Real-Time Multi-Task Environmental Perception System for Traffic Safety Empowered by Edge Artificial Intelligence-Reference-Cited by-同舟云学术

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Real-Time Multi-Task Environmental Perception System for Traffic Safety Empowered by Edge Artificial Intelligence

Published:2024-01 Issue:1 Volume:25 Page:517-531
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Liu Chenxi¹^ORCID,Yang Hao¹^ORCID,Zhu Meixin²^ORCID,Wang Feilong¹^ORCID,Vaa Torgeir³^ORCID,Wang Yinhai¹^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA

2. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Guangzhou, China

3. Norwegian Public Roads Administration, Oslo, Norway

Funder

Norwegian Public Roads Administration

Pacific Northwest Transportation Consortium

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10403543/10249217.pdf?arnumber=10249217

Reference44 articles.

1. Analysis of high-temperature forecast accuracy of consumer weather forecasts from 2005–2016;Rose,2017

2. A study on crashes related to visibility obstruction due to fog and smoke

3. Evaluation of international roughness index for asphalt overlays placed over cracked and seated concrete pavements

4. 13 Pedestrian flow and capacity: the highway capacity manual

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1. Decentralized Semantic Traffic Control in AVs Using RL and DQN for Dynamic Roadblocks;ICC 2024 - IEEE International Conference on Communications;2024-06-09

2. Cost-effective Vehicle Recognition System in Challenging Environment Empowered by Micro-Pulse LiDAR and Edge AI;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

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