Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements

M Hossain, M Abdel-Aty, MA Quddus… - Accident Analysis & …, 2019 - Elsevier
Proactive traffic safety management systems can monitor traffic conditions in real-time,
identify the formation of unsafe traffic dynamics, and implement suitable interventions to …

Urban anomaly analytics: Description, detection, and prediction

M Zhang, T Li, Y Yu, Y Li, P Hui… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Urban anomalies may result in loss of life or property if not handled properly. Automatically
alerting anomalies in their early stage or even predicting anomalies before happening is of …

A high-resolution trajectory data driven method for real-time evaluation of traffic safety

Y Hu, Y Li, H Huang, J Lee, C Yuan, G Zou - Accident Analysis & Prevention, 2022 - Elsevier
Real-time safety evaluation is essential for developing proactive safety management
strategy and improving the overall traffic safety. This paper proposes a method for real-time …

A vision-based system for traffic anomaly detection using deep learning and decision trees

A Aboah - Proceedings of the IEEE/CVF Conference on …, 2021 - openaccess.thecvf.com
Any intelligent traffic monitoring system must be able to detect anomalies such as traffic
accidents in real-time. In this paper, we propose a Decision-Tree enabled approach …

Highway crash detection and risk estimation using deep learning

T Huang, S Wang, A Sharma - Accident Analysis & Prevention, 2020 - Elsevier
Crash Detection is essential in providing timely information to traffic management centers
and the public to reduce its adverse effects. Prediction of crash risk is vital for avoiding …

A novel variable selection method based on frequent pattern tree for real-time traffic accident risk prediction

L Lin, Q Wang, AW Sadek - Transportation Research Part C: Emerging …, 2015 - Elsevier
With the availability of large volumes of real-time traffic flow data along with traffic accident
information, there is a renewed interest in the development of models for the real-time …

Predicting crash likelihood and severity on freeways with real-time loop detector data

C Xu, AP Tarko, W Wang, P Liu - Accident Analysis & Prevention, 2013 - Elsevier
Real-time crash risk prediction using traffic data collected from loop detector stations is
useful in dynamic safety management systems aimed at improving traffic safety through …

A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways

M Hossain, Y Muromachi - Accident Analysis & Prevention, 2012 - Elsevier
The concept of measuring the crash risk for a very short time window in near future is
gaining more practicality due to the recent advancements in the fields of information systems …

Crash risk analysis during fog conditions using real-time traffic data

Y Wu, M Abdel-Aty, J Lee - Accident Analysis & Prevention, 2018 - Elsevier
This research investigates the changes of traffic characteristics and crash risks during fog
conditions. Using real-time traffic flow and weather data at two regions in Florida, the traffic …

Surrogate measures of safety

AP Tarko - Safe mobility: challenges, methodology and solutions, 2018 - emerald.com
Purpose–This chapter overviews surrogate measures of safety to help better understand the
related challenges and opportunities. The chapter is meant to serve as a primer for …