The invention relates to an urban main road multi-vehicle trajectory reconstruction method based on multi-source data. The method comprises the steps that S1, floating vehicle GPS data and gate video data in urban multi-source heterogeneous data are acquired; s2, screening bayonet data according to the position of the main road; s3, extracting a license plate number in the checkpoint data set as a feature attribute of data fusion; s4, the time when the vehicle enters the road section and the time when the vehicle leaves the road section in the checkpoint data set are extracted, and the travel time of the floating vehicle in the main road is obtained; and S5, opening the floating car GPS file passing through the road section in the step S4, and segmenting the GPS floating car file by taking the travel time as a data segmentation standard to obtain data of all floating cars in a driving time period on the road section. According to the method, the urban main road traffic state can be accurately estimated, the traffic jam propagation rule is analyzed, and urban jam treatment decision analysis is supported.
本发明涉及一种基于多源数据的城市主干道多车轨迹重构方法,包括S1、获取城市多源异构数据中的浮动车GPS数据与卡口视频数据;S2、根据主干道位置筛选卡口数据;S3、提取出卡口数据集中的车牌号码,作为数据融合的特征属性;S4、提取卡口数据集中的该车辆进入路段的时间与离开路段的时间,获取浮动车在主干道内的行程时间;S5、打开通过S4中所述路段的浮动车GPS文件,并以这行程时间为数据分割标准,分割GPS浮动车文件,得到所有浮动车在此路段上行驶的时间段内的数据。本发明有助于精准估计城市主干道交通状态,进而剖析交通拥堵传播规律,支撑城市拥堵治理决策分析。
Urban trunk road multi-vehicle trajectory reconstruction method based on multi-source data
基于多源数据的城市主干道多车轨迹重构方法
2022-11-11
Patent
Electronic Resource
Chinese
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