Crash prediction for freeway work zones in real time: A comparison between Convolutional Neural Network and Binary Logistic Regression model

Crash prediction for freeway work zones in real time: A comparison between Convolutional Neural Network and Binary Logistic Regression model

Safety of drivers in freeway work zones has been a problem. Real-time crash prediction helps prevent crashes before they happen. This paper looks at real-time crash prediction in freeway work zones by using machine learning approaches. Both the Convolutional Neural Network and the Binary Logistic Re...

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Bibliographic Details
Main Authors: Junhua Wang, Hao Song, Ting Fu, Molly Behan, Lei Jie, Yingxian He, Qiangqiang Shangguan
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2022-09-01
Series:International Journal of Transportation Science and Technology
Subjects:
Work zone
Freeway safety
Real-time crash prediction
Machine learning
Convolutional Neural Network
Binary Logistic Regression
Online Access:http://www.sciencedirect.com/science/article/pii/S2046043021000514

Internet

http://www.sciencedirect.com/science/article/pii/S2046043021000514

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