{"title":"An automobile detection algorithm development for automated emergency braking system","authors":"L. Xia, Tran Duc Chung, K. A. A. Kassim","doi":"10.1145/2593069.2593083","DOIUrl":null,"url":null,"abstract":"Automated emergency braking (AEB) systems become more and more important than ever in modern vehicles for assisting drivers in emergency driving situations. They mostly require fusion techniques for vehicle detection (camera and radar or stereo-vision system) that require complicated algorithms and additional costs. These have caused AEB systems less attractive to the market. This paper presents an automobile detection algorithm using single camera for the AEB system. The algorithm contains three main steps: background subtraction, thresholding, and inverted U-shape back wheel detection. The simulation under MATLAB environment provides 87.25% and 78% of detection rate and accuracy, respectively for a 1080×1920 pixel input image; 88.25% and 73.5% of detection rate and accuracy for a 480×640 pixel input image. Processing time achieved are 0.156s and 0.0297s accordingly.","PeriodicalId":433816,"journal":{"name":"2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2593069.2593083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Automated emergency braking (AEB) systems become more and more important than ever in modern vehicles for assisting drivers in emergency driving situations. They mostly require fusion techniques for vehicle detection (camera and radar or stereo-vision system) that require complicated algorithms and additional costs. These have caused AEB systems less attractive to the market. This paper presents an automobile detection algorithm using single camera for the AEB system. The algorithm contains three main steps: background subtraction, thresholding, and inverted U-shape back wheel detection. The simulation under MATLAB environment provides 87.25% and 78% of detection rate and accuracy, respectively for a 1080×1920 pixel input image; 88.25% and 73.5% of detection rate and accuracy for a 480×640 pixel input image. Processing time achieved are 0.156s and 0.0297s accordingly.