基于GPS轨迹数据的拥堵路段预测

基于真实的GPS轨迹数据,对城市拥堵路段进行预测.在此过程中,摒弃传统的基于交通流预测和拥堵识别的方法,提出一种新的基于拥堵向量和拥堵转移矩阵的拥堵路段预测方法.该方法同时考虑路段拥堵的时间周期性和时空相关性,通过对出租车GPS轨迹数据进行挖掘和训练,建立拥堵向量和拥堵转移矩阵,实现对拥堵路段的预测.真实数据集上的实验验证了所提的拥堵路段预测方法的有效性.

The Congestion Road Segment Prediction Based on GPS Trajectory Data

Congestion road segments over real GPS trajectory data was predicted. The traditional methods were ostracized based on traffic flow prediction and congestion identification， and a novel method was proposed based on the congestion vector and the congestion transition matrix. The congestion vector and the congestion transition matrix were established by mining and training taxi GPS trajectory data， resulting in the implementation of the prediction of traffic congestion. In the course of prediction， time periodicity and spatial-temporal correlation of road segment congestion were both considered. The experiments on real data show the effectiveness of the congestion road segment prediction method proposed.