本文選題：非機動車 + 不安全行為　； 參考：《北京交通大學(xué)》2015年碩士論文

【摘要】：非機動車出行有方便、快捷、環(huán)保等優(yōu)點,故受到各國政府的大力支持,越來越多的人選擇非機動車出行。然而,在城市交通中,非機動車是弱勢群體,涉及非機動車的交通事故越來越多。如何減少非機動車交通事故,提高非機動車出行的安全性已成為全社會關(guān)注的重點問題,研究非機動車的交通安全問題具有十分重要的意義。 自行車和電動車作為兩類不同的出行方式,在行為和安全性能等方面存在顯著差別,很少有文獻對兩種交通方式的安全性進行詳細比較。存在不安全行為時不同車輛之間的碰撞直接導(dǎo)致了事故的發(fā)生,不同危險場景下碰撞風(fēng)險感知的比較在現(xiàn)有文獻中很少涉及。據(jù)此,本文以非機動車為主要研究對象,采用多元logistic模型、因子分析和結(jié)構(gòu)方程模型等方法,探究自行車和電動車的不安全行為及其風(fēng)險感知等問題。具體的研究工作如下： (1)結(jié)合調(diào)查數(shù)據(jù),研究非機動車騎行者在個人屬性、騎行屬性及安全屬性等方面的分布特點,并比較了自行車與電動車的差異。結(jié)果表明已婚、全職、女性的騎行者選擇電動車出行要多于自行車。電動車事故率要明顯高于自行車。兩類車型騎行者在騎行距離、出行目的、事故責(zé)任方等方面也存在一定的差異。在實際管理、使用和政策制定等方面應(yīng)該對兩種車型有所區(qū)別。 (2)研究騎行者對不同交通方式安全性感知,應(yīng)用多元logistic回歸的方法,建立交通方式安全感知模型。結(jié)果發(fā)現(xiàn)有駕照的騎行者認為電動車比自行車安全的概率是無駕照騎行者的4.15倍,認為開車比自行車安全的概率是無駕照者的3.16倍。已婚的騎行者、男性騎行者認為開車和電動車出行比自行車安全；相反,單身的騎行者、女性騎行者則認為自行車出行更安全。此外,年齡、目前所使用的交通工具等因素對交通方式安全性感知也有顯著影響。 (3)研究不同危險情形下碰撞風(fēng)險感知的差異,結(jié)合因子分析結(jié)果建立碰撞風(fēng)險感知結(jié)構(gòu)方程模型。根據(jù)風(fēng)險感知得分分析,與速度較快車輛(小汽車、電動車)發(fā)生碰撞時風(fēng)險感知較高；同樣情形下自己違規(guī)時,碰撞風(fēng)險感知會降低。根據(jù)結(jié)構(gòu)方程模型結(jié)果,不安全行為或不安全傾向增多時,感知碰撞風(fēng)險會下降；主觀規(guī)范提升時,感知碰撞風(fēng)險會相應(yīng)升高。 本文利用SPSS統(tǒng)計分析軟件對調(diào)查數(shù)據(jù)進行分析,研究非機動車的交通安全問題,最后結(jié)合各部分研究結(jié)果,對如何提高非機動車行駛安全性,提出了各種合理有效的建議。
[Abstract]:Non motor vehicle travel has the advantages of convenience, shortcut, environmental protection and so on. Therefore, more and more people choose non motor vehicles to travel. However, in urban traffic, non motor vehicles are vulnerable groups and more and more accidents involving non motor vehicles are involved. Integrity has become a major concern of the whole society. It is of great significance to study the traffic safety problem of non motorized vehicles.
As two different modes of travel, bicycles and electric vehicles have significant differences in behavior and safety performance. Few documents compare the safety of the two modes of traffic in detail. The collision between different vehicles directly leads to the occurrence of accidents when there is unsafe behavior, and the risk perception of collision in different dangerous scenes. The comparison is rarely involved in the existing literature. According to this, this paper takes the non motor vehicle as the main research object, uses the multiple logistic model, the factor analysis and the structural equation model to explore the unsafe behavior and risk perception of the bicycle and the electric vehicle.
(1) according to the survey data, the distribution characteristics of non motor vehicle riders in personal attributes, riding properties and safety attributes are studied, and the differences between bicycles and electric vehicles are compared. The results show that married, full-time and female riders choose to travel more than bicycle. The accident rate of electric vehicles is obviously higher than that of bicycles. Two types of cars are more than bicycles. There are also certain differences in riders' riding distance, travel purposes, and accident liability parties. The two types of models should be different in actual management, use and policy formulation.
(2) to study the safety awareness of riders on different modes of traffic and use the multiple logistic regression method to establish a traffic safety perception model. The results show that a rider with a driver's license is 4.15 times more likely to be safer than a bicycle and that the probability of opening a car is 3.16 times more likely to be safer than a non driver. For married riders, male riders think driving and electric car travel are safer than bicycles; on the contrary, single riders and female riders think bicycles are safer. In addition, age, and current means of transportation have a significant impact on traffic safety.
(3) to study the difference of risk perception in different dangerous situations, and to establish the structural equation model of collision risk perception with the result of factor analysis. According to the risk perception score, the risk perception is higher when the speed vehicle (car, electric vehicle) collides with the risk perception score. In the same case, the collision risk perception will be reduced. As the result of the structural equation model, the perceived collision risk will decrease when the unsafe behavior or insecurity tendency increases, and the perceived collision risk will rise correspondingly when the subjective norm is raised.
In this paper, the SPSS statistical analysis software is used to analyze the survey data and to study the traffic safety of non motor vehicles. Finally, in combination with the results of various parts, this paper puts forward all kinds of reasonable and effective suggestions on how to improve the safety of non motor vehicles.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U491

【參考文獻】

相關(guān)期刊論文 前10條

1 熊輝;邱建棟;;信號交叉口自行車通行能力研究[J];北京理工大學(xué)學(xué)報;2008年02期

2 石臣鵬;;電動自行車交通現(xiàn)狀及對策分析[J];重慶交通大學(xué)學(xué)報(自然科學(xué)版);2008年05期

3 徐良杰,王煒;左轉(zhuǎn)自行車對直行機動車通行的影響分析模型[J];東南大學(xué)學(xué)報(自然科學(xué)版);2005年05期

4 吳兵;;電動自行車交通安全研究[J];江蘇警官學(xué)院學(xué)報;2011年05期

5 丁芝華;;美國的電動自行車安全立法研究[J];中國自行車;2009年09期

6 王培;饒培倫;Gavriel Salvendy;;我國騎車人違規(guī)行為及安全對策[J];工業(yè)工程;2012年03期

7 約翰·普切爾;拉爾夫·比勒;孫苑鑫;;難以抵擋的騎行誘惑:荷蘭、丹麥和德國的自行車交通推廣經(jīng)驗研究[J];國際城市規(guī)劃;2012年05期

8 李志斌;楊晨;王煒;江國俊;;基于出行態(tài)度的自行車通勤出行市場劃分[J];東南大學(xué)學(xué)報(自然科學(xué)版);2012年04期

9 唐洪;;電動自行車的交通安全現(xiàn)狀分析及管理對策[J];湖北警官學(xué)院學(xué)報;2010年03期

10 魏麗英;呂凱;;信號交叉口處自行車交通流的跟馳行為[J];吉林大學(xué)學(xué)報(工學(xué)版);2008年01期

，

本文編號：1776998