The invention relates to the technical field of traffic roads, and provides a lane traffic capacity prediction method and system based on big data analysis. The method comprises the following steps: performing multi-angle acquisition on a target lane based on image acquisition equipment to obtain multi-angle lane information; obtaining basic data of a target lane; monitoring the state in the target lane based on an infrared detection technology; based on a real-time theoretical traffic model, outputting a theoretical traffic flow with a time identifier, and pre-judging a theoretical driving track of a target vehicle according to the theoretical traffic flow with the time identifier; acquiring an actual track of the target vehicle based on a path tracking algorithm; and performing deviation analysis, and predicting the traffic capacity of the target lane based on a deviation analysis result. According to the method and the device, the technical problems of huge investigation workload, relatively low accuracy of acquired data and relatively low reliability in the prior art are solved, and the technical effect of improving the prediction accuracy of the vehicle road traffic capacity is achieved.
本申请涉及交通道路技术领域,提供基于大数据分析的车道通行能力预测方法及系统。所述方法包括:基于图像采集设备对目标车道进行多角度采集,获取多角度车道信息;获取目标车道基础数据;基于红外探测技术,对所述目标车道内的状态进行监测;基于实时理论通行模型,输出具有时间标识的理论车流量,根据所述具有时间标识的理论车流量对目标车辆的理论行驶轨迹进行预判;基于路径跟踪算法获取目标车辆的实际轨迹;进行偏差分析,基于偏差分析结果对所述目标车道的通行能力进行预测。本申请解决了现有技术中调查的工作量巨大,获取数据精准度较低,可靠度较低的技术问题,达到了提高车辆道路通行能力的预测精准度技术效果。
Lane traffic capacity prediction method and system based on big data analysis
基于大数据分析的车道通行能力预测方法及系统
2023-11-07
Patent
Electronic Resource
Chinese
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