{"title":"Using the driving behaviour to design a forward collision probability index","authors":"Yuan-Lin Chen","doi":"10.1504/IJVS.2017.10006056","DOIUrl":null,"url":null,"abstract":"This paper uses the driving behaviour to design a Forward Collision Probability Index (FCPI) for alerting and to assist the driver to keep a safety driving distance for avoiding the forward collision accident in highway driving. We use the time-to-collision (TTC) as a main factor for calculating the FCPI. The index of FCPI is easy understanding for the driver even those who have no professional knowledge in vehicle technology. A self-learning algorithm for reducing the wrong warnings is presented for obtaining a suitable FCPI for the driver, which means that calculating the FCPI could meet each driver's behaviour. For the value of FCPI, value 0 is indicating the 0% probability of forward collision, and values 0.5 and 1 are indicating the 50% and 100% probabilities of forward collision, respectively. The experimental results guaranteed that the self-learning algorithm could figure out an optimal FCPI index for each driver to meet his/her driving behaviour and could reduce the wrong warnings.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"196-208"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Vehicle Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJVS.2017.10006056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 1
Abstract
This paper uses the driving behaviour to design a Forward Collision Probability Index (FCPI) for alerting and to assist the driver to keep a safety driving distance for avoiding the forward collision accident in highway driving. We use the time-to-collision (TTC) as a main factor for calculating the FCPI. The index of FCPI is easy understanding for the driver even those who have no professional knowledge in vehicle technology. A self-learning algorithm for reducing the wrong warnings is presented for obtaining a suitable FCPI for the driver, which means that calculating the FCPI could meet each driver's behaviour. For the value of FCPI, value 0 is indicating the 0% probability of forward collision, and values 0.5 and 1 are indicating the 50% and 100% probabilities of forward collision, respectively. The experimental results guaranteed that the self-learning algorithm could figure out an optimal FCPI index for each driver to meet his/her driving behaviour and could reduce the wrong warnings.
期刊介绍:
The IJVS aims to provide a refereed and authoritative source of information in the field of vehicle safety design, research, and development. It serves applied scientists, engineers, policy makers and safety advocates with a platform to develop, promote, and coordinate the science, technology and practice of vehicle safety. IJVS also seeks to establish channels of communication between industry and academy, industry and government in the field of vehicle safety. IJVS is published quarterly. It covers the subjects of passive and active safety in road traffic as well as traffic related public health issues, from impact biomechanics to vehicle crashworthiness, and from crash avoidance to intelligent highway systems.