The invention provides a large-curvature road electric bicycle converse motion behavior identification method based on trajectory data. The method comprises the following steps: 1) trajectory data acquisition and cleaning: collecting trajectory data and cleaning missing and drifting data; 2) map matching: accurately matching the trajectory data to an urban road network; 3) retrograde motion behavior identification: calibrating retrograde motion points on a one-way road and a two-way road by using a geometry and road topological relation principle under the condition of considering a large-curvature road, and further identifying a retrograde motion behavior; and 4) road network risk level division: based on the shared electric bicycle track data, counting the occurrence frequency of the retrograde behavior of each road section in one day, performing risk level division on the road sections according to the occurrence frequency, and displaying the road network risk level on a GIS map platform. According to the method, the retrograde behavior under the road with the great curvature is recognized through the topology relation between geometry and the road, and compared with a previous method, the robustness and accuracy of retrograde detection are remarkably improved.
本发明提出一种基于轨迹数据的大曲率道路电动自行车逆行行为识别方法,包括以下步骤:1)轨迹数据获取与清洗:收集轨迹数据并清洗缺失和漂移的数据;2)地图匹配:将轨迹数据精确匹配至城市道路网络;3)逆行行为识别:考虑大曲率道路条件下,利用几何学与道路拓扑关系原理,标定单向路与双向路上的逆行点,进而识别逆行行为;4)路网风险水平划分:基于共享电动自行车轨迹数据,统计一天内各路段逆行行为发生频次,并据此对路段进行风险等级划分,在GIS地图平台上展示路网风险水平。本发明通过几何学与道路拓扑关系识别大大曲率道路下的逆行行为,与前人方法相比显著提高了逆行检测的鲁棒性和准确性。
Large-curvature road electric bicycle retrograde motion behavior identification method based on trajectory data
基于轨迹数据的大曲率道路电动自行车逆行行为识别方法
2025-04-08
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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