Simulation Analysis and Improvement of the Vehicle Queuing System on Intersections Based on MATLAB

Wang, Fuyu; Ye, Chunming; Zhang, Yanan; Li, Yan · 2015 · OpenAlex-citations

DOI: 10.2174/1874110x01408010217

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Summary

This study addresses the critical issue of urban traffic congestion, specifically focusing on vehicle queuing at road intersections. Motivated by the rapid growth of motor vehicles in China and the resulting overload of urban road networks, the authors aim to reduce waiting times and enhance intersection capacity. The research identifies intersections as the primary bottleneck in urban traffic systems, where congestion leads to increased accidents, pollution, and economic inefficiency. The paper seeks to optimize intersection operations through a combination of queuing theory, facilities planning, and management systems. The methodology involves a case study of the five-fork intersection of Jiangdong Road and Hunan Road in Maanshan City. The authors conducted five days of on-site field research to collect data on traffic flow, vehicle arrival intervals, service times, and traffic light durations. This empirical data was used to construct frequency distribution tables for vehicle arrivals and service times. To analyze the system, the authors developed a simulation model based on the Monte Carlo method and the M/M/1 queuing model, implemented using MATLAB. The simulation logic accounts for random variables such as arrival intervals and service times, calculating key performance indicators including average waiting time, average length of stay, and the number of vehicles in the system. The results demonstrate that the theoretical values derived from the simulation closely matched the analog (simulated) values, validating the model's accuracy. Analysis of the five intersection approaches revealed significant disparities in performance. Intersection 1 exhibited a service intensity of 94%, indicating a high probability (94%) that vehicles would need to wait, with an average waiting time of 97.76 seconds. In contrast, Intersections 2 through 5 showed lower service intensities (approximately 80%) and significantly shorter waiting times (around 26–27 seconds). The study identifies Intersection 1 as the primary source of congestion, noting that its service intensity is 14% higher and its average waiting time is 67% longer than the other intersections. The authors suggest that an optimal service intensity is around 70–80%, implying that Intersection 1 is over-utilized and requires structural or managerial improvements. The significance of this work lies in providing a quantitative, simulation-based approach to diagnosing and improving intersection efficiency. By identifying specific bottlenecks, such as the uneven outlet arrangement at Intersection 1, the study offers actionable insights for urban planners and government departments. The findings support the need for redesigning facility layouts, optimizing traffic light durations, and balancing traffic flow across different lanes. The paper concludes that while the simulation model effectively represents actual system behavior, further research is needed to address broader socioeconomic and environmental factors associated with traffic management.

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• traffic density