{"title":"Context-Aware Cooperative Collision Avoidance Vehicle Braking Alert System for VANET","authors":"Zeeshan Shafiq, L. U. Khan, S. Mahmud, G. M. Khan","doi":"10.5555/2762722.2762739","DOIUrl":null,"url":null,"abstract":"Cooperative safety and infotainment were the key motivating factors behind the advent of vehicular communication architecture. In this paper, the Context-aware cooperative collision avoidance braking system is proposed. The vehicles moving in the same lane, closer than the safety distance (SD) are prompted to reduce their speed or increase the inter-vehicular distance. The SD is set according to the available parameters and road infrastructure, and is further tuned with the help of context-aware SD adjustment system. The system proposed is self-learning and alert messages are directed to only pertinent vehicles with the help of clustering. The hardware system is implemented in vehicle on highway for SD calculation.","PeriodicalId":426100,"journal":{"name":"International Conference on Context-Aware Systems and Applications","volume":"452 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Context-Aware Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5555/2762722.2762739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Cooperative safety and infotainment were the key motivating factors behind the advent of vehicular communication architecture. In this paper, the Context-aware cooperative collision avoidance braking system is proposed. The vehicles moving in the same lane, closer than the safety distance (SD) are prompted to reduce their speed or increase the inter-vehicular distance. The SD is set according to the available parameters and road infrastructure, and is further tuned with the help of context-aware SD adjustment system. The system proposed is self-learning and alert messages are directed to only pertinent vehicles with the help of clustering. The hardware system is implemented in vehicle on highway for SD calculation.