Traffic Accident Prevention in Low Visibility Conditions Using VANeTs Cloud environment

Kwok Tai Chui, Tanveer Singh Kochhar, Amit Chhabra, Sunil K. Singh, Deepinder Singh, Dragan Peraković, Ammar Almomani, Varsha Arya

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Road accidents have become a major concern for safety today. The increase in the number of vehicles has significantly increased the real-time road traffic, leading to many fatal accidents. Over the years, researchers have been trying to find solutions to enhance vehicular security in order to prevent these accidents or at least reduce their impact. This paper aims to contribute in this domain by studying the reaction time of vehicles in low visibility conditions and proposing a solution which can be implemented in the real world to prevent accidents in such scenarios. A novel algorithm is proposed which utilizes a modified form of AODV routing protocol in VANETS Cloud to alert the vehicles whenever a leading vehicle in the same lane slows down. This study can help the drivers by providing them sufficient time to react before any occurrence of an accident. The drivers would have a better idea about the vehicles in front, allowing them to make proper and informed decisions while driving in low visibility conditions.

Original languageEnglish
JournalInternational Journal of Cloud Applications and Computing
Volume12
Issue number1
DOIs
Publication statusPublished - 2022

Keywords

  • AODV
  • NS2
  • SUMO
  • VANET
  • VCC

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