基于前车与经验数据的车辆到站时间预测模型

摘要

Operation of public transport vehicles experience data reflects the general laws of bus arrival time, the front bus data reflects the real time line of vehicle arrival time.A prediction model of bus vehicle arrival time is presented, based on the front bus data and empirical data.In the model, the travel time between sites and site retention time distinction is classified into peak and ravine. The delay time is predicted by taking the effects of different direction light difference between waiting time and a zebra crossing into consideration.The model is verified by Hangzhou 104 bus line data. The results show that the prediction model has higher predictive accuracy and can accurately predict bus arrival time.%公交车辆运行经验数据体现了到站时间的一般性规律，前车数据反映了到站时间的实时性。提出一种基于前车与经验数据的公交车辆到站时间预测模型。在该模型中对站点间路段行驶时间及站点停留时间区分了高峰期和非高峰期，站点间的延时时间考虑了不同方向红灯等待时间的区别以及斑马线的影响。用杭州公交104路公交车的数据对预测模型进行了验证，结果表明，该预测模型具有较高的预测精度，能够较为准确地预测公交车辆到站时间。