Cyber-Physical System for Smart Traffic Light Control
Author:
Deshpande Siddhesh1ORCID, Hsieh Sheng-Jen1ORCID
Affiliation:
1. Engineering Technology and Industrial Distribution Department, Texas A&M University, College Station, TX 77843, USA
Abstract
In recent years, researchers have proposed smart traffic light control systems to improve traffic flow at intersections, but there is less focus on reducing vehicle and pedestrian delays simultaneously. This research proposes a cyber-physical system for smart traffic light control utilizing traffic detection cameras, machine learning algorithms, and a ladder logic program. The proposed method employs a dynamic traffic interval technique that categorizes traffic into low, medium, high, and very high volumes. It adjusts traffic light intervals based on real-time traffic data, including pedestrian and vehicle information. Machine learning algorithms, including convolutional neural network (CNN), artificial neural network (ANN), and support vector machine (SVM), are demonstrated to predict traffic conditions and traffic light timings. To validate the proposed method, the Simulation of Urban Mobility (SUMO) platform was used to simulate the real-world intersection working. The simulation result indicates the dynamic traffic interval technique is more efficient and showcases a 12% to 27% reduction in the waiting time of vehicles and a 9% to 23% reduction in the waiting time of pedestrians at an intersection when compared to the fixed time and semi-dynamic traffic light control methods.
Funder
Texas A&M-FAPESP Texas A&M University
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference46 articles.
1. (2023, May 10). Manual on Uniform Traffic Control Devices for Streets and Highways, Available online: https://mutcd.fhwa.dot.gov/pdfs/2009/mutcd2009edition.pdf. 2. Simulation study of vehicle travel time on route with signals considering comprehensive influencing factors;Lv;Phys. A Stat. Mech. its Appl.,2019 3. Urbanik, T., Tanaka, A., Lozner, B., Lindstrom, E., Lee, K., Quayle, S., Beaird, S., Tsoi, S., Ryus, P., and Gettman, R. (2015). Signal Timing Manual. 4. (2016). Highway Capacity Manual: A Guide for Multimodal Mobility Analysis. 5. Ghazal, B., ElKhatib, G., Chahine, K., and Kherfan, M. (2016, January 21–23). Smart traffic light control system. Proceedings of the 2016 Third International Conference on Electrical, Electronics, Computer Engineering and Their Applications (EECEA), Beirut, Lebanon.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|