研究生: |
鄭志展 Chih-Chan Cheng |
---|---|
論文名稱: |
應用學習曲線於小客車及軍事卡車駕駛之探討 Learning Curve Analysis of Passenger Vehicle and Military Truck Driving |
指導教授: |
紀佳芬
Chia-Fen Chi 石裕川 Yuh-Chuan Shih |
口試委員: |
黃雪玲
Sheue-Ling Hwang 江行全 Bernard C. Jiang 林久翔 Chiuhsiang Joe Lin 陳協慶 Hsieh-Ching Chen 石裕川 Yuh-Chuan Shih 紀佳芬 Chia-Fen Chi |
學位類別: |
博士 Doctor |
系所名稱: |
管理學院 - 工業管理系 Department of Industrial Management |
論文出版年: | 2019 |
畢業學年度: | 107 |
語文別: | 中文 |
論文頁數: | 60 |
中文關鍵詞: | 學習曲線 、心智負荷 、駕駛學習 、高齡者 、大貨車 |
外文關鍵詞: | Learning Curve, Mental workload, Driving Training, Elderly Drivers, Truck |
相關次數: | 點閱:441 下載:1 |
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學習曲線可作為評估人員學習新工作績效的有效工具,透過學習率及主觀心智負荷可比較個體的學習成效及學習差異,進而改善訓練課程之設計。本研究主要區分高齡者模擬器駕駛學習及國軍大貨車駕駛訓練等二實驗進行討論。
高齡者模擬器駕駛實驗共招募20位受試者,其中高齡者及年輕人各10位,皆擁有小客車駕照,所有受試者操作模擬器10回合,並紀錄每回完成時間及第1、5、10回合之NASA-TLX負荷,透過學習曲線公式計算學習率與第一回完成時間。結果顯示高齡者之操作完成時間顯著較年輕人長,但兩者間的學習率無顯著差異,即高齡者學習力並未因老化而衰退,且高齡者較年輕人偏向認知學習,兩者間表現差距有縮小之傾向,另全體受試者工作負荷隨練習次數而顯著降低。學習曲線可作為高齡者模擬器駕駛能力學習效果之評估,且可納入高齡駕駛的安全規範或駕訓設計之參考,如高齡駕駛能力檢測標準之設定或駕訓課程內容是否足夠且可行。
大貨車駕訓實驗共招募國軍40位駕訓學員,區分為17位生手及23位熟手學員兩組,紀錄每位學員5個駕訓科目各28回合的練習時間與第10、第28回合的NASA-TLX負荷,5個科目包含倒車入庫、曲巷調頭、路邊停車、曲線進退及上下坡道。結果證實學習率及主觀負荷可區別學習差異,尤其經驗不足的生手練習前後的負荷變化大,其負荷感受高低幅度大過於有經驗學員,且易受學習表現(學習率、作業完成時間)影響,故此表示有經驗的熟手學員對於作業負荷的評估會較周延正確而具參考價值。
Learning curves can be used to determine the length of training for new workers and performance standards for a particular task. Learning rate and mental workload were found to be important measures for comparing individual differences in order to better design a training program.
The first experiment aimed to examine the age drivers’ learning effect and workload through a driving simulator. Twenty subjects, including 10 age and 10 young adult drivers, participated in the study. They all had valid license of small vehicle. All participants drove on a simulator and the same driving route was repeated 10 times. Each finishing time was recorded and the workload assessed by NASA-TLX was evaluated after the first, fifth, and tenth practice. For each participant, these data of finishing time were used to calculate the learning rate and theoretical first finishing time (T1).
The result showed that aging people had significant longer T1, but learning rate and workload (NASA-TXL) between aging and young people were not significantly different. Interestingly, the workload decreased with numbers of practices. Understanding the learning effect could be helpful to trainers in determining how to allocate training resources and/or schedule practices so as to optimize the training effectiveness. Notably, that of aging people having longer finishing time should be taken into account while legislating regulation, designing vehicle, and any actions for safety considerations.
The second experiment aimed to examine the experience effect on military truck training. Forty subjects, including 17 novice and 23 experienced drivers, participated in the study. The experiment was designed to collect the total 28 repeat task completion times and subjective mental workload of five driving tasks including (a) reverse into garage, (b) 3-point turn, (c) parallel parking, (d) S-curve, and (e) up-down-hill.
The results indicated that task completion times of truck driving can be predicted with a learning curve. Practice significantly reduced the mental workload rating. However, the novice trainees tended to have a more significant reduction because compared to experienced trainees, they tended to give greater or lower workload scores than the experienced trainees before and after practice, respectively. The current study may not be complete enough to provide guidelines for a training program, but it is adequate to suggest that learning rate and workload measure can serve as indexes for factoring in the individual differences.
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