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    Please use this identifier to cite or link to this item: http://ir.cnu.edu.tw/handle/310902800/31916


    標題: 駕駛模擬器訓練駕駛之風險感知信效度分析
    The Reliability and Validity of the Driving Perception Risk in Simulator Training
    作者: 歐晏均
    貢獻者: 應用空間資訊系
    許桂樹
    關鍵字: 車載模擬平台(PreScan)
    駕駛訓練
    風險感知
    driving simulation
    PreScan
    driving training
    Perception Risk
    日期: 2018
    上傳時間: 2019-02-27 16:48:23 (UTC+8)
    摘要: 在過去駕訓考試中多採用場內考照制度,應試者通常只要熟記口訣就能通過考試,對實際道路狀況沒有有效的幫助,而目前我國開始以正式上路實施場外路考,雖然學員在面對真實路面狀況有更好的體驗,但對於駕駛經驗的累積仍然杯水車薪,因為新手駕駛與經驗駕駛對於路面風險感知程度不一樣,新手駕駛比較難以察覺道路上潛在的風險,需要在風險中逐漸累積經驗,本研究以風險事件模擬與測試的方式,讓不同程度經驗的駕駛進行情境查覺訓練。  
    本研究以駕駛模擬系統作為研究工具,使用車載模擬平台PreScan製作類真實的交通環境,讓受測駕駛員在駕駛模擬過程觀察道路中的潛在風險進行風險感知的教育,從風險感知的訓練結果分別紀錄每次訓練對於風險發生的感知時間、反應時間以及決策是否正確,從結果比對取得風險訓練的信效度分析。結果表明:模擬器的風險訓練,對於駕駛對道路風險認知的學習有顯著的成長效果。
    In the past, the on-site examination system was adopted in the driving test. As long as they remember exam questions can usually pass the exam, there is no effective help for the actual road conditions. Currently, road tests have been formally implemented in our country, so that trainees can get students can gain better learning results in the face of real road conditions, but the accumulation of driving experience is still not enough, because novice and experienced drivers have different levels of road perception risk, with the former required to gradually accumulate experience from risks because it is more difficult for them to perceive potential road risks.   
    In this project, a driving simulation system was employed as the research tool. The car simulation platform PreScan was used to produce the semi real traffic environment for the perception risk education, which enabled the trained drivers to observe the potential road risks in the simulation process, where the perception risk time and risk reaction time for all training were recorded to determine whether the decision-making was correct. The reliability and validity analysis results indicated that the simulator-based risk training could significantly enhance the learning of road perception risks for drivers.
    關聯: 電子全文公開日期:2020-08-01,學年度:106, 56頁
    Appears in Collections:[應用空間資訊系(所)] 博碩士論文

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