Pith. sign in

REVIEW 1 cited by

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

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2410.17576 v1 pith:ZIZJKV2B submitted 2024-10-23 cs.RO cs.AIcs.SYeess.SY

classification cs.ROcs.AIcs.SYeess.SY
keywords systemautonomouscommunicationvehicle-to-vehiclecontrolcooperativedistributeddriving
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. APEX$^2$: Adaptive and Extreme Summarization for Personalized Knowledge Graphs

    cs.LG 2024-12 conditional novelty 5.0 of 10

    APEX2 maintains an extremely small personalized knowledge graph by decaying old interest scores, diffusing new query heat, and incrementally re-sorting triples, outperforming static summarizers in simulated evolving-q...

Pith tools