Algorithmic Identification of Conflicting Traffic Lights: A Large-Scale Approach with a Network Conflict Matrix

Efficient urban traffic management is crucial for mitigating congestion and enhancing road safety. This study introduces a novel algorithm, with code provided, to generate a traffic light conflict matrix, identifying potential signal conflicts solely based on road network topology. Unlike existing graphical approaches that are difficult to execute automatically, our method leverages readily available topological data and adjacency matrices, ensuring broad applicability and automation. While our approach deliberately focuses on topology as a stable foundation, it is designed to complement rather than replace dynamic traffic analysis, serving as an essential preprocessing layer for subsequent temporal optimization. Implemented in MATLAB, with specific functionality for Vissim users, the algorithm has been tested on various networks with up to 547 traffic lights, demonstrating high efficiency, even in complex scenarios. This tool enables focused allocation of computational resources for traffic light optimization and is particularly valuable for prioritizing emergency vehicles. Our findings make a significant contribution to traffic management strategies by offering a scalable and efficient tool that bridges critical gaps in current research. As urban areas continue to grow, this algorithm represents a step forward in developing sustainable solutions for modern transportation challenges.

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Publication Details

Journal
Systems
Published
2025-04-15
DOI
https://doi.org/10.3390/systems13040290
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Algorithmic Identification of Conflicting Traffic Lights: A Large-Scale Approach with a Network Conflict Matrix

Manuel Otero-Mateo, Alberto Cerezo-Narváez, S. Sáez, Sergio Rojas
Systems
Traffic Prediction and Management Techniques
article

Algorithmic Identification of Conflicting Traffic Lights: A Large-Scale Approach with a Network Conflict Matrix

Manuel Otero-Mateo, Alberto Cerezo-Narváez, S. Sáez, Sergio Rojas
article en

Abstract

Efficient urban traffic management is crucial for mitigating congestion and enhancing road safety. This study introduces a novel algorithm, with code provided, to generate a traffic light conflict matrix, identifying potential signal conflicts solely based on road network topology. Unlike existing graphical approaches that are difficult to execute automatically, our method leverages readily available topological data and adjacency matrices, ensuring broad applicability and automation. While our approach deliberately focuses on topology as a stable foundation, it is designed to complement rather than replace dynamic traffic analysis, serving as an essential preprocessing layer for subsequent temporal optimization. Implemented in MATLAB, with specific functionality for Vissim users, the algorithm has been tested on various networks with up to 547 traffic lights, demonstrating high efficiency, even in complex scenarios. This tool enables focused allocation of computational resources for traffic light optimization and is particularly valuable for prioritizing emergency vehicles. Our findings make a significant contribution to traffic management strategies by offering a scalable and efficient tool that bridges critical gaps in current research. As urban areas continue to grow, this algorithm represents a step forward in developing sustainable solutions for modern transportation challenges.

SystemsVol. 13(4)
Universidad de Cádiz (ES)
Universidad de Cádiz
Openalex Percentile: Top 93%
Traffic Prediction and Management Techniques
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