A deep learning approach for real-time crash prediction using vehicle-by-vehicle data-Reference-Cited by-同舟云学术

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A deep learning approach for real-time crash prediction using vehicle-by-vehicle data

Published:2021-11 Issue: Volume:162 Page:106409
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Basso Franco,Pezoa Raúl,Varas Mauricio,Villalobos Matías

Funder

Comisión Nacional de Investigación Científica y Tecnológica

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference60 articles.

1. Crash risk assessment using intelligent transportation systems data and real-time intervention strategies to improve safety on freeways;Abdel-Aty;J. Intell. Transp. Syst.,2007

2. Predicting freeway crashes from loop detector data by matched case-control logistic regression;Abdel-Aty;Transp. Res. Rec.,2004

3. Guide to convolutional neural networks;Aghdam;New York, NY: Springer,2017

4. Bayesian updating approach for real-time safety evaluation with automatic vehicle identification data;Ahmed;Transp. Res. Rec.,2012

5. Assessment of the importance of gully erosion effective factors using boruta algorithm and its spatial modeling and mapping using three machine learning algorithms;Amiri;Geoderma,2019

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