Bus arrival time prediction at bus stop with multiple routes

被引:268
|
作者
Yu, Bin [1 ,2 ]
Lam, William H. K. [1 ]
Tam, Mei Lam [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Civil & Struct Engn, Kowloon, Hong Kong, Peoples R China
[2] Dalian Maritime Univ, Transportat Management Coll, Dalian, Peoples R China
基金
中国博士后科学基金;
关键词
Bus arrival time prediction; Multiple bus routes; Support vector machine; Artificial neural network; k nearest neighbours algorithm; NEURAL-NETWORKS; REAL-TIME; MODEL;
D O I
10.1016/j.trc.2011.01.003
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Provision of accurate bus arrival information is vital to passengers for reducing their anxieties and waiting times at bus stop. This paper proposes models to predict bus arrival times at the same bus stop but with different routes. In the proposed models, bus running times of multiple routes are used for predicting the bus arrival time of each of these bus routes. Several methods, which include support vector machine (SVM), artificial neural network (ANN), k nearest neighbours algorithm (k-NN) and linear regression (LR), are adopted for the bus arrival time prediction. Observation surveys are conducted to collect bus running and arrival time data for validation of the proposed models. The results show that the proposed models are more accurate than the models based on the bus running times of single route. Moreover, it is found that the SVM model performs the best among the four proposed models for predicting the bus arrival times at bus stop with multiple routes. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1157 / 1170
页数:14
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