騎乘自行車之潛在風險分析

ANALYSIS OF POTENTIAL RISKS FOR BICYCLIST

本研究針對都會區自行車使用者之潛在風險進行分析，期望了解造成自行車使用者所感知主觀風險之情境為何，本研究透過羅序（Rasch）模式分析自行車騎主觀風險認知；另一方面，則是透過自行車事故之客觀歷史資料進行迴歸分析，建構潛在風險因素和意外事故死亡人數之邏輯斯迴歸分析模式，並比較自行車使用者主觀風險和客觀資料所呈現之風險差異。本研究並透過羅序模式之DIF檢測與ANOVA分析，依基本特性將自行車使用者分類，找出風險感知度低之族群，並與自行車事故死亡機率的邏輯斯迴歸模型比較分析，進而找出對於行車環境中的高危險因子，但自行車使用者風險感知度低之高風險族群，並期望利用工程、教育與執法不同層面之改善來減少主觀和客觀因素間的風險落差，以提供自行車使用者一個安全舒適的行車環境。

This study aims to investigate the potential risks for bicyclists. The Rasch model is used to measure bicyclists’ subjective perceived risk, and logistic regression is constructed to find contributor to the bicycle accidents casualty. Besides, we compare the Rasch and logistic model to discuss the gap between subjective and objective view of the potential risks. Our result also demonstrates some situations may be dangerous but cyclist did not aware of it which is high potential risk. Furthermore, we characterize bicyclist by DIF test and ANOVA shows that male and older bicyclist ride at night has a higher risk to casualty accident. The finding of this study can help government to build a more safety riding environment for bicyclists.