Issue |
E3S Web Conf.
Volume 136, 2019
2019 International Conference on Building Energy Conservation, Thermal Safety and Environmental Pollution Control (ICBTE 2019)
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Article Number | 01008 | |
Number of page(s) | 4 | |
Section | Ultra-Low Energy Consumption Building Technology | |
DOI | https://doi.org/10.1051/e3sconf/201913601008 | |
Published online | 10 December 2019 |
Development and Application of Dynamic Timing Optimization Platform for Big Data Intelligent Traffic Signals
1 Big Data Research Center, Jianghan University, Wuhan, Hubei, 430056, China
2 Big Data Research Center, Jianghan University, Wuhan, Hubei, 430056, China
3 YiBen Investment Fund, New York, 10005, United States
As the number of car ownership increases, road traffic flow continues to increase. At the same time, traffic pressure at intersections is increasing as well. At present, most of the traffic lights in China are fixed cycle control. This timing control algorithm obviously cannot make timely adjustments according to changes in traffic flow. In this case, a large number of transportation resources would be wasted. It is very necessary to establish a dynamic timing system for Big data intelligent traffic signals. In this research, the video recognition method was used to acquire the number of vehicles at the intersection in real time, and the obtained data was processed by the optimization algorithm to make a reasonable dynamic timing of the traffic signals. The test results show that after using the big data intelligent traffic signal dynamic timing optimization control platform, in the experimental area, the overall total delay time was reduced by 23%, and the travel time was reduced by 15%. During the off-peak period, the overall total delay time in the experimental region was reduced by 17% and travel time was reduced by 10%. The big data intelligent traffic signal dynamic timing optimization platform would improve the operational efficiency and traffic supply capacity of the existing transportation infrastructure, and could provide real convenience for citizens.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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