本研究主要是運用數位行車記錄器與OBDII去收集各種不同的道路特徵資訊,在道路特徵資料的收集上分為山路、平面道路、高速公路以及混合型道路,並將這些收集來的資料建置到本研究所建置的道路資料庫系統中做儲存。 本研究在發展各種道路型的指標上主要分成四類型的指標,分別是轉彎型、干擾型、油耗型以及速度型的指標,這些指標主要是由八類型的指標所組成,一開始先對這八類型的指標進行單因子變異數分析,將同屬於同一種道路特徵的路況先以單因子變異數分析進行顯著的比較,將不同的路段做融合,之後運用主成份分析將八維度的指標進行萃取,並將萃取過後的結果套入至集群分析中進行道路分群的動作。 研究結果顯示,對於單因子變異數分析的結果上,可以把許多平面道路的特徵合併成同一種平面道路的道路別,主成份分析將各個指標萃取過後的結果再經過集群分析後,也確實把不同種的道路特徵完全分離開來。 另一主體是本研究論文也有對道路進行油耗分析,例如紅綠燈與油耗關係、道路彎曲程度與油耗關係以及道路坡度與油耗關係逐一做探討。
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.