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題名:濃霧中前車緊急煞車時道路駕駛人對前車相對速度感知與反應時間不確性之關聯--以海森堡不確定性原理觀點
書刊名:運輸計劃
作者:陳穆臻 引用關係吳熙仁
作者(外文):Chen, Mu-chenWu, Hsi-jen
出版日期:2017
卷期:46:2
頁次:頁117-140
主題關鍵詞:濃霧前車相對速度感知量子光流反應時間不確定性Foggy conditionPerceived relative speedQuantum optical flowReaction timeUncertainty
原始連結:連回原系統網址new window
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濃霧影響道路駕駛人對速度和距離感知的判斷;然而,在濃霧中前車緊急煞車時,駕駛人對前車相對速度感知與反應時間不確性是複雜的,需要進一步探討。本研究嘗試以海森堡不確定性原理觀點出發,除探討前述特殊環境與路況下,兩者不確性之權衡關聯性外,亦設計 1個二階段實驗,依序驗證兩項假說:(1)假設濃霧中,本車駕駛人對前車相對速度感知所產生之心理物能動能的不確定性,與其反應時間不確定性之間,存在權衡關聯性;(2)假設濃霧中,在駕駛心理負荷和相對速度感知平均值條件下,相對速度感知與反應時間不確性存在權衡關聯性。實驗結果顯示兩項權衡關聯性均存在。另外,比較其結果與附加晴朗天候條件之實驗結果,發現濃霧和晴朗天候之 2個動作常數無明顯差異。本研究結果有助於解釋濃霧中跟車現象,激發新的駕駛人感知車流理論之發展。
Foggy weather conditions affect uncertainties of driver perceptual judgments of speed and distance. However, in a heavy foggy condition and a leading vehicle braking condition uncertainties of perceived relative speed and reaction time are complicated and need to be identified. If those uncertainties in a foggy weather condition exist in a perspective imitating Heisenberg Uncertainty Principle, then some phenomena for the following driver behaviors can be explained. The purpose of the research aimed to test the first hypothesis that explained a trade-off relationship between uncertainties of perceived psychological energy and uncertainties of reaction time of following vehicle drivers, and the second hypothesis that stated a trade-off relation between uncertainties of reaction time and uncertainties of perceived relative speed in regard to averages of perceived relative speed and mental workload. One additional experiment have conducted, giving comparisons with those uncertainties exist in a clear weather condition having been tested in Sheu’s two-stage experiment based on a quantum optical flow-based model. The findings of this study not only show that those uncertainties also exist in foggy and braking conditions but also indicate the statistical significant no-difference between the two action constants in foggy and clear weather conditions. The results may help to characterize car following phenomena in foggy conditions under driver perception uncertainties and to stimulate new ideas for the development of dynamic, stochastic and time-varying driver perception model and theories.
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