Bus arrival time prediction based on particle filter

被引：0

作者：

Ren, Yuan ^{[1
]}

Lv, Yong-Bo ^{[1
]}

Ma, Ji-Hui ^{[1
]}

Chen, Xin-Jie ^{[1
]}

Yu, Ming-Jie ^{[1
]}

机构：

[1] School of Traffic and Transportation, Beijing Jiaotong University, Beijing,100044, China

来源：

Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2016年 / 16卷 / 06期

关键词：

Forecasting - Traffic congestion - Bus transportation - Tracking (position) - Bandpass filters - Kalman filters - Monte Carlo methods;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Providing accurate bus arrival time (BAT) can help to improve the service quality of a transit system, enhance bus attractiveness and ease traffic jams. BAT is greatly influenced by the complex road conditions, particle filter algorithm can be well applied to this kind of nonlinear and non-Gaussian systems. Therefore, a BAT based on particle filter algorithm prediction model (BAT-PF) is proposed tentatively. Then, based on the location data, a case study of the inner line 300 of Beijing is conducted. Bus arrival time during the morning peak hours and off-peak hours are forecasted by both the BAT-PF and the Kalman filter (KF). The results show that the BAT-PF is more applicable and stable to predict bus arrival time and has a higher accuracy. Copyright © 2016 by Science Press.

引用

页码：142 / 146

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