车辆轨迹的动态分组

G. Reyes, L. Lanzarini, César Estrebou, A. F. Bariviera
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引用次数: 1

摘要

近年来,大城市的车辆交通量有所增加,造成了流动性问题;因此,对车辆流量数据的分析成为一个相关的研究课题。智能交通系统通过收集GPS轨迹来监测和控制车辆的运动,从而实时提供车辆的地理位置。因此,使用聚类技术处理信息以识别车辆流模式。这项工作提出了一种方法,能够分析给定区域内的车辆流量,确定速度范围,并保持交互式地图的更新,以方便识别可能的交通堵塞区域。在瓜亚基尔-厄瓜多尔、罗马-意大利和北京-中国三个城市的数据集上获得的结果令人满意,并且清楚地代表了车辆的运动速度,并实时自动识别最具代表性的范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic grouping of vehicle trajectories
Vehicular traffic volume in large cities has increased in recent years, causing mobility problems; therefore,the analysis of vehicle flow data becomes a relevant research topic. Intelligent Transportation Systems monitor and control vehicular movements by collecting GPS trajectories, which provides the geographic location of vehicles in real time. Thus information is processed using clustering techniques to identify vehicular flow patterns. This work presents a methodologycapable of analyzing the vehicular flow in a given area, identifying speed ranges and keeping an interactivemap updated that facilitates the identification of possible traffic jam areas. The results obtained on threedata sets from the cities of Guayaquil-Ecuador, RomeItaly and Beijing-China are satisfactory and clearlyrepresent the speed of movement of the vehicles, automatically identifying the most representative ranges inreal time.
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