehicles
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