【摘要】：駕駛風(fēng)格指駕駛員在日常生活中習(xí)慣性的駕駛方式。駕駛風(fēng)格因人而異，對駕駛行為有重要的影響。本研究分為兩個部分。 研究一：多維度駕駛風(fēng)格量表的修訂 通過“滾雪球”技術(shù)，在全國20個大中城市先后分兩次選取655名駕駛員參加測試。經(jīng)過項目分析，探索性因素分析和驗證性因素分析，形成中文版多維度駕駛風(fēng)格量表（MDSI-C）。MDSI-C共24個項目，分為感覺尋求、憤怒、焦慮、分心和冒險五個維度。MDSI-C主要用來測量駕駛員冒險型、憤怒型和焦慮型三種非適應(yīng)性駕駛風(fēng)格。 MDSI-C總的信度為0.86，各個維度的內(nèi)部一致性系數(shù)均在0.70以上。各個維度與量表總分的相關(guān)系數(shù)在0.60~0.77之間，均p 0.001，說明量表具有很好的內(nèi)容效度。驗證性因素分析發(fā)現(xiàn)，修訂版量表的模型擬合度和結(jié)構(gòu)效度均較好。 研究二：不同情緒狀態(tài)對駕駛風(fēng)格的影響研究 在遼寧省沈陽和大連兩個城市，，隨即入戶選取188名駕駛員參加測試。被試先后完成中文版多維度駕駛風(fēng)格量表和駕駛員情緒狀態(tài)量表。結(jié)合人口學(xué)因素和不同情緒狀態(tài)，通過分層回歸分析來探索駕駛風(fēng)格最有力的預(yù)測因子，研究結(jié)論如下： 第一，駕駛員情緒量表的憤怒，緊張和抑郁維度均與MDSI-C各維度成正相關(guān)。精力維度與MDSI-C分心維度呈微弱負相關(guān)。 第二，駕駛員各人口學(xué)因素和不同情緒狀態(tài)的因素主效應(yīng)與交互作用，可以解釋MDSI-C感覺尋求維度33.2%的變異，憤怒維度39.6%的變異，冒險維度29.9%的變異，焦慮維度37.8%的變異，分心維度42.2%的變異。 第三，駕駛員各人口學(xué)因素和不同情緒狀態(tài)的因素主效應(yīng)與交互作用，可以解釋MDSI-C冒險型駕駛風(fēng)格31.8%的變異，憤怒型駕駛風(fēng)格37.5%的變異，焦慮型駕駛風(fēng)格43.1%的變異。 總體來說，中文版多維度駕駛風(fēng)格量表具有很好的信、效度。量表為今后評估職業(yè)駕駛員的駕駛行為，篩選事故傾向性駕駛員等提供一個可靠的測量工具。同時，該研究首次揭示了情緒狀態(tài)對駕駛風(fēng)格的影響，豐富了駕駛行為與駕駛風(fēng)格關(guān)系模型，為開發(fā)消極情緒影響駕駛風(fēng)格的實時監(jiān)測技術(shù)提供了科學(xué)依據(jù)。
[Abstract]:Driving style refers to the driver's habitual driving style in daily life. Driving styles vary from person to person and have an important impact on driving behavior. This study is divided into two parts. Research 1: the revision of the Multidimensional driving style scale was carried out by snowballing technique. 655 drivers were selected twice in 20 large and medium-sized cities in China to take part in the test. After item analysis, exploratory factor analysis and confirmatory factor analysis, a Chinese version of Multidimensional driving style scale (MDSI-C) .MDSI-C was formed, which was divided into feeling seeking, anger and anxiety. Five dimensions of distraction and risk-taking. MDSI-C was mainly used to measure three kinds of non-adaptive driving styles: risk-taking, anger and anxiety. The total reliability of MDSI-C was 0.86, and the internal consistency coefficient of each dimension was above 0.70. The correlation coefficient between each dimension and the total score of the scale was between 0.60 and 0.77, all P 0.001, which indicated that the scale had good content validity. Confirmatory factor analysis showed that the model fit and structural validity of the revised scale were good. Study 2: the influence of different emotional states on driving style was studied in Shenyang and Dalian, Liaoning Province. 188 drivers were selected to take part in the test. Subjects completed the Chinese version of the multi-dimensional driving style scale and driver emotional state scale. Combined with demographic factors and different emotional states, the most powerful predictors of driving style were explored by hierarchical regression analysis. The conclusions were as follows: first, anger of driver's emotion scale, Both stress and depression dimensions were positively correlated with MDSI-C dimensions. There was a weak negative correlation between energy dimension and MDSI-C distraction dimension. Secondly, the main effects and interactions of drivers' demographics and different emotional states can explain the 33.2% variation of MDSI-C sensation, 39.6% variation of anger dimension, 29.9% variation of risk-taking dimension, 37.8% variation of anxiety dimension. The variation of distraction dimension was 42.2%. Thirdly, the main effect and interaction of demography factors and different emotional states of drivers can explain the variation of MDSI-C risk-taking driving style 31.8%, angry driving style 37.5%, anxiety driving style 43.1%. In general, the Chinese version of the Multidimensional driving style scale has good reliability and validity. The scale provides a reliable measurement tool for evaluating the driving behavior of professional drivers and screening accident prone drivers in the future. At the same time, this study for the first time reveals the influence of emotional state on driving style, enriches the model of relationship between driving behavior and driving style, and provides a scientific basis for the development of real-time monitoring technology of negative emotion influencing driving style.
【學(xué)位授予單位】：遼寧師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：B842.6

【參考文獻】

相關(guān)期刊論文 前2條

1 孫舒放;Chris S. Dula;Cristi L. Adams;;1282名駕駛員焦慮水平與危險駕駛關(guān)系研究[J];廣東醫(yī)學(xué);2009年10期

2 孫龍;常若松;;營運駕駛員駕駛風(fēng)格研究[J];人類工效學(xué);2014年03期

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