loading
Documents

Research.Publish.Connect.

Paper

Authors: Mohammed Elhenawy ; Hesham Rakha and Hao Chen

Affiliation: Virginia Tech Transportation Institute, United States

ISBN: 978-989-758-185-4

Keyword(s): Transportation Planning and Traffic Operation, Real-time Automatic Congestion Identification, Mixture of Linear Regression, ITS.

Abstract: Real-time automatic congestion identification is one of the important routines of intelligent transportation systems (ITS). Previous efforts usually use traffic state measurements (speed, flow, occupancy) to develop congestion identification algorithms. However, the impacts of weather conditions to identify congestion have not been investigated in the existing studies. In this paper, we proposed an algorithm that uses the speed probe data and the corresponding weather and visibility to build a transferable model. This model can be used on any road stretch. Our algorithm assumes traffic states can be classified into three regimes: congestion, speed at capacity and free-flow. Moreover, the speed distribution follows a mixture of three components whose means are functions in weather and visibility. The mean of each component is defined using a linear regression using different weather conditions and visibility levels as predictors. We used three data sets from VA, CA and TX to estimate t he model parameters. The fitted model is used to calculate the speed cut-off between congestion and speed at capacity which minimize either the Bayesian classification error or the false positive (congestion) rate. The test results demonstrate the proposed method produces promising congestion identification output by considering weather condition and visibility. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.225.17.239

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Elhenawy M., Rakha H. and Chen H. (2016). A Unified Real-time Automatic Congestion Identification Model Considering Weather and Roadway Visibility Conditions.In Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-185-4, pages 39-48. DOI: 10.5220/0005791400390048

@conference{vehits16,
author={Mohammed Elhenawy and Hesham Rakha and Hao Chen},
title={A Unified Real-time Automatic Congestion Identification Model Considering Weather and Roadway Visibility Conditions},
booktitle={Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2016},
pages={39-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005791400390048},
isbn={978-989-758-185-4},
}

TY - CONF

JO - Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - A Unified Real-time Automatic Congestion Identification Model Considering Weather and Roadway Visibility Conditions
SN - 978-989-758-185-4
AU - Elhenawy M.
AU - Rakha H.
AU - Chen H.
PY - 2016
SP - 39
EP - 48
DO - 10.5220/0005791400390048

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.