使用類神經網路與模糊法評估分心因素對車輛駕駛行為之影響分析

Abstract

本研究從駕駛者的觀點出發，依據駕駛者的表現行為，如反應時間與心跳率此二項量測數據，使用具有學習能力的類神經網路及加入專家知識規則之模糊邏輯控制，建立安全程度評估系統，分析在分心因素影響下，駕駛者的安全程度，以期能夠達到預警作用，降低因分心而造成的事故發生率。

This thesis measures the parameters of drivers’ behavior like the response time and the heart rate. For the safety evaluation, the thesis combines neural network which has the learning capability and fuzzy logics which carries the rule base from expert’s knowledge, and then establishes the safety degree evaluation system to analyze the drivers’ safety degree when they are distracted. The safety degree evaluation system raises an alarm in time when drivers are going to be distracted.