mlsanityData to 14 Oct 2026

Real-time Vehicle-to-Vehicle Communication Based Network Cooperative Control System through Distributed Database and Multimodal Perception: Demonstrated in Crossroads

arXiv 2410.17576 ↗First posted 23 Oct 2024cs.RO cs.AI cs.SYcited by 6

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Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 5 of its 23 references that are in the map. First posted on arXiv 23 Oct 2024.

Builds on

5 of 23 references.

References · 5

  1. 2019Exploring the Limitations of Behavior Cloning for Autonomous Drivingcited by 346
  2. 2024Advances in APPFL: A Comprehensive and Extensible Federated Learning Frameworkcited by 19
  3. 2021Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehiclescited by 10
  4. 2021LiDAR Cluster First and Camera Inference Later: A New Perspective Towards Autonomous Drivingcited by 4
  5. 2018LiDAR and Camera Detection Fusion in a Real Time Industrial Multi-Sensor Collision Avoidance Systemcited by 2

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Citing papers per year: 2024: 1; 2025: 5.

6 papers.