{"title":"自动驾驶汽车功能能力的可靠性分析","authors":"Brain Ndlovu, M. Ayomoh","doi":"10.33889/ijmems.2023.8.5.054","DOIUrl":null,"url":null,"abstract":"The reliability of autonomous vehicles (AVs) is a research domain of high interest, covering a diverse pool of researchers, captains of smart auto industries, government agencies, and technology enthusiasts. The reliability of AVs is not extensively explored in the literature, despite the apprehension due to fatal accidents recorded in the past. Despite being in existence for over a decade, AVs have yet to reach a certified commercial-level deployment. Due to the complexity that comes with the self-operation of an AV, the issue of trustworthiness, which signifies reliability, becomes inevitable. The identification, analysis, and categorization of functional elements using systems engineering conceptual design principles and the linkage of these to the road traffic rules were conducted to address this. Also, the evaluation of the reliability of AVs using various developed vehicles from selected industries was addressed by integrating the traffic rules. The analysis of reliability was carried out using life-to-failure data premised on the probability plotting approach. It was found that there is a 99.94% chance that an autonomous vehicle will fail at least one of the traffic rules within 20 minutes of driving. Furthermore, the hazard rate of AVs was found to be on the rise, meaning a high indication of accidents.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reliability Analysis of the Functional Capabilities of an Autonomous Vehicle\",\"authors\":\"Brain Ndlovu, M. Ayomoh\",\"doi\":\"10.33889/ijmems.2023.8.5.054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The reliability of autonomous vehicles (AVs) is a research domain of high interest, covering a diverse pool of researchers, captains of smart auto industries, government agencies, and technology enthusiasts. The reliability of AVs is not extensively explored in the literature, despite the apprehension due to fatal accidents recorded in the past. Despite being in existence for over a decade, AVs have yet to reach a certified commercial-level deployment. Due to the complexity that comes with the self-operation of an AV, the issue of trustworthiness, which signifies reliability, becomes inevitable. The identification, analysis, and categorization of functional elements using systems engineering conceptual design principles and the linkage of these to the road traffic rules were conducted to address this. Also, the evaluation of the reliability of AVs using various developed vehicles from selected industries was addressed by integrating the traffic rules. The analysis of reliability was carried out using life-to-failure data premised on the probability plotting approach. It was found that there is a 99.94% chance that an autonomous vehicle will fail at least one of the traffic rules within 20 minutes of driving. Furthermore, the hazard rate of AVs was found to be on the rise, meaning a high indication of accidents.\",\"PeriodicalId\":44185,\"journal\":{\"name\":\"International Journal of Mathematical Engineering and Management Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mathematical Engineering and Management Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33889/ijmems.2023.8.5.054\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mathematical Engineering and Management Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33889/ijmems.2023.8.5.054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Reliability Analysis of the Functional Capabilities of an Autonomous Vehicle
The reliability of autonomous vehicles (AVs) is a research domain of high interest, covering a diverse pool of researchers, captains of smart auto industries, government agencies, and technology enthusiasts. The reliability of AVs is not extensively explored in the literature, despite the apprehension due to fatal accidents recorded in the past. Despite being in existence for over a decade, AVs have yet to reach a certified commercial-level deployment. Due to the complexity that comes with the self-operation of an AV, the issue of trustworthiness, which signifies reliability, becomes inevitable. The identification, analysis, and categorization of functional elements using systems engineering conceptual design principles and the linkage of these to the road traffic rules were conducted to address this. Also, the evaluation of the reliability of AVs using various developed vehicles from selected industries was addressed by integrating the traffic rules. The analysis of reliability was carried out using life-to-failure data premised on the probability plotting approach. It was found that there is a 99.94% chance that an autonomous vehicle will fail at least one of the traffic rules within 20 minutes of driving. Furthermore, the hazard rate of AVs was found to be on the rise, meaning a high indication of accidents.
期刊介绍:
IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.