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 2020

 DRIVING BEHAVIOR ANALYSIS ON GPS DATA USING MACHINE LEARNING METHODS

 Bin Ibrahim, Sultan Ibrahim


//uquui/handle/20.500.12248/130903
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DRIVING BEHAVIOR ANALYSIS ON GPS DATA USING MACHINE LEARNING METHODS

رقم الطلب : 24410
الناشر :جامعة أم القرى
مكان النشر : مكة المكرمة
تاريخ النشر : 2020 - 1442 هـ
الوصف : 96 ورقة.
نوع الوعاء : ماجستير
اللغة : انجليزي
المصدر : مكتبة الملك عبدالله بن عبدالعزيز الجامعية
يظهر في المجموعات : الرسائل العلمية المحدثة

Traffic analysis of vehicles in densely populated areas and places of public gathering can provide interesting insights into crowd behavior. Hajj is a spatio-temporally bound religious activity that is held annually and attended by more than 2 million people. More than 17,000 buses are used to transport pilgrims on fixed days to fixed locations. This poses great challenges in terms of crowd management. Using Global Positioning System (GPS) and Automatic Vehicle Location (AVL) sensors attached to buses, a large amount of spatio-temporal vehicle data can be collected for traffic analysis. In this paper, we present a study whereby driver behavior was extracted from an analysis of vehicle big data. We have explained in detail how we collected data, cleaned it, moved it to a big data repository, processed it and extracted information that helped us characterize driver behavior according to our definition of aggressiveness. We have used data from 17,000 buses that has been collected during Hajj 2018.

العنوان: DRIVING BEHAVIOR ANALYSIS ON GPS DATA USING MACHINE LEARNING METHODS
المؤلفون: Felemban, Emad
Bin Ibrahim, Sultan Ibrahim
الموضوعات :: Computer Science
Computer systems
تاريخ النشر :: 2020
الناشر :: جامعة أم القرى
الملخص: Traffic analysis of vehicles in densely populated areas and places of public gathering can provide interesting insights into crowd behavior. Hajj is a spatio-temporally bound religious activity that is held annually and attended by more than 2 million people. More than 17,000 buses are used to transport pilgrims on fixed days to fixed locations. This poses great challenges in terms of crowd management. Using Global Positioning System (GPS) and Automatic Vehicle Location (AVL) sensors attached to buses, a large amount of spatio-temporal vehicle data can be collected for traffic analysis. In this paper, we present a study whereby driver behavior was extracted from an analysis of vehicle big data. We have explained in detail how we collected data, cleaned it, moved it to a big data repository, processed it and extracted information that helped us characterize driver behavior according to our definition of aggressiveness. We have used data from 17,000 buses that has been collected during Hajj 2018.
الوصف :: 96 ورقة.
الرابط: http://dorar.uqu.edu.sa//uquui/handle/20.500.12248/130903
يظهر في المجموعات :الرسائل العلمية المحدثة

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24410.pdf
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الرسالة الكاملة3.04 MBAdobe PDFعرض/ فتح
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Absa24410.pdf
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ملخص الرسالة بالعربي78.86 kBAdobe PDFعرض/ فتح
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Abse24410.pdf
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ملخص الرسالة بالإنجليزي8.99 kBAdobe PDFعرض/ فتح
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Indu24410.pdf
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المقدمة215.15 kBAdobe PDFعرض/ فتح
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cont24410.pdf
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فهرس الموضوعات162.95 kBAdobe PDFعرض/ فتح
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Title24410.pdf
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غلاف21.08 kBAdobe PDFعرض/ فتح
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