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Authors: Mohammed Elhenawy ; Hesham Rakha and Hao Chen

Affiliation: Virginia Tech Transportation Institute, United States

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 the 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)

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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 - VEHITS; ISBN 978-989-758-185-4; ISSN 2184-495X, SciTePress, 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 - VEHITS},
year={2016},
pages={39-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005791400390048},
isbn={978-989-758-185-4},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - A Unified Real-time Automatic Congestion Identification Model Considering Weather and Roadway Visibility Conditions
SN - 978-989-758-185-4
IS - 2184-495X
AU - Elhenawy, M.
AU - Rakha, H.
AU - Chen, H.
PY - 2016
SP - 39
EP - 48
DO - 10.5220/0005791400390048
PB - SciTePress

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