Short term traffic flow prediction for a non urban highway using Artificial Neural Network

被引：185
|
作者：
Kumar, Kranti [1 ]
Parida, M. [2 ]
Katiyar, V. K. [3 ]
机构：
[1] Vellore Inst Technol Univ, Sch Adv Sci, Velloree 632014, Tamil Nadu, India
[2] Indian Inst Technol, Dept Civil Engn, Roorkee 247667, Uttar Pradesh, India
[3] Indian Inst Technol, Dept Math, Roorkee 247667, Uttar Pradesh, India
来源：
2ND CONFERENCE OF TRANSPORTATION RESEARCH GROUP OF INDIA (2ND CTRG) | 2013年 / 104卷
关键词：
traffic flow; speed; heterogeneous traffic; multi-layer perceptron; sensitivity; MODEL;
D O I：
10.1016/j.sbspro.2013.11.170
中图分类号：
U [交通运输];
学科分类号：
08 ; 0823 ;
摘要：
This study applies Artificial Neural Network (ANN) for short term prediction of traffic flow using past traffic data. The model incorporates traffic volume, speed, density, time and day of week as input variables. Speed of each category of vehicles was considered separately as input variables in contrast to previous studies reported in literature which consider average speed of combined traffic flow. Results show that Artificial Neural Network has consistent performance even if time interval for traffic flow prediction was increased from 5 minutes to 15 minutes and produced good results even though speeds of each category of vehicles were considered separately as input variables. (C) 2013 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：755 / 764
页数：10
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