Scenario based traffic optimization in Egypt performance gains through simulation modeling

基于场景的埃及交通优化通过仿真建模提升性能

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Abstract

Rapid urbanization and the growing number of vehicles in Mansoura, Egypt, have exacerbated traffic congestion, underscoring the need for efficient urban traffic management solutions. This study evaluates traffic control strategies at Umm Kulthum Square using the SUMO (Simulation of Urban Mobility) software. Two scenarios were analyzed: Scenario 1 represents existing traffic conditions, with road geometry and lane counts adjusted to real-world dimensions derived from satellite imagery, while Scenario 2 applies optimized lane connections, turning movements, and traffic signal configurations, including signal locations, phase durations, and signal states. Simulations were conducted for 999 s and 3599 s to evaluate traffic performance, queuing behavior, emissions, fuel consumption, and noise levels. Compared with Scenario 1, Scenario 2 reduced average departure delay from 6.02 to 5.54 s at 999 s and from 32.63 to 7.08 s at 3599 s. Average travel duration decreased from 414.19 to 349.25 s and from 388.60 to 246.15 s, while waiting time was reduced from 139.90 to 100.90 s and from 288.21 to 143.70 s, respectively. The number of completed trips increased from 262 to 317 vehicles at 999 s and from 672 to 715 vehicles at 3599 s. Environmental performance also improved, with notable reductions in CO₂, CO, HC, NOx, and PMx emissions, as well as fuel consumption and noise levels. Additionally, queuing time and queue lengths decreased, indicating smoother traffic flow. These results demonstrate that traffic signal optimization and intersection design improvements can significantly enhance traffic efficiency and reduce environmental impacts at congested urban intersections in Mansoura.

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