Predicting driver behaviour at intersections based on driver gaze and traffic light recognition-Reference-Cited by-同舟云学术

Predicting driver behaviour at intersections based on driver gaze and traffic light recognition

Published:2020-12 Issue:14 Volume:14 Page:2083-2091
ISSN:1751-956X
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET intell. transp. syst

Author:

Rahman Md. Junaedur¹,Beauchemin Steven S.¹,Bauer Michael A.¹

Affiliation:

1. Department of Computer ScienceThe University of Western OntarioLondonOntarioCanada

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2020.0087

Reference33 articles.

1. World Health Organization (WHO). Global Status Report on Road Safety 2018. December2018.https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/. accessed May 22 2020

2. Ministry of Transport 2015. Canadian Motor Vehicle Traffic Collision Statistics 2015. Collected in cooperation with the Canadian Council of Motor Transport Administrators

3. Zhu L. Young S. Day C.: ‘Exploring First‐Order Approximation of Energy Equivalence of Safety at Intersections: Preprint’ United States: 2019. Web. National Renewable Energy Laboratory (NREL):www.nrel.gov/publications

4. https://www.autoaccident.com/statistics‐on‐intersection‐accidents.htrnl. accessed February 1 2020

5. John V. Yoneda K. Qi B. et al.: ‘Traffic light recognition in varying illumination using deep learning and saliency map’.17th Int. Conf. on Intelligent Transportation Systems (ITSC) Qingdao China 2014 pp.2286–2291

Cited by 7 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. A review of driver gaze estimation and application in gaze behavior understanding;Engineering Applications of Artificial Intelligence;2024-07

2. Factors, Prediction, and Explainability of Vehicle Accident Risk Due to Driving Behavior through Machine Learning: A Systematic Literature Review, 2013–2023;Computation;2024-06-28

3. Towards applying image retrieval approach for finding semantic locations in autonomous vehicles;Multimedia Tools and Applications;2023-08-03

4. Fusion of Gaze and Scene Information for Driving Behaviour Recognition: A Graph-Neural-Network- Based Framework;IEEE Transactions on Intelligent Transportation Systems;2023-08

5. Smartphone Inertial Measurement Unit Data Features for Analyzing Driver Driving Behavior;IEEE Sensors Journal;2023-06-01