Traffic Intersection Optimization Based on Random Forest and SUMO Simulation in Xi’an

Xianqi Dai

2024

Abstract

With the rapid pace of urbanization, traffic congestion, especially at intersections, has become a significant challenge in cities like Xi'an, China. This study conducted a comprehensive analysis of traffic congestion issues, with a specific focus on the intersection of Shang Hong Road and Shang Ji Road, a critical bottleneck area in Xi'an City. Utilizing AutoCAD for road layout optimization design, the paper simulated the optimized solution using the SUMO simulation tool. Furthermore, a random forest model was employed to predict traffic flow, leading to recommendations for optimizing signal light duration and lane configuration. The research findings indicate that an enhanced traffic network design and signal light configuration can significantly improve intersection throughput, reduce delay times, and enhance traffic safety. This study provides scientifically grounded optimization suggestions for urban traffic management authorities, offering practical measures to improve traffic efficiency, alleviate congestion, and contribute to safer and more sustainable urban environments.

Paper Citation

in Harvard Style

Dai X. (2024). Traffic Intersection Optimization Based on Random Forest and SUMO Simulation in Xi’an. In Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM; ISBN 978-989-758-738-2, SciTePress, pages 301-309. DOI: 10.5220/0013329600004558

in Bibtex Style

@conference{mlscm24,
author={Xianqi Dai},
title={Traffic Intersection Optimization Based on Random Forest and SUMO Simulation in Xi’an},
booktitle={Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM},
year={2024},
pages={301-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013329600004558},
isbn={978-989-758-738-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM
TI - Traffic Intersection Optimization Based on Random Forest and SUMO Simulation in Xi’an
SN - 978-989-758-738-2
AU - Dai X.
PY - 2024
SP - 301
EP - 309
DO - 10.5220/0013329600004558
PB - SciTePress