Prediction of Truck-Involved Crash Severity on a Rural Mountainous Freeway Using Transfer Learning with ResNet-50 Deep Neural Network-Reference-Cited by-同舟云学术

Prediction of Truck-Involved Crash Severity on a Rural Mountainous Freeway Using Transfer Learning with ResNet-50 Deep Neural Network

Published:2024-02 Issue:2 Volume:150 Page:
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Khan Md Nasim¹^ORCID,Das Anik²^ORCID,Ahmed Mohamed M.³^ORCID

Affiliation:

1. Postdoctoral Scholar, Civil Engineering Program Ingram School of Engineering, Texas State Univ., RFM 5224, 601 University Dr., San Marcos, TX 78666. ORCID: .

2. Postdoctoral Research Associate, Research and Implementation Program, Texas A&M Transportation Institute, 1111 RELLIS Pkwy., Room 3448, Bryan, TX 77807-3135 (corresponding author). ORCID: .

3. Professor and Director, Dept. of Civil and Architectural Engineering and Construction Management, Transportation Center Baldwin Hall, CEAS - Civil Eng–0071, Univ. of Cincinnati, 2850 Campus Way, Cincinnati, OH 45221-0071. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JTEPBS.TEENG-7304

Reference63 articles.

1. Development of artificial neural network models to predict driver injury severity in traffic accidents at signalized intersections;Abdelwahab H. T.;Transp. Res. Rec.,2001

2. Gully erosion susceptibility assessment in the Kondoran watershed using machine learning algorithms and the Boruta feature selection;Ahmadpour H.;Sustainability,2021

3. Effects of truck traffic on crash injury severity on rural highways in Wyoming using Bayesian binary logit models;Ahmed M. M.;Accid. Anal. Prev.,2018

4. Ahmed, M. M., S. Gaweesh, M. J. Hossain, S. Sharmin, and T. Peel. 2017. Calibrating crash modification factors for Wyoming-specific conditions: Application of the highway safety manual - Part D. Cheyenne, WY: Wyoming DOT.

5. Severity prediction of traffic accident using an artificial neural network;Alkheder S.;J. Forecasting,2017

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing road safety with machine learning: Current advances and future directions in accident prediction using non-visual data;Engineering Applications of Artificial Intelligence;2024-11

2. Enhanced analysis of tabular data through Multi-representation DeepInsight;Scientific Reports;2024-06-04

3. Detection of Vehicle Crashes on Roads using Deep Learning;2024 2nd International Conference on Advancement in Computation & Computer Technologies (InCACCT);2024-05-02

4. Predicting pedestrian-involved crash severity using inception-v3 deep learning model;Accident Analysis & Prevention;2024-03