霧天高速公路預警措施有效性評估
發(fā)布時間:2018-09-08 14:03
【摘要】:霧天高速公路行車存在很大安全隱患,相關(guān)部門和學者對其提出了許多處置措施,然而,有關(guān)措施的有效性評估研究較少。本文針對可變信息板及霧燈此兩類典型措施開展有效性分析,通過駕駛模擬平臺構(gòu)建高速公路場景,結(jié)合眼動儀,分析霧天高速公路措施對行車風險及駕駛員行為影響,為相關(guān)管理者采取有效的預警措施以提高高速公路車輛通行的安全性提供參考。研究從以下幾方面進行。首先,針對長沙市境內(nèi)的京珠高速和繞城高速開展霧天實地調(diào)查,對獲取的車速、車頭時距數(shù)據(jù)進行統(tǒng)計分析,得到霧天高速公路行車特征。其次,在3Dmax中構(gòu)建基本的道路模型,然后在駕駛模擬器平臺中構(gòu)建成實驗所需要的高速公路場景,包括道路場景和駕駛場景,分可變信息板、霧燈及其組合措施場景加載50m、250m、500m的霧天能見度環(huán)境,招募合適的實驗者結(jié)合SMI iView XTM HED眼動儀進行駕駛模擬實驗采集駕駛行為及眼動數(shù)據(jù)。然后,對霧天高速公路行車風險進行評估預測。先運用Fisher最優(yōu)分割方法,選取能見度和車頭時距作為霧天高速公路行車風險評估指標,確定將風險分為4級并結(jié)合可能發(fā)生事故的嚴重程度(損失)得出分級標準;運用有序Logistic回歸對行車風險進行預測,通過能見度和車頭時距值計算出現(xiàn)風險等級的概率。最后,從行車風險及駕駛行為兩方面對措施有效性進行評價。分析發(fā)現(xiàn)采取措施后大部分駕駛員行車風險降低;采用描述統(tǒng)計、方差分析、Logistic回歸方法,分不同測試點進行數(shù)據(jù)分析,結(jié)果發(fā)現(xiàn):在不采取任何措施時,與正常天氣相比較,霧天車輛平均速度均有不同程度下降;在設置可變信息板的測試點,根據(jù)能見度和平均速度通過Logistic回歸建立了減速概率模型,在設置霧燈誘導后,有83.3%的駕駛員最后車輛平穩(wěn)運行的速度會比無霧燈時有不同程度的提高。
[Abstract]:There are a lot of hidden dangers in the driving of foggy days expressway. The relevant departments and scholars have put forward many measures to deal with them. However, there is little research on the effectiveness evaluation of the relevant measures. Based on the analysis of the effectiveness of the two typical measures, variable information board and fog lamp, this paper constructs the freeway scene through driving simulation platform and analyzes the influence of the measures on the driving risk and driver's behavior by combining with the eye movement instrument. To provide reference for relevant managers to take effective early warning measures to improve the safety of freeway vehicles. The research is carried out from the following aspects. Firstly, the fog field investigation is carried out on the Beijing-Zhuhai Expressway and around the City Expressway in Changsha City. The obtained speed and the headway time distance data are statistically analyzed, and the driving characteristics of the foggy days Expressway are obtained. Secondly, the basic road model is built in 3Dmax, and then the freeway scene is constructed in the driving simulator platform, including the road scene and driving scene, and the variable information board is divided into two parts: one is the road scene, the other is the driving scene. The fog lamp and its combined measure scene were loaded with 50 mG 250 mm2 500m fog visibility environment. Suitable experimenters were recruited to carry out driving simulation experiment with SMI iView XTM HED eye movement device to collect driving behavior and eye movement data. Then, the traffic risk of foggy expressway is evaluated and forecasted. Firstly, the Fisher optimal segmentation method is used to select visibility and headway distance as the evaluation index of traffic risk of foggy freeway. The risk is divided into four levels and combined with the severity (loss) of possible accidents, the classification standard is obtained. The traffic risk is predicted by using ordered Logistic regression, and the probability of risk grade is calculated by visibility and head-time distance. Finally, the effectiveness of the measures is evaluated from two aspects: driving risk and driving behavior. The analysis found that most drivers' driving risk was reduced after taking measures, and the data were analyzed by descriptive statistics, ANOVA and Logistic regression method. The results showed that when no measures were taken, the results were compared with the normal weather. At the test point with variable information board, the deceleration probability model was established by Logistic regression according to visibility and average speed. In 83.3% of the drivers, the speed of the final vehicle running smoothly was higher than that without fog lamp.
【學位授予單位】:長沙理工大學
【學位級別】:碩士
【學位授予年份】:2015
【分類號】:U492.8
本文編號:2230739
[Abstract]:There are a lot of hidden dangers in the driving of foggy days expressway. The relevant departments and scholars have put forward many measures to deal with them. However, there is little research on the effectiveness evaluation of the relevant measures. Based on the analysis of the effectiveness of the two typical measures, variable information board and fog lamp, this paper constructs the freeway scene through driving simulation platform and analyzes the influence of the measures on the driving risk and driver's behavior by combining with the eye movement instrument. To provide reference for relevant managers to take effective early warning measures to improve the safety of freeway vehicles. The research is carried out from the following aspects. Firstly, the fog field investigation is carried out on the Beijing-Zhuhai Expressway and around the City Expressway in Changsha City. The obtained speed and the headway time distance data are statistically analyzed, and the driving characteristics of the foggy days Expressway are obtained. Secondly, the basic road model is built in 3Dmax, and then the freeway scene is constructed in the driving simulator platform, including the road scene and driving scene, and the variable information board is divided into two parts: one is the road scene, the other is the driving scene. The fog lamp and its combined measure scene were loaded with 50 mG 250 mm2 500m fog visibility environment. Suitable experimenters were recruited to carry out driving simulation experiment with SMI iView XTM HED eye movement device to collect driving behavior and eye movement data. Then, the traffic risk of foggy expressway is evaluated and forecasted. Firstly, the Fisher optimal segmentation method is used to select visibility and headway distance as the evaluation index of traffic risk of foggy freeway. The risk is divided into four levels and combined with the severity (loss) of possible accidents, the classification standard is obtained. The traffic risk is predicted by using ordered Logistic regression, and the probability of risk grade is calculated by visibility and head-time distance. Finally, the effectiveness of the measures is evaluated from two aspects: driving risk and driving behavior. The analysis found that most drivers' driving risk was reduced after taking measures, and the data were analyzed by descriptive statistics, ANOVA and Logistic regression method. The results showed that when no measures were taken, the results were compared with the normal weather. At the test point with variable information board, the deceleration probability model was established by Logistic regression according to visibility and average speed. In 83.3% of the drivers, the speed of the final vehicle running smoothly was higher than that without fog lamp.
【學位授予單位】:長沙理工大學
【學位級別】:碩士
【學位授予年份】:2015
【分類號】:U492.8
【引證文獻】
相關(guān)碩士學位論文 前1條
1 羅小東;惡劣天氣條件下高速公路路徑誘導策略研究[D];長沙理工大學;2016年
,本文編號:2230739
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