本文選題：信號交叉口 + 闖紅燈��； 參考：《北京交通大學(xué)》2014年博士論文

【摘要】：機(jī)動車與非機(jī)動車的混合交通是當(dāng)前我國城市交通的主要特征,也是造成我國城市交通擁堵和事故頻發(fā)的一個重要原因。非機(jī)動車出行靈活、準(zhǔn)時性高,是解決中短距離出行和接駁換乘的理想交通方式,作為符合我國國情并擁有廣泛群眾基礎(chǔ)的代步工具,在現(xiàn)階段依然具有不可替代性。以前的非機(jī)動車主要指人力自行車,近年來隨著技術(shù)的發(fā)展,電動自行車的使用已越來越普遍。與人力自行車相比,電動自行車可到達(dá)的距離更遠(yuǎn),速度更快,但伴隨的交通隱患也更高,這給我國城市交通帶來了一些新的問題。此外,非機(jī)動車是一種健康、環(huán)保、低能耗的出行方式。發(fā)展城市非機(jī)動車交通是預(yù)防和緩解交通擁堵、減少大氣污染和能源消耗的重要途徑之一,關(guān)系人民群眾的生產(chǎn)生活和城市可持續(xù)發(fā)展。 然而,城市交通中,非機(jī)動車是一個相對弱勢的群體,涉及到非機(jī)動車的交通事故比重一直居高不下。非機(jī)動車交通事故中,闖紅燈違規(guī)是導(dǎo)致事故發(fā)生的主要原因,由于較差的法律約束和人們較低的安全意識,當(dāng)前非機(jī)動車的闖紅燈行為在我國極為普遍。目前,研究信號交叉口非機(jī)動車闖紅燈行為的文獻(xiàn)很少,更鮮有文獻(xiàn)運(yùn)用生存分析方法來分析非機(jī)動車闖紅燈行為。生存分析的優(yōu)點(diǎn)是可以考慮刪失數(shù)據(jù),并能將事件的結(jié)果和出現(xiàn)此結(jié)果所經(jīng)歷的時間結(jié)合起來分析,非常適合用來研究信號交叉口闖紅燈行為。據(jù)此,本論文結(jié)合當(dāng)前我國交通的特點(diǎn),以非機(jī)動車為主要研究對象,基于生存分析方法,重點(diǎn)分析城市干道信號交叉口非機(jī)動車的穿越行為,揭示信號交叉口非機(jī)動車騎行者的違規(guī)風(fēng)險、等待忍耐時間及其關(guān)鍵影響因素,并對特殊的管控措施進(jìn)行評價。具體來講,本論文的主要工作如下： (1)非機(jī)動車穿越行為的實(shí)證調(diào)研。通過選取典型城市干道信號交叉口對非機(jī)動車穿越行為進(jìn)行實(shí)地拍攝,獲取基礎(chǔ)數(shù)據(jù)。分析非機(jī)動車和行人穿越信號交叉口過程中的等待時間分布、等待區(qū)域空間分布、運(yùn)行軌跡、運(yùn)行速度、穿越間隙等,揭示信號交叉口自行車、電動車與行人的微觀行為差異。結(jié)果表明電動車的違規(guī)率明顯高于行人和自行車；來自兩側(cè)非機(jī)動車的違規(guī)率明顯高于直行到達(dá)的；行人不等待直接違規(guī)的比例顯著低于自行車和電動車；違規(guī)者中行人的等待時間明顯比自行車和電動車長,電動車運(yùn)行速度比自行車和行人的快,而穿越的安全界限則比自行車和行人小。 (2)非機(jī)動車騎行者的等待忍耐時間分布規(guī)律。基于實(shí)證調(diào)研數(shù)據(jù),建立信號交叉口非機(jī)動車穿越前的等待忍耐時間持續(xù)模型,對紅燈期間到達(dá)的非機(jī)動車在穿越前的等待忍耐時間進(jìn)行估計,探索不同等待時間下非機(jī)動車闖紅燈違規(guī)率的分布。結(jié)果表明隨著等待時間的增加,非機(jī)動車的違規(guī)概率逐漸增大,18.2%的騎行者幾乎不等待就直接闖紅燈違規(guī)；20.6%的騎行者愿意等待時間120s,甚至更長。并指出對刪失數(shù)據(jù)的不當(dāng)處理會導(dǎo)致明顯高估非機(jī)動車騎行者的闖紅燈違規(guī)率。 (3)非機(jī)動車闖紅燈行為的Cox風(fēng)險模型及其影響因素分析。構(gòu)建非機(jī)動車騎行者等待忍耐時間的Cox風(fēng)險模型,運(yùn)用調(diào)查數(shù)據(jù)對模型參數(shù)進(jìn)行估計,系統(tǒng)地分析各個潛在因素對騎行者的違規(guī)風(fēng)險和等待忍耐時間的影響。結(jié)果表明交通方式、等待位置、高峰期、從眾行為和機(jī)動車流量等對非機(jī)動車闖紅燈行為有顯著影響。電動車騎行者比自行車的違規(guī)風(fēng)險更高,愿意等待的時間更短；等待位置越靠前(靠近路)違規(guī)風(fēng)險越大；平峰期的違規(guī)風(fēng)險大于高峰期；正在違規(guī)的人越多,機(jī)動車流量越小,則非機(jī)動車騎行者越容易違規(guī),等待時間越短。并指出建立的Cox風(fēng)險模型可用來預(yù)測或評估這些交通運(yùn)營、管理和政策的變化對非機(jī)動車闖紅燈行為的影響。 (4)非機(jī)動車通勤者的安全穿越可靠性建模與分析。運(yùn)用可靠性思想和加速風(fēng)險模型理論,結(jié)合非機(jī)動車穿越問題,建立非機(jī)動車通勤者的安全穿越可靠性模型,基于實(shí)證數(shù)據(jù),找出最優(yōu)可靠性模型的數(shù)學(xué)形式,并揭示影響通勤者安全穿越可靠性的關(guān)鍵因子。進(jìn)一步把非機(jī)動車通勤者分為等待者和不等待者兩類,分別探討了他們的安全穿越可靠性問題。結(jié)果表明在各個潛在影響因素中,騎行者的等待位置、來自方向和從眾行為等行為特征因素是影響非機(jī)動車通勤者安全穿越可靠性的最主要因素；Gompertz模型最適合用來擬合非機(jī)動車等待人群的安全穿越可靠性問題。 (5)交通協(xié)管的管控效果評價。通過運(yùn)用Logistic模型、方差分析、協(xié)方差分析和生存分析等方法,比較信號交叉口有無交通協(xié)管時非機(jī)動車的穿越行為特征、闖紅燈違規(guī)率和等待忍耐時間的差異,據(jù)此來評價交通協(xié)管對非機(jī)動車闖紅燈行為的管控效果。結(jié)果表明交通協(xié)管對闖紅燈行為有顯著影響。有協(xié)管時非機(jī)動車和行人的闖紅燈違規(guī)率都顯著低于無協(xié)管的情形,有協(xié)管時的等待忍耐時間則比無協(xié)管時更長；不同來自方向中,交通協(xié)管對直行人群的闖紅燈行為具有很好的管控效果,而對來自左右兩側(cè)人群的管控效果相對較弱。
[Abstract]:The mixed traffic of motor vehicle and non motor vehicle is the main feature of urban traffic in China. It is also an important cause of traffic congestion and frequent accidents in China. Non motor vehicle is flexible and punctual. It is an ideal way to solve short distance travel and transfer. With the development of the technology, the use of electric bicycles has become more and more common in recent years. Compared with the human bicycle, the electric bicycle can reach far distance, faster speed, but the accompanying traffic danger is higher, This has brought some new problems to urban traffic in China. In addition, non motor vehicles are a healthy, environmentally friendly and low energy consumption mode. The development of urban non motor traffic is one of the important ways to prevent and alleviate traffic congestion, reduce air pollution and energy consumption, which is related to the production and life of the people and the sustainable development of the city.
However, in urban traffic, non motor vehicles are a relatively weak group, and the proportion of traffic accidents involving non motor vehicles has always been high. In non motor traffic accidents, violation of red light is the main cause of the accident. Due to poor legal constraints and people's lower safety awareness, the current non motor vehicles break the red light line. It is very common in China. At present, there are few literature to study the behavior of non motor vehicles running red lights at signal intersection. There are few literature to use survival analysis to analyze the behavior of non motor vehicles running red light. The advantage of survival analysis is to consider censored data and to combine the result of the event with the time experienced by this result. According to the characteristics of traffic in our country, this paper takes non motor vehicle as the main research object, and based on the survival analysis method, this paper focuses on the analysis of the non motor vehicle crossing behavior of the signal intersection of the urban trunk road, and reveals the violation risk of the non motor vehicle riders at the signal intersection. Endurance time and its key influencing factors, and evaluation of special control measures.
(1) the empirical investigation of non motor vehicle crossing behavior. Through selecting the typical urban trunk road signal intersection to take the non motor vehicle crossing behavior on the spot, obtain the basic data, analyze the waiting time distribution in the process of the intersection of non motor vehicle and pedestrian crossing signal, wait for the distribution of the space, the running track, the running speed, the crossing gap and so on. The microscopic behavior differences between bicycles at signalized intersections, electric vehicles and pedestrians were revealed. The results showed that the violation rate of electric vehicles was significantly higher than that of pedestrians and bicycles; the violation rate from both sides of non motor vehicles was obviously higher than that of direct traffic; the proportion of pedestrians not waiting for direct violation was significantly lower than that of bicycles and electric vehicles; Compared with bicycles and electric cars, electric vehicles run faster than bicycles and pedestrians, and the safety limits crossing them are smaller than bicycles and pedestrians.
(2) the non motor vehicle riders wait for the time distribution of endurance. Based on the empirical research data, the waiting time model of waiting time for non motor vehicles crossing the signal intersection is established, and the waiting time of waiting time for non motor vehicles arriving at the red light during the crossing is estimated, and the rate of violation of the red light violation rate for non motor vehicles under different waiting time is explored. The results show that the probability of violation of non motor vehicles increases with the increase of waiting time, and 18.2% of the riders hardly wait for the red light violation. 20.6% of the riders are willing to wait for the time 120s or even longer. Regulation rate.
(3) the Cox risk model of the non motor vehicle running red light and its influencing factors. The Cox risk model of the non motor vehicle rider waiting for the time of patience is constructed, the parameters of the model are estimated by the survey data, and the effects of the potential factors on the cyclist's risk of violation and the waiting time are systematically analyzed. The results show the mode of traffic, The waiting position, the peak period, the crowd behavior and the traffic flow of the motor vehicle have a significant influence on the red light behavior of the non motor vehicle. The bicycle rider has a higher risk of infraction than the bicycle and is willing to wait for a shorter time; the longer the waiting position is near the Road, the greater the risk of violation; the risk of violation of the irregularities at the peak period is greater than the peak period; the people who are in violation are violating. The more the less traffic, the smaller the traffic, the easier the non motorist is to violate, the shorter the waiting time. It is pointed out that the Cox risk model can be used to predict or evaluate the effects of these traffic operations, management and policy changes on the behavior of non motor vehicles running red light.
(4) modeling and analysis of safety crossing reliability of non motor vehicle commuters. Using reliability thought and accelerated risk model theory and combining non motor vehicle crossing problems, the safety crossing reliability model of non motor vehicle commuters is established. Based on the empirical data, the mathematical form of the optimal reliability model is found out, and the safety wear of commuters is revealed. The key factor of the more reliability is to further divide the non motor vehicle commuters into two categories: the waiting and the non waiting ones. The problem of their safety crossing reliability is discussed respectively. The results show that the waiting position of the rider, the direction and the herd behavior are the factors affecting the non motor vehicle commuters. The most important factor in the reliability of full traversing is the Gompertz model, which is most suitable for fitting the safety traversing reliability of non motor vehicle waiting crowd.
(5) the evaluation of the control effect of traffic co management. By using Logistic model, variance analysis, covariance analysis and survival analysis, we compare the characteristics of non motor vehicle crossing behavior at the signal intersection without traffic coincident, break the violation rate of the red light and wait for the time of endurance, and evaluate the traffic coordination tube's behavior to the non motor vehicle running red light. The results show that the traffic coordination tube has a significant influence on the behavior of the red light. The violation rate of the red light of non motor vehicles and pedestrians at the time of cobing is significantly lower than that of the non cotube, while the waiting time of the cotube waiting for patience is longer than that without the cotube. Good control effect, but on the left and right sides of the crowd control effect is relatively weak.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：U491.225

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