基于GPS数据的高速公路行程时间估计与可靠性分析

Expressway travel time estimation based on GPS data and reliability analysis

准确地进行高速公路行程时间估计与可靠性分析对交通规划与缓解交通拥堵具有重要意义。针对目前行程时间估计准确性不高、可靠性分析不够全面的问题,提出基于BP神经网络的高速公路行程时间估计模型,并利用该模型计算的行程时间分析高速公路上车辆行驶的行程时间可靠性。以广州机场高速公路GPS浮动车数据为例进行实例验证,结果表明,与速度-时间积分法和位置-时间内插法相比,本文提出的模型提高了行程时间估计的准确度,同时能多方面地分析车辆行程时间的可靠性。

Accurate highway travel time estimation and reliability analysis is of great significance for traffic planning and traffic congestion alleviation.Aiming at the current problems of low accuracy of travel time estimation and insufficiently comprehensive reliability analysis,this paper proposes a highway travel time estimation model based on BP neural network,and uses the travel time calculated by this model to analyze the travel time reliability of vehicles traveling on highways.Taking the GPS floating car data of Guangzhou Airport Expressway as an example for verification,the model proposed in this paper improves the accuracy of travel time estimation compared to the speed time integration method and the position time interpolation method,and can analyze the reliability of vehicle travel time in multiple aspects.