Bus Dwell Time Prediction Based on KNN

被引：14

作者：

Xin, Jianxia ^{[1
,2
]}

Chen, Shuyan ^{[1
,2
]}

机构：

[1] Southeast Univ, Jiangsu Key Lab Urban ITS, Si Pai Lou 2, Nanjing 210096, Jiangsu, Peoples R China

[2] Jiangsu Prov Collaborat Innovat Ctr Morden Urban, Si Pai Lou 2, Nanjing 210096, Jiangsu, Peoples R China

来源：

GREEN INTELLIGENT TRANSPORTATION SYSTEM AND SAFETY | 2016年 / 138卷

关键词：

bus dwell time; prediction; k-nearest neighbor algorithm;

D O I：

10.1016/j.proeng.2016.01.260

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The objective of this research is to develop a dynamic model to predict bus dwell time at downstream stops. The research also intends to test the proposed model using real-world data. This model is based on k-Nearest Neighbour (KNN) algorithm using history and current data collected by GPS (Global Positon System) fixed on buses. In the research, the data of buses of No.B1 line of Changzhou in China is used. In the test with real-world data, the proposed bus dwell time prediction model performed effectively both on accuracy and calculating speed. (C) 2016 The Authors. Published by Elsevier Ltd.

引用

页码：283 / 288

页数：6

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