以模糊法評估分心因素對行車安全之影響

Abstract

近十年來汽車工業快速的成長，汽車早已成為大眾所依賴的交通工具；但也因車輛數目的急速增加，導致交通事故的事件天天在新聞媒體播放。而這些人為因素所造成的遺憾都是社會及家庭的重大損失。 本論文從分心駕駛得到靈感，利用設計不同類型的分心會造成不同程度的感知反應時間和心跳率；並且藉由模糊邏輯的規劃、輸入輸出的歸屬函數建立、模糊化及解模糊化後所得到的結果推論出分心程度的高或低；意即安全程度的低或高，則即可在駕駛者因為分心未注意車況時達到提醒的功能，進一步避免車禍的發生。

Due to the rapid growth of the automobile industry in the last decade, cars have become the most popular means of transportation. However, the growing number of vehicles has contributed to the rise in traffic accidents. These accidents, mostly caused by man-made error, bring severe loss to the families of the victims as well as the society. Inspired by different modes of driving distractions, the thesis designs experiences of different driving distractions to obtain readings of time of perceptual response and the rates of heart beat of the driver under different modes. The thesis then employs fuzzy logics and membership function of Input and Output to infer the risk of different modes of driving distraction by fuzzification and defuzzification. This level of risk of different modes of driving distraction, in other words, level of safety, can serve as warnings to drivers and prevent future traffic accidents.