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Car Travel Time Estimation near a Bus Stop with Non-motorized Vehicles
Author(s) -
Xiaobao Yang,
Mei Huan,
Hongwei Guo,
Gao Feng Liang
Publication year - 2011
Publication title -
international journal of computational intelligence systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.385
H-Index - 41
eISSN - 1875-6891
pISSN - 1875-6883
DOI - 10.1080/18756891.2011.9727885
Subject(s) - travel time , transport engineering , computer science , traffic flow (computer networking) , volume (thermodynamics) , hazard , duration (music) , traffic volume , real time data , real time computing , engineering , computer security , art , chemistry , physics , literature , organic chemistry , quantum mechanics , world wide web
Real time system for vehicle travel time and traffic flow is an essential part of Intelligent Transportation Systems. In many Chinese cities, the interactions among buses, bicycles and cars bring difficulty to travel time prediction and traffic safety management. The aim of this paper is to develop a new model to estimate car travel time near bus stops in developing countries by data mining techniques and survival analysis methods. The travel time data under mixed traffic conditions are collected by video camera. Four influential factors including car volume, nonmotorized volume, bus departure volume and free ratio of bus stop are chosen by using data mining techniques. A proportional hazard-based duration model is proposed to analyze the factors related to car travel time. The results indicate that mixed traffic flow impacts the car travel time significantly. In addition, various factors can modify the travel time distribution in different degrees and the model can be used to estimate the travel time under assumed conditions. It is hoped to help improve the planning and designing of proper facilities with mixed traffic flow. © 2011 Copyright Taylor and Francis Group, LLC.

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