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Hauptverfasser: Zhu, Xinwen, Li, Zihao, Jiang, Yuxuan, Xu, Jiazhen, Wang, Jie, Bai, Xuyang
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2410.17576
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author Zhu, Xinwen
Li, Zihao
Jiang, Yuxuan
Xu, Jiazhen
Wang, Jie
Bai, Xuyang
author_facet Zhu, Xinwen
Li, Zihao
Jiang, Yuxuan
Xu, Jiazhen
Wang, Jie
Bai, Xuyang
contents The autonomous driving industry is rapidly advancing, with Vehicle-to-Vehicle (V2V) communication systems highlighting as a key component of enhanced road safety and traffic efficiency. This paper introduces a novel Real-time Vehicle-to-Vehicle Communication Based Network Cooperative Control System (VVCCS), designed to revolutionize macro-scope traffic planning and collision avoidance in autonomous driving. Implemented on Quanser Car (Qcar) hardware platform, our system integrates the distributed databases into individual autonomous vehicles and an optional central server. We also developed a comprehensive multi-modal perception system with multi-objective tracking and radar sensing. Through a demonstration within a physical crossroad environment, our system showcases its potential to be applied in congested and complex urban environments.
format Preprint
id arxiv_https___arxiv_org_abs_2410_17576
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Real-time Vehicle-to-Vehicle Communication Based Network Cooperative Control System through Distributed Database and Multimodal Perception: Demonstrated in Crossroads
Zhu, Xinwen
Li, Zihao
Jiang, Yuxuan
Xu, Jiazhen
Wang, Jie
Bai, Xuyang
Robotics
Artificial Intelligence
Systems and Control
The autonomous driving industry is rapidly advancing, with Vehicle-to-Vehicle (V2V) communication systems highlighting as a key component of enhanced road safety and traffic efficiency. This paper introduces a novel Real-time Vehicle-to-Vehicle Communication Based Network Cooperative Control System (VVCCS), designed to revolutionize macro-scope traffic planning and collision avoidance in autonomous driving. Implemented on Quanser Car (Qcar) hardware platform, our system integrates the distributed databases into individual autonomous vehicles and an optional central server. We also developed a comprehensive multi-modal perception system with multi-objective tracking and radar sensing. Through a demonstration within a physical crossroad environment, our system showcases its potential to be applied in congested and complex urban environments.
title Real-time Vehicle-to-Vehicle Communication Based Network Cooperative Control System through Distributed Database and Multimodal Perception: Demonstrated in Crossroads
topic Robotics
Artificial Intelligence
Systems and Control
url https://arxiv.org/abs/2410.17576