【作者】 管珊珊； 张益农；

【Author】 GUAN Shan-shan;ZHANG Yi-nong;Beijing Key Laboratory of Information Service Engineering,Beijing Union University;College of Urban Rail Transit and Logistics,Beijing Union University;

【机构】 北京联合大学北京市信息服务工程重点实验室； 北京联合大学城市轨道交通与物流学院；

【摘要】 车速预测可为车辆的决策系统提供行驶数据,对智能车辆安全辅助驾驶及动力系统控制等研究有着重要意义。由于车速受多种因素的影响,具有显著的时变性与非线性,因此对预测有较高的要求。讨论了人工神经网络、贝叶斯网络、回归等机器学习算法及马尔科夫模型在车速预测中的应用及优缺点。最后分析了车速预测的进一步发展方向。更多还原

【Abstract】 Vehicle speed prediction can provide driving data for the decision-making system of the vehicle,which is of great significance to the research of intelligent vehicle safety-assisted driving and power system control.As the speed is affected by a variety of factors,with significant time-varying and non-linear,the forecast has a higher demand.The application of artificial neural network,Bayesian network,regression and other machine learning algorithms and Markov model in vehicle speed prediction were discussed in this paper.Finally,the further development direction of vehicle speed prediction was analyzed.更多还原