Short-term traffic forecasting: Where we are and where we're going
Short-term traffic forecasting: Where we are and where we're going
复制标题
DOI：
10.1016/j.trc.2014.01.005
复制
发表时间：
2014-06-01
影响因子：
8.3
通讯作者：
Golias, John C.
中科院分区：
文献类型：
--
作者：
Vlahogianni, Eleni I.;Karlaftis, Matthew G.;Golias, John C.
自20世纪80年代初以来，短期交通预测已成为大多数智能交通系统（ITS）研究和应用的一个组成部分；大部分工作都投入到开发可用于模拟交通特征和产生预期交通状况的方法上。现有的文献是大量的，并且主要使用高速公路的单点数据，并使用单变量数学模型来预测交通量或旅行时间。技术的最新发展以及强大的计算机和数学模型的广泛使用，为研究人员提供了前所未有的机会来拓展视野，并在10个具有挑战性但相对较少研究的方向上指导工作。本文对这些存在的挑战进行了回顾，并对今后的工作提出了建议。(C) 2014 Elsevier Ltd.版权所有。
Since the early 1980s, short-term traffic forecasting has been an integral part of most Intelligent Transportation Systems (ITS) research and applications; most effort has gone into developing methodologies that can be used to model traffic characteristics and produce anticipated traffic conditions. Existing literature is voluminous, and has largely used single point data from motorways and has employed univariate mathematical models to predict traffic volumes or travel times. Recent developments in technology and the widespread use of powerful computers and mathematical models allow researchers an unprecedented opportunity to expand horizons and direct work in 10 challenging, yet relatively under researched, directions. It is these existing challenges that we review in this paper and offer suggestions for future work. (C) 2014 Elsevier Ltd. All rights reserved.