Bayesian predictive travel time methodology for advanced traveller information system

被引:8
|
作者
Khan, Ata M. [1 ]
机构
[1] Carleton Univ, Ottawa, ON K1S5B6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
advanced traveller information system; predictive travel time; data fusion; Bayesian; model; MODELS;
D O I
10.1002/atr.147
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Travellers can benefit from the availability of point-to-point driving time estimates on a real time basis for making travel decisions such as route choice at strategic locations (e.g. junctions of major routes). This paper reports a predictive travel time methodology that features a Bayesian approach to fusing and updating information for use in advanced traveller information system. The methodology addresses the issue that data captured in real time on travel conditions becomes obsolete and has archival value only unless it is used as an input to a predictive travel time method for updating the information. The need for fusing real time data with other factors that influence travel time is defined and the concept of predictive travel time is discussed. The methodological framework and its components are advanced and an example application is provided for illustrating the fusion of data captured by infrastructure-based and mobile technology with model-based predictions in order to produce expected travel times. Copyright (c) 2010 John Wiley & Sons, Ltd.
引用
收藏
页码:67 / 79
页数:13
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