Arterial traffic signal optimization: A person-based approach

Christofa, Eleni; Ampountolas, Konstantinos; Skabardonis, Alexander · 2015 · OpenAlex-citations

DOI: 10.1016/j.trc.2015.11.009

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Summary

This paper addresses the need for more efficient multimodal traffic signal control systems that prioritize person mobility over vehicle throughput. While existing real-time signal control systems often minimize vehicle delays or apply transit priority through rigid rules, few explicitly minimize person delay across arterial networks. The authors identify critical gaps in current literature, noting that many systems fail to efficiently resolve conflicts when multiple transit vehicles travel in opposing directions, ignore the importance of transit schedule adherence, or suffer from high computation times that hinder real-world implementation. To address these issues, the study proposes a real-time signal control system that optimizes signal settings by minimizing total person delay, explicitly accounting for passenger occupancy in both autos and transit vehicles. The methodology employs a mixed-integer linear programming model based on a pairwise optimization strategy. The system optimizes signal timings for consecutive pairs of intersections along an arterial, starting from a critical intersection and proceeding sequentially. This approach maintains auto vehicle progression by incorporating delays associated with interrupting vehicle platoons. The objective function minimizes the sum of delays for all passengers, weighting auto delays by occupancy and transit delays by occupancy plus a schedule adherence factor. This additional weighting prioritizes transit vehicles that are behind schedule, providing a mechanism to resolve conflicts between transit routes traveling in opposite directions. The model utilizes readily available data from vehicle detectors, Automated Vehicle Location (AVL), and Automated Passenger Counter (APC) systems, ensuring low computation times suitable for real-time application. The proposed system was tested on a four-intersection segment of San Pablo Avenue in Berkeley, California, under both deterministic and stochastic arrival conditions. Performance was benchmarked against optimal fixed-time signal settings generated by TRANSYT-7F, a state-of-the-art offline optimization software. The results demonstrate that the person-based approach outperforms the pretimed optimal settings by significantly reducing total person delay. Specifically, the system successfully reduced bus person delay by efficiently assigning priority to transit vehicles, even in scenarios involving conflicting transit routes. The findings confirm that the system can handle multiple priority requests and stochastic traffic variations while maintaining computational efficiency. The significance of this work lies in its advancement of traffic-responsive signal control toward person-centric optimization. By integrating passenger occupancy and schedule adherence into the optimization process, the system offers a robust solution for managing multimodal traffic on arterials. It resolves the complex issue of conflicting transit priorities without relying on pre-selected rules or high-penetration connected vehicle data. The low computation time and reliance on existing surveillance technologies enhance the feasibility of deploying such systems in real-world settings, offering a cost-effective method to improve the efficiency and sustainability of urban transportation networks.

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