Urban Traffic Jam Time Prediction Mode

Zhixu Gao, Guyue Tian, Fengsi Yu

Abstract

Urban transportation is the core of urban social activities and economic activities. However, due to the increase of population and motor vehicles, traffic congestion is caused by many factors. This paper established a traffic congestion duration model based on survival analysis. The purpose is to use the model to obtain the relationship between congestion index and congestion time, and improve the accuracy of prediction. Using the nonparametric method to calculate, after defining the Shanghai Expressway survival function and risk function, combined with the compiled data, calculate whether it is the impact of the working day on traffic congestion, and the difference between the early, middle and late peaks for traffic congestion. The result can be obtained: Traffic congestion on workdays is higher than on weekends, and traffic congestion is longer than weekends.

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Paper Citation


in Harvard Style

Gao Z., Tian G. and Yu F. (2020). Urban Traffic Jam Time Prediction Mode.In Proceedings of the International Symposium on Frontiers of Intelligent Transport System - Volume 1: FITS, ISBN 978-989-758-465-7, pages 38-41. DOI: 10.5220/0010019600380041


in Bibtex Style

@conference{fits20,
author={Zhixu Gao and Guyue Tian and Fengsi Yu},
title={Urban Traffic Jam Time Prediction Mode},
booktitle={Proceedings of the International Symposium on Frontiers of Intelligent Transport System - Volume 1: FITS,},
year={2020},
pages={38-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010019600380041},
isbn={978-989-758-465-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the International Symposium on Frontiers of Intelligent Transport System - Volume 1: FITS,
TI - Urban Traffic Jam Time Prediction Mode
SN - 978-989-758-465-7
AU - Gao Z.
AU - Tian G.
AU - Yu F.
PY - 2020
SP - 38
EP - 41
DO - 10.5220/0010019600380041