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根据公交浮动车辆实时GPS数据,考虑不同时段的路段平均速度、公交车站、信号灯等多因素的影响,建立了一种新的公交车辆到站时间预测模型。通过估计到达下游最临近站点的时间和判断道路上GPS数据的有效性等方法,改善了预测模型的精度,并应用重庆公交车辆数据对模型进行验证。计算结果表明:该模型能够实时预测公交浮动车辆到达下游站点的时间,预测精度优于现有方法,在高峰时段预测误差小于9%,在非高峰时段预测误差约为6%,并对各种道路交通条件具有较好的适应性。
According to the real-time GPS data of floating buses, a new bus arrival time prediction model is established considering the influence of multi-factors such as the average speed of road sections, bus stops and signal lights in different periods. By estimating the time to reach the nearest downstream station and judging the validity of the GPS data on the road, the accuracy of the prediction model is improved and the model is verified with Chongqing bus data. The results show that the model can predict the time when the floating car arrives at the downstream site in real time. The prediction accuracy is better than the existing method. The prediction error is less than 9% in peak period and about 6% in non-peak period. Road traffic conditions have good adaptability.