虛擬現(xiàn)實駕駛仿真環(huán)境下的駕駛分心研究
本文選題:交通安全 切入點:視覺分心 出處:《北方工業(yè)大學》2017年碩士論文
【摘要】:調(diào)研數(shù)據(jù)顯示,駕駛分心是引發(fā)交通事故的主要原因之一。隨著車載智能設備的增加和日益復雜的交通狀況,占用了駕駛員越來越多的注意力資源,容易引發(fā)駕駛分心現(xiàn)象,從而導致駕駛員感知、決策能力降低,甚至造成駕駛失誤等一系列不安全駕駛行為,因此駕駛分心已經(jīng)成為交通安全領域重要研究問題。本文根據(jù)人眼瞳孔的變化特征與自主神經(jīng)相互關系的醫(yī)學基礎,利用眼動測量法記錄駕駛員眼動信息,選定眼睛本身指標—瞳孔直徑進行視覺分心和認知分心的識別方法研究.首先,在對國內(nèi)外研究成果廣泛調(diào)研基礎上,開展了預實驗和預處理。課題從駕駛員眼動角度開展研究,確定研究內(nèi)容和思路。通過預實驗選擇了合適的實驗被試、有效的研究指標和適宜的環(huán)境,為正式實驗的開做鋪墊。原始數(shù)據(jù)的處理過程分為兩步,第一步剔除兩眼瞳孔直徑絕對差值大于閾值的數(shù)據(jù),第二步利用滑動標準差查找異常數(shù)據(jù),結(jié)合線性插值法對異常數(shù)據(jù)進行修復,并取得了較好的處理效果。其次,課題設計了視覺分心實驗方案,通過設置標識牌使被試發(fā)生駕駛狀態(tài)改變,每位實驗被試根據(jù)提示先后進行跟馳駕駛、超車駕駛和視覺分心駕駛。實驗結(jié)束后提取三種駕駛狀態(tài)下瞳孔直徑信息,利用方差分析從數(shù)值上進行視覺分心識別方法研究,均方根分析和遞歸圖分析分別從能量和圖像上可進行視覺分心狀態(tài)的觀測。接下來利用車道中心偏離距離進行駕駛安全性分析,發(fā)現(xiàn)視覺分心狀態(tài)下存在駕駛安全問題。最后,課題設計了認知分心實驗方案,通過詢問計算題的方式使被試發(fā)生認知分心,并利用包絡分析觀測認知分心水平變化。結(jié)果表明,認知分心過程中瞳孔直徑逐漸升高,并隨著認知分心結(jié)束而回歸正常水平。隨后對認知分心狀態(tài)進行駕駛安全性分析,選用方向盤旋轉(zhuǎn)率指標,通過與正常駕駛狀態(tài)進行對比,發(fā)現(xiàn)認知分心狀態(tài)下方向盤旋轉(zhuǎn)率變化平緩,表明此時橫向駕駛績效降低。
[Abstract]:Research data show that driving distraction is one of the main causes of traffic accidents.With the increase of vehicle intelligent devices and the increasingly complex traffic conditions, drivers are occupying more and more attention resources, which can easily lead to driving distractions, thus leading to the driver's perception and decision-making ability.Even causes a series of unsafe driving behavior such as driving error, so driving distraction has become an important research problem in the field of traffic safety.Based on the medical basis of the relationship between the characteristics of eye pupil change and autonomic nerve, the eye movement information of driver was recorded by eye movement measurement method, and the visual distraction and cognitive distraction were studied by selecting the index of eye itself-pupil diameter.Firstly, on the basis of extensive research results at home and abroad, pre-experiment and pre-treatment were carried out.The research is carried out from the angle of driver's eye movement, and the research content and train of thought are determined.The suitable experimental subjects were selected by pre-experiment, the effective research index and the suitable environment were selected, which paved the way for the formal experiment.The process of processing the original data is divided into two steps. The first step is to eliminate the data whose absolute difference of pupil diameter is greater than the threshold. The second step is to search the abnormal data by sliding standard deviation, and to repair the abnormal data with linear interpolation method.Good results have been obtained.Secondly, a visual distraction experiment scheme is designed, which changes the driving state of the subjects by setting up a signboard. Each subject carries on following driving, overtaking driving and visual distracted driving according to the prompts.At the end of the experiment, the information of pupil diameter in three driving states was extracted, the visual distraction recognition method was studied numerically by variance analysis, and the visual distraction state could be observed from energy and image by root mean square analysis and recursive graph analysis, respectively.Then the driving safety analysis is carried out by using the driveway center deviation distance, and it is found that there are driving safety problems in visual distraction.Finally, a cognitive distraction experiment scheme was designed, in which cognitive distraction was induced by asking and calculating questions, and the change of cognitive distraction level was observed by envelope analysis.The results showed that the pupil diameter increased gradually during cognitive distraction and returned to normal level with the end of cognitive distraction.Then the driving safety of cognitive distraction state was analyzed and the steering wheel rotation rate index was selected. By comparing with the normal driving state, it was found that the steering wheel rotation rate changed slowly under cognitive distraction state, which indicated that the lateral driving performance decreased.
【學位授予單位】:北方工業(yè)大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:U491.25;TP391.9
【參考文獻】
相關期刊論文 前10條
1 張貴滿;朱守林;戚春華;;單調(diào)路側(cè)景觀色彩對駕駛員眼動指標的影響分析[J];科學技術與工程;2016年18期
2 馬艷麗;顧高峰;高月娥;馬勇;;基于駕駛績效的車載信息系統(tǒng)操作分心判定模型[J];中國公路學報;2016年04期
3 胡英奎;陳仲林;張青文;翁季;黃珂;;駕車接近隧道過程中駕駛員瞳孔大小變化規(guī)律[J];土木建筑與環(huán)境工程;2015年06期
4 馬勇;石涌泉;付銳;郭應時;;駕駛?cè)朔中臅r長對車道偏離影響的實車試驗[J];吉林大學學報(工學版);2015年04期
5 韓向方;李曉杰;;道路交通事故分析及交通安全對策[J];中國地質(zhì)大學學報(社會科學版);2013年S1期
6 王暢;郭應時;付銳;袁偉;宋殿明;;視線離開前方區(qū)域時的駕駛?cè)瞬僮餍袨閇J];重慶交通大學學報(自然科學版);2014年03期
7 馬勇;付銳;王暢;郭應時;袁偉;宋殿明;;視覺分心時駕駛?cè)俗⒁曅袨樘匦苑治鯷J];中國安全科學學報;2013年05期
8 寧世發(fā);馮忠祥;;道路交通事故成因分析[J];交通標準化;2006年10期
9 徐高平,余翔,薛麗霞,凌寧;人眼不同瞳孔直徑波前像差特性分析[J];光電工程;2005年07期
10 趙中利;駕駛員交通肇事行為原因及預防[J];濟南交通高等?茖W校學報;1996年S1期
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