Front-Vehicle and Lane Detection with Emulated Mobile Devices
碩士 === 國立臺北科技大學 === 電子工程系 === 106 === As technology in the automotive industry is being seen more important nowadays, Advance Driver Assistance Systems is one of the most research topics in the industry. The main purpose is not to control the vehicle but to analyze the working environment in order t...
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ndltd-TW-106TIT054270692019-07-04T06:00:00Z http://ndltd.ncl.edu.tw/handle/b675zq Front-Vehicle and Lane Detection with Emulated Mobile Devices 模擬行動裝置之前車與車道偵測警示系統 Chun-Yuan Chen 陳俊元 碩士 國立臺北科技大學 電子工程系 106 As technology in the automotive industry is being seen more important nowadays, Advance Driver Assistance Systems is one of the most research topics in the industry. The main purpose is not to control the vehicle but to analyze the working environment in order to provide valuable information to the drive to prevent accidents. According to reports from multiple countries transportation accident analysis, the two majority cause of accidents are vehicle leaving their lane and not keeping a safe distance to the vehicle in front. Vehicle needs to be at least 50 meters when traveling 100 kilometers an hour. To prevent these types of accidents, LDW is put into action. Previous systems use characteristics such as the shadow of the vehicle, horizontal or vertical structure, license plate … etc to increase the accuracy, but with the cost of low efficiency in systems calculation. Purpose of this research is to improve the systems ability to recognize the road and to eliminate noise caused by characters written on the road. Also, utilizing horizontal characteristic of the vehicle and overlapping the image of shadows from the rear light during night and day can well improve the noise that was previously mentioned. With collaboration of the sensors monitoring the vehicle ahead, these systems can help increase the accuracy of a vehicle keeping in lane. Sun-Yen Tan 譚巽言 2018 學位論文 ; thesis 65 zh-TW |
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zh-TW |
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碩士 === 國立臺北科技大學 === 電子工程系 === 106 === As technology in the automotive industry is being seen more important nowadays, Advance Driver Assistance Systems is one of the most research topics in the industry. The main purpose is not to control the vehicle but to analyze the working environment in order to provide valuable information to the drive to prevent accidents.
According to reports from multiple countries transportation accident analysis, the two majority cause of accidents are vehicle leaving their lane and not keeping a safe distance to the vehicle in front. Vehicle needs to be at least 50 meters when traveling 100 kilometers an hour. To prevent these types of accidents, LDW is put into action. Previous systems use characteristics such as the shadow of the vehicle, horizontal or vertical structure, license plate … etc to increase the accuracy, but with the cost of low efficiency in systems calculation.
Purpose of this research is to improve the systems ability to recognize the road and to eliminate noise caused by characters written on the road. Also, utilizing horizontal characteristic of the vehicle and overlapping the image of shadows from the rear light during night and day can well improve the noise that was previously mentioned. With collaboration of the sensors monitoring the vehicle ahead, these systems can help increase the accuracy of a vehicle keeping in lane.
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author2 |
Sun-Yen Tan |
author_facet |
Sun-Yen Tan Chun-Yuan Chen 陳俊元 |
author |
Chun-Yuan Chen 陳俊元 |
spellingShingle |
Chun-Yuan Chen 陳俊元 Front-Vehicle and Lane Detection with Emulated Mobile Devices |
author_sort |
Chun-Yuan Chen |
title |
Front-Vehicle and Lane Detection with Emulated Mobile Devices |
title_short |
Front-Vehicle and Lane Detection with Emulated Mobile Devices |
title_full |
Front-Vehicle and Lane Detection with Emulated Mobile Devices |
title_fullStr |
Front-Vehicle and Lane Detection with Emulated Mobile Devices |
title_full_unstemmed |
Front-Vehicle and Lane Detection with Emulated Mobile Devices |
title_sort |
front-vehicle and lane detection with emulated mobile devices |
publishDate |
2018 |
url |
http://ndltd.ncl.edu.tw/handle/b675zq |
work_keys_str_mv |
AT chunyuanchen frontvehicleandlanedetectionwithemulatedmobiledevices AT chénjùnyuán frontvehicleandlanedetectionwithemulatedmobiledevices AT chunyuanchen mónǐxíngdòngzhuāngzhìzhīqiánchēyǔchēdàozhēncèjǐngshìxìtǒng AT chénjùnyuán mónǐxíngdòngzhuāngzhìzhīqiánchēyǔchēdàozhēncèjǐngshìxìtǒng |
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