Statistical and machine-learning methods for clearance time prediction of road incidents: A methodology review

J Tang, L Zheng, C Han, W Yin, Y Zhang, Y Zou… - Analytic methods in …, 2020 - Elsevier
Accurate clearance time prediction for road incident would be helpful to evaluate the
incident impacting range and provide route guiding strategy according to the predicted …

[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 …

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 …

Real-time traffic accidents post-impact prediction: Based on crowdsourcing data

Y Lin, R Li - Accident Analysis & Prevention, 2020 - Elsevier
Traffic accident management is a critical issue for advanced intelligent traffic management.
The increasingly abundant crowdsourcing data and floating car data provide new support for …

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 …

Ridesharing and crowdsourcing for smart cities: technologies, paradigms and use cases

KP Seng, LM Ang, E Ngharamike, E Peter - IEEE Access, 2023 - ieeexplore.ieee.org
Recent technology developments and the numerous availabilities of mobile users, devices
and Internet technologies together with the growing focus on reducing traffic congestion and …

Traffic accident duration prediction using multi-mode data and ensemble deep learning

J Chen, W Tao, Z **g, P Wang, Y ** - Heliyon, 2024 - cell.com
Predicting the duration of traffic accidents is a critical component of traffic management and
emergency response on expressways. Traffic accident information is inherently multi-mode …

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 …

Review of driving-behaviour simulation: VISSIM and artificial intelligence approach

H Al-Msari, S Koting, AN Ahmed, A El-Shafie - Heliyon, 2024 - cell.com
Examining driving behaviour is crucial for traffic operations because of its influence on driver
safety and the potential for increased risk of accidents, injuries, and fatalities. Approximately …

Analysis of time-to-lane-change-initiation using realistic driving data

S Jokhio, P Olleja, J Bärgman, F Yan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Lane changing is a complex, yet extremely common driving manoeuvre. Studying lane
changes can provide insight into how long drivers wait after activating their turn signal …