{"title":"Comforting and Safer Highway Overtaking for Lane Change Based on Vehicles Speed Advisory","authors":"Hamid Sh. Aldulaimi, Bassem Ben Hamed","doi":"10.1109/ICCSA57511.2022.00019","DOIUrl":null,"url":null,"abstract":"In the present world, a lots of highway users could fall in unsafe overtaking maneuver to make un appropriate lane change, this is almost caused an a lot of highway accidents. Vehicular Ad-hoc Networks (VANET) applications can present many solutions to facilitate the driving along highways, such as driving awareness, V2V communication and data transmission, traffic analysis and so on. It is a principal task to make the right decision within right time due to the high speed of the vehicles and the changing conditions on the highway. In this article, we suggest an algorithm for safe overtaking maneuver for connected vehicles (what we called S-AV), the algorithm contributes to emphases the rules of safe lane-change along the highway to achieve the right decision for safe vehicles-overtaking at the right time. The proposed algorithm can classify the safe overtaking between vehicles into major categories based on different highway traffic situations, thus, the classification also based on different criteria of vehicle performance. The proposed algorithm designed to contribute in increase of driving safety on the highway. Finally, we have to suggest some vital research subjects that deals with VANETs safety and comfort issues that seek to the traffic decision center to advice all highway user with real-time information about the safe overtaking between vehicles at any segment of highway, it is a critical research issue to inspire the researchers how to integrate the connected vehicles with driver drowsiness detection techniques to obtain best safety factor on highway driving.","PeriodicalId":218147,"journal":{"name":"2022 22nd International Conference on Computational Science and Its Applications (ICCSA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 22nd International Conference on Computational Science and Its Applications (ICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSA57511.2022.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the present world, a lots of highway users could fall in unsafe overtaking maneuver to make un appropriate lane change, this is almost caused an a lot of highway accidents. Vehicular Ad-hoc Networks (VANET) applications can present many solutions to facilitate the driving along highways, such as driving awareness, V2V communication and data transmission, traffic analysis and so on. It is a principal task to make the right decision within right time due to the high speed of the vehicles and the changing conditions on the highway. In this article, we suggest an algorithm for safe overtaking maneuver for connected vehicles (what we called S-AV), the algorithm contributes to emphases the rules of safe lane-change along the highway to achieve the right decision for safe vehicles-overtaking at the right time. The proposed algorithm can classify the safe overtaking between vehicles into major categories based on different highway traffic situations, thus, the classification also based on different criteria of vehicle performance. The proposed algorithm designed to contribute in increase of driving safety on the highway. Finally, we have to suggest some vital research subjects that deals with VANETs safety and comfort issues that seek to the traffic decision center to advice all highway user with real-time information about the safe overtaking between vehicles at any segment of highway, it is a critical research issue to inspire the researchers how to integrate the connected vehicles with driver drowsiness detection techniques to obtain best safety factor on highway driving.