大專院校學生死亡交通事故類型與影響因子分析之研究

Abstract

交通事故傷害為台灣年輕族群的首要死因，年輕族群中的大專院校學生因交通事故死亡之人數超過其總死亡數的五成，顯示瞭解大專學生死亡交通事故之重要性。本研究目的為分析大專學生死亡交通事故，應用統計方法及約略集合理論探討事故類型與影響因子之關聯，藉以描繪大專學生死亡交通事故型態，作為交通安全改善之參考依據。 本研究對象為民國92年至95年因交通事故死亡之學生數為全國大專院校前22名學校，蒐集這22所學校四年內發生之學生死亡交通事故案件進行分析，並根據學生年級將資料區分為新生(一年級學生)事故及非新生(二年級以上學生)事故。本研究首先透過頻率分析瞭解事故因子的分布概況，採用卡方檢定得知對於事故類型具顯著影響之因子；接續利用羅吉斯迴歸模式建構大專學生死亡交通事故模式，瞭解影響單一車輛事故與多車碰撞事故發生之關鍵因子；另外應用約略集合理論分析交通事故因果鏈，藉由事故案件推演之決策規則掌握事故類型與影響因子之邏輯關係。 研究結果顯示學生交通工具、精神狀況及道路型態這三項因素會顯著影響兩類型交通事故發生之可能性，其中新生駕駛汽車發生造成死亡的單一車輛事故勝算明顯較高，而非新生較不可能在精神狀況良好或道路型態為十字路口時發生單一車輛事故。另外，新生單一車輛事故常見型態為學生精神良好時行駛於有建築物郊區的直路上，而非新生常見的單一車輛車事故型態則為學生持有重型機車駕照於凌晨且精神疲勞時行駛於道路上。建議學校根據學生常見事故型態輔以實際案例加強該族群交通安全宣導教育，相關單位制定因應制度及措施減少大專院校學生交通事故傷害。

Logistic regression and rough set theory are applied to analyze the relation between types and factors of fatal traffic accidents involving college students in the study. A sample of over 200 accident cases is included. The data are classified into freshman and non-freshman accident according to the grade of the students. Chi-squared test of independence is used first to identify key factors affecting accident types, and then logistic regression model is constructed to determine the odds of being involved in a single vehicle accident. Besides, rough set theory is utilized to propose accident casual chains which imply the logical links between factors and accident types. The results show that students’ vehicle and psychological conditions and road types are three significant factors which have great influences on accident types. Freshman is more likely to be involved in a single vehicle accident when he/she drives a car, while non-freshman is less likely to be involved when he/she is in good condition or on an intersection. Moreover, the frequently-occurred single vehicle accident patterns are found: freshman in good condition drives/rides on a straight road in the suburbs; non-freshman with motorcycle license is tired while driving/riding deep in the night.