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Statistical and machine-learning methods for clearance time prediction of road incidents: A methodology review
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 …
incident impacting range and provide route guiding strategy according to the predicted …
[HTML][HTML] A systematic review of traffic incident detection algorithms
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 …
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
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 …
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
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 …
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
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 …
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
Recent technology developments and the numerous availabilities of mobile users, devices
and Internet technologies together with the growing focus on reducing traffic congestion and …
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 …
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 …
with open roadways, road closures caused by traffic accidents in the tunnel have greater …
Review of driving-behaviour simulation: VISSIM and artificial intelligence approach
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 …
safety and the potential for increased risk of accidents, injuries, and fatalities. Approximately …
Analysis of time-to-lane-change-initiation using realistic driving data
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 …
changes can provide insight into how long drivers wait after activating their turn signal …