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Development and External Validation of a Novel Prediction Model for the TraumaTriage App

Gulickx M, Lokerman RD, Sluijs Rvd, Tuinema RM, Vliet Rv, Hietbrink F, Groenwold RHH, Heijl Mv.   +7 more
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Real-Time Framework to Predict Crash Likelihood and Cluster Crash Severity

Transportation Research Record: Journal of the Transportation Research Board, 2023
This study proposes a three-stage framework for real-time crash likelihood and severity prediction. Firstly, a real-time crash likelihood prediction model was developed. Secondly, a real-time crash severity clustering model was proposed to cluster the crashes into different severity levels. Thirdly, a severity clustering validation model was developed
Md Rakibul Islam, Mohamed Abdel-Aty, Zubayer Islam, Amr Abdelraouf   +3 more
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Real-time prediction of visibility related crashes

Transportation Research Part C: Emerging Technologies, 2012
More researchers started using real-time traffic surveillance data, collected from loop/radar detectors (LDs), for proactive crash risk assessment. However, there is a lack of prior studies that investigated the link between real-time traffic data and crash risk of reduced visibility related (VR) crashes.
Abdel-Aty, Mohamed A., Hassan, Hany M., Ahmed, Mohamed, Al-Ghamdi, Ali S.   +3 more
openaire   +2 more sources

Real-time crash risk prediction on arterials based on LSTM-CNN

Accident Analysis & Prevention, 2020
Real-time crash risk prediction is expected to play a crucial role in preventing traffic accidents. However, most existing studies only focus on freeways rather than urban arterials. This paper proposes a real-time crash risk prediction model on arterials using a long short-term memory convolutional neural network (LSTM-CNN).
Pei, Li, Mohamed, Abdel-Aty, Jinghui, Yuan   +2 more
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Real-time crash prediction for expressway weaving segments

Transportation Research Part C: Emerging Technologies, 2015
Weaving segments are potential recurrent bottlenecks which affect the efficiency and safety of expressways during peak hours. Meanwhile, they are one of the most complicated segments, since on- and off-ramp traffic merges, diverges and weaves in the limited space.
Wang, Ling, Abdel-Aty, Mohamed, Shi, Qi, Park, Juneyoung   +3 more
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Examining imbalanced classification algorithms in predicting real-time traffic crash risk

Accident Analysis & Prevention, 2020
The Active Traffic Management (ATM) system has been widely used in the United States and the European countries to improve the traffic safety of urban expressways. The accurate real-time crash risk prediction is fundamental to the system running well.
Yichuan, Peng, Chongyi, Li, Ke, Wang, Zhen, Gao, Rongjie, Yu   +4 more
openaire   +2 more sources

Transfer learning for spatio-temporal transferability of real-time crash prediction models

Accident Analysis & Prevention, 2022
Real-time crash prediction is a heavily studied area given their potential applications in proactive traffic safety management in which a plethora of statistical and machine learning (ML) models have been developed to predict traffic crashes in real-time.
Cheuk Ki, Man, Mohammed, Quddus, Athanasios, Theofilatos   +2 more
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Evaluation of the predictability of real-time crash risk models

Accident Analysis & Prevention, 2016
The primary objective of the present study was to investigate the predictability of crash risk models that were developed using high-resolution real-time traffic data. More specifically the present study sought answers to the following questions: (a) how to evaluate the predictability of a real-time crash risk model; and (b) how to improve the ...
Chengcheng Xu, Pan Liu, Wei Wang
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Investigating the predictability of crashes on different freeway segments using the real-time crash risk models

Accident Analysis & Prevention, 2021
Improvement of the prediction efficiency of crash risks has attracted the attention of numerous studies. Nevertheless, one of the most important factors, crash precursors, were neglected. This study mainly focuses on identifying optimal crash precursors for different freeway section types, as well as providing a threshold selection method for real-time
Qikang, Zheng, Chengcheng, Xu, Pan, Liu, Yuxuan, Wang   +3 more
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