[HTML][HTML] A systematic review of traffic incident detection algorithms

O ElSahly, A Abdelfatah - Sustainability, 2022 - mdpi.com
Traffic incidents have negative impacts on traffic flow and the gross domestic product of most
countries. In addition, they may result in fatalities and injuries. Thus, efficient incident …

Dynamic prediction of traffic incident duration on urban expressways: A deep learning approach based on LSTM and MLP

W Zhu, J Wu, T Fu, J Wang, J Zhang… - Journal of intelligent …, 2021 - ieeexplore.ieee.org
Purpose-Efficient traffic incident management is needed to alleviate the negative impact of
traffic incidents. Accurate and reliable estimation of traffic incident duration is of great …

Incident duration prediction using a bi-level machine learning framework with outlier removal and intra–extra joint optimisation

A Grigorev, AS Mihaita, S Lee, F Chen - Transportation research part C …, 2022 - Elsevier
Predicting the duration of traffic incidents is a challenging task due to the stochastic nature of
events. The ability to accurately predict how long accidents will last can provide significant …

Prediction of the traffic incident duration using statistical and machine-learning methods: A systematic literature review

H Korkmaz, MA Erturk - Technological Forecasting and Social Change, 2024 - Elsevier
This paper aims to present a comprehensive review and analysis to demonstrate the main
papers, journals, authors, and trends significantly contributing to the scientific output in …

Application of the bayesian model averaging in analyzing freeway traffic incident clearance time for emergency management

Y Zou, B Lin, X Yang, L Wu… - Journal of advanced …, 2021 - Wiley Online Library
Identifying the influential factors in incident duration is important for traffic management
agency to mitigate the impact of traffic incidents on freeway operation. Previous studies have …

Using the scanners and drone for comparison of point cloud accuracy at traffic accident analysis

MN Perc, D Topolšek - Accident Analysis & Prevention, 2020 - Elsevier
The purpose of the paper is to describe, compare and analyse the instruments used, time
needed and accuracy of gathered data, sketches, 3D models and to enhance the extracted …

Prediction in traffic accident duration based on heterogeneous ensemble learning

Y Zhao, W Deng - Applied Artificial Intelligence, 2022 - Taylor & Francis
Based on millions of traffic accident data in the United States, we build an accident duration
prediction model based on heterogeneous ensemble learning to study the problem of …

Incorporating real-time weather conditions into analyzing clearance time of freeway accidents: A grouped random parameters hazard-based duration model with time …

Q Zeng, F Wang, T Chen, NN Sze - Analytic methods in accident research, 2023 - Elsevier
To minimize non-recurrent congestion, a better understanding of the factors that affect
accident clearance time is crucial, in order to optimize incident management strategies. A …

Exploration of road closure time characteristics of tunnel traffic accidents: A case study in Pennsylvania, USA

Q Luo, C Liu - Tunnelling and Underground Space Technology, 2023 - Elsevier
With the increase of roadway tunnels, tunnel traffic accidents are also increasing. Compared
with open roadways, road closures caused by traffic accidents in the tunnel have greater …

Modeling spatiotemporal heterogeneity in interval-censored traffic incident time to normal flow by leveraging crowdsourced data: A geographically and temporally …

Y Gu, H Zhang, LD Han, A Khattak - Accident Analysis & Prevention, 2024 - Elsevier
Non-recurrent traffic congestion arising from traffic incidents is unpredictable but should be
addressed efficiently to mitigate its adverse impacts on safety and travel time reliability …