Detecting phone‐related pedestrian distracted behaviours via a two‐branch convolutional neural network-Reference-Cited by-同舟云学术

Detecting phone‐related pedestrian distracted behaviours via a two‐branch convolutional neural network

Published:2020-12-08 Issue:1 Volume:15 Page:147-158
ISSN:1751-956X
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET intell. transp. syst

Author:

Saenz Humberto¹²,Sun Huiming¹,Wu Lingtao³,Zhou Xuesong⁴,Yu Hongkai¹

Affiliation:

1. Department of Electrical Engineering and Computer Science Cleveland State University Cleveland Ohio USA

2. Department of Computer Science University of Texas‐Rio Grande Valley Edinburg Texas USA

3. Texas A&M Transportation Institute College Station Texas USA

4. School of Sustainable Engineering and the Built Environment Arizona State University Tempe Arizona USA

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/itr2.12012

Reference42 articles.

1. 2017 Fatal motor vehicle crashes: overview National Highway Traffic Safety Administration US Department of Transportation(2017).https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812603. Accessed 25 July 2020.

2. Texas motor vehicle crash statistics 2019 Texas Department of Transportation(2019).https://www.txdot.gov/government/enforcement/annual-summary.html. Accessed 25 July 2020

3. Traffic safety facts 2018 National Highway Traffic Safety Administration US Department of Transportation(2018).https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812850. Accessed 25 July 2020

4. Pedestrians and their phones - detecting phone-based activities of pedestrians for autonomous vehicles

5. When Vehicles See Pedestrians With Phones: A Multicue Framework for Recognizing Phone-Based Activities of Pedestrians

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