Deep learning-based pedestrian trajectory prediction and risk assessment at signalized intersections using trajectory data captured through roadside LiDAR-Reference-Cited by-同舟云学术

Deep learning-based pedestrian trajectory prediction and risk assessment at signalized intersections using trajectory data captured through roadside LiDAR

Published:2023-05-14 Issue: Volume: Page:1-13
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Zhou Shanglian¹^ORCID,Xu Hao²^ORCID,Zhang Guohui¹,Ma Tianwei³,Yang Yin⁴

Affiliation:

1. Department of Civil and Environmental Engineering, University of HI at Manoa, Honolulu, HI, USA

2. Department of Civil and Environmental Engineering, University of NV, Reno, Reno, NV, USA

3. College of Engineering, Texas A&M University-Corpus Christi, Corpus Christi, TX, USA

4. School of Computing, The University of UT, Salt Lake City, UT, USA

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Information Systems,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2023.2209912

Reference34 articles.

1. Pedestrian and Cyclist Detection and Intent Estimation for Autonomous Vehicles: A Survey

2. Practical Recommendations for Gradient-Based Training of Deep Architectures

3. An introduction to ROC analysis

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