The Study of Road Characteristic and Fuel Consumption Analysis
碩士 === 元智大學 === 資訊工程學系 === 100 === In this study is using digital driving recorder and OBDII to collect different of road characteristic information, on the road characteristic data collection are divided into the mountain road, flat roads, highways and the hybrid road, and the collection informatio...
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ndltd-TW-100YZU053920502015-10-13T21:33:10Z http://ndltd.ncl.edu.tw/handle/58209501703979311534 The Study of Road Characteristic and Fuel Consumption Analysis 道路特徵與油耗分析之研究 Wei-Sheng Chiu 邱偉盛 碩士 元智大學 資訊工程學系 100 In this study is using digital driving recorder and OBDII to collect different of road characteristic information, on the road characteristic data collection are divided into the mountain road, flat roads, highways and the hybrid road, and the collection information are bulid to the road database system to solve. In the development of different road index, and these index are divided into four types, the turning type, interference type, speed type and fuel consumption type, these four type index are composed of eight road index. First using one-way ANOVA analysis to let the same of road characteristic significant comparison, if it has not significant comparison, we will combine it. After using of principal component analysis of eight dimensions of index, and extraction results using the cluster analysis to cluster different of road characteristic. The results show one way ANOVA can be merge into many flat road, the principle component analysis extraction new index, and using this new index to cluster, its result can divided into every different of road characteristic. Another subject of this research paper on road fuel consumption analysis, such as traffic lights and fuel consumption relationships, the road curved relationship of the degree of fuel consumption and road slope and fuel consumption relationship do explore. Hsiu-HsenYao 姚修慎 學位論文 ; thesis 71 zh-TW |
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碩士 === 元智大學 === 資訊工程學系 === 100 === In this study is using digital driving recorder and OBDII to collect different of road characteristic information, on the road characteristic data collection are divided into the mountain road, flat roads, highways and the hybrid road, and the collection information are bulid to the road database system to solve.
In the development of different road index, and these index are divided into four types, the turning type, interference type, speed type and fuel consumption type, these four type index are composed of eight road index. First using one-way ANOVA analysis to let the same of road characteristic significant comparison, if it has not significant comparison, we will combine it. After using of principal component analysis of eight dimensions of index, and extraction results using the cluster analysis to cluster different of road characteristic.
The results show one way ANOVA can be merge into many flat road, the principle component analysis extraction new index, and using this new index to cluster, its result can divided into every different of road characteristic.
Another subject of this research paper on road fuel consumption analysis, such as traffic lights and fuel consumption relationships, the road curved relationship of the degree of fuel consumption and road slope and fuel consumption relationship do explore.
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author2 |
Hsiu-HsenYao |
author_facet |
Hsiu-HsenYao Wei-Sheng Chiu 邱偉盛 |
author |
Wei-Sheng Chiu 邱偉盛 |
spellingShingle |
Wei-Sheng Chiu 邱偉盛 The Study of Road Characteristic and Fuel Consumption Analysis |
author_sort |
Wei-Sheng Chiu |
title |
The Study of Road Characteristic and Fuel Consumption Analysis |
title_short |
The Study of Road Characteristic and Fuel Consumption Analysis |
title_full |
The Study of Road Characteristic and Fuel Consumption Analysis |
title_fullStr |
The Study of Road Characteristic and Fuel Consumption Analysis |
title_full_unstemmed |
The Study of Road Characteristic and Fuel Consumption Analysis |
title_sort |
study of road characteristic and fuel consumption analysis |
url |
http://ndltd.ncl.edu.tw/handle/58209501703979311534 |
work_keys_str_mv |
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