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Development and Application of Dynamic Timing Optimization Platform for Big Data Intelligent Traffic Signals

机译:大数据智能交通信号动态时序优化平台的开发与应用

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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.
机译:随着汽车拥有量的增加,道路交通流量继续增加。同时,十字路口的交通压力也在增加。目前,中国的大多数交通信号灯都是固定周期控制。这种定时控制算法显然不能根据交通流量的变化及时进行调整。在这种情况下,将浪费大量的运输资源。建立大数据智能交通信号的动态计时系统是非常必要的。本研究采用视频识别方法实时获取十字路口的车辆数量,并通过优化算法对获得的数据进行处理,以实现交通信号的合理动态定时。测试结果表明,使用大数据智能交通信号动态时序优化控制平台后,在实验区域内,总的总延迟时间减少了23%,行驶时间减少了15%。在非高峰时段,实验区域中的总总延迟时间减少了17%,旅行时间减少了10%。大数据智能交通信号动态时序优化平台将提高现有交通基础设施的运营效率和交通供应能力,为市民提供真正的便利。

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