The COVCRAV project: Architecture and design of a cooperative V2V crash avoidance system

Outay, Fatma; Bargaoui, Hichem; Chemek, Anouar; Kamoun, Faouzi; Yasar, Ansar-Ul-Haque

doi:10.1016/j.procs.2019.11.062

Cited by 5 publications

(1 citation statement)

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“…Connected Vehicle Crash Avoidance (COVCRAF) [14] emerges as an alternative from a previous collision avoidance system that depends on a sensor-based mechanism to detect and avoid the road hazard condition. In a sensor-based order, the information gathered from the environment depends on the internal sensor capability without receiving information from other vehicles around the vehicles at various road conditions.…”

Section: A Intelligent Transportation System (Its)mentioning

confidence: 99%

A Study of V2V Communication on VANET: Characteristic, Challenges and Research Trends

Bintoro¹

2021

JISA

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Vehicle to Vehicle (V2V) communication is a specific type of communication on Vehicular Ad Hoc Network (VANET) that attracts the great interest of researchers, industries, and government attention in due to its essential application to improve safety driving purposes for the next generation of vehicles. Our paper is a systematic study of V2V communication in VANET that cover the particular research issue, and trends from the recent works of literature. We begin the article with a brief V2V communication concept and the V2V application to safety purposes and non-safety purposes; then, we analyze several problems of V2V communication for VANET related to safety issues and non-safety issues. Next, we provide the trends of the V2V communication application for VANET. Finally, provide SWOT analysis as a discussion to identify opportunities and challenges of V2V communication for VANET in the future. The paper does not include a technical explanation. Still, the article describes the general perspective of VANET to the reader, especially for the beginner reader, who intends to learn about the topic.

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Section: A Intelligent Transportation System (Its)mentioning

confidence: 99%