都會區運具種類眾多，包括私人運具如小客車及機車，大眾運輸系統如公車、捷運等，由於大型車輛為民眾較常搭乘的大眾運輸運具，能減少私人運具的使用，提升能源的使用效率，但肇事時會造成重大傷亡，每常成為社會關注的焦點。因此，本研究先以都會區大型車輛職業駕駛人為研究對象，配合記錄資料設備的可設置性，收集駕駛行為資料，據以分析能源消耗及不當駕駛行為，以作為宣導及矯正駕駛行為的依據，並研擬我國發展大型車輛職業駕駛人訓練制度可能對策。 本研究引進VigilVanguard行車偵測系統，並且配合OBDII車輛診斷設備針對100位不同的大客車職業駕駛者，以都會區的路線進行實車測詴。收集駕駛行為資料，包含行車影像、車速、加速度和瞬間耗油量等，據以分析能源消耗及不當駕駛行為，以作為宣導及矯正駕駛行為的依據。 研究中完整將30位大客車駕駛的行車數據透過自動化程式分類成11種駕駛行為，並計算出各種駕駛行為油耗分析結果。結果顯示，屬於直行的駕駛行為其燃油效率會受速度影響，亦會受加速/減速影響。於非加速行為中，燃油效率以最高平均速度時為最高，而在加速行為下，燃油效率則以未踩油門時的減速(中度及重度)、滑行時為最高。 Reducing energy consumption and the greenhouse effect is an important issue for our country. Educating drivers to learn correct driving behavior is a feasible way to achieve this objective. Eco-driving has been proved to save up to 7% of energy consumption in Europe. The research is to observe driving behavior of professional dual-axle passenger drivers through an electric recorder installed on the bus. This research used the VigilVanguard detection system that comes from the Australia to combine the OBDII on-board diagnostic device to experiment the 100 different bus drivers. In the experiment, researcher collected the data of driving process, including driving image, speed, acceleration and instantaneous fuel consumption and so on. According to the driving data, we analyzed the fuel consumption and unsafe driving behaviors, and develop the training system for the large vehicle of professional drivers. This research analyzed the driving data of the 30 bus drivers to classify the 11 different driving behaviors and fuel economy.During acceleration and nonacceleration behaviors, the speed and acceleration of behavior affected the fuel ecomony. During nonacceleration behaviors, the highest mean speed had the largest fuel economy. During acceleration behavior, deceleration behavior and coasting behavior had the largest fuel economy.
