Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data
Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data
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DOI：
10.1080/15230406.2015.1130649
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发表时间：
2016-01
影响因子：
2.5
通讯作者：
Luliang Tang;Zihan Kan;Xia Zhang;Xue Yang;Fangzhen Huang;Qingquan Li
中科院分区：
文献类型：
--
作者：
Luliang Tang;Zihan Kan;Xia Zhang;Xue Yang;Fangzhen Huang;Qingquan Li
十字路口是不同交通流交汇和转向的关键部位，是城市交通的“瓶颈”和“塞点”。交叉口通行时间是公共路线规划、交通管理和工程优化的重要参数。提出了一种基于低频时空全球定位系统（GPS）轨迹数据的交叉口行驶时间估计方法。该方法首先对车辆通过交叉口的不同出行方式进行分析，然后动态合理地确定交叉口的通行范围，利用模糊拟合的方法得到不同出行方式下交叉口的交通流速度和延误。最后，根据不同出行方式下的交通流速度、延迟和交叉口距离估算出交叉口的平均出行时间。以武汉市道路网数据和出租车GPS轨迹数据为例进行了实验验证，结果表明该方法可以提高城市交叉口出行时间估计的精度。
ABSTRACT Intersections are the critical parts where different traffic flows converge and change directions, forming “bottlenecks” and “clog points” in urban traffic. Intersection travel time is an important parameter for public route planning, traffic management, and engineering optimization. Based on low-frequency spatial-temporal Global Positioning System (GPS) trace data, this article presents a novel method for estimating intersection travel time. The proposed method first analyzes the different travel patterns of vehicles through an intersection, then determines the range of an intersection dynamically and reasonably, and obtains traffic flow speed and delay at the intersection under different travel patterns using a fuzzy fitting approach. Finally, the average intersection travel time is estimated from traffic flow speed and delay and intersection range in different travel patterns. Wuhan road network data and GPS trace data from taxicabs were tested in the experiments and the results show that the proposed method can improve the accuracy of travel time estimation at city intersections.