九曲桥行人运动实验与模拟研究

公共场所中的人群疏散是行人疏散动力学研究中的重要内容。基于九曲桥行人运动观测实验对转角区域的行人运动特征进行研究,并利用人员疏散模拟软件Pathfinder模拟了因激励作用所导致的行人速度提高对通行效率的影响。结果表明,由于行人的停留、拍照行为导致转角内区域出现了明显的行人变换走道现象;行人在转角内区域出现的停留、超越行为导致行人速度出现大幅度波动,最低速度约为0.2 m/s,最高速度约为0.7 m/s;与转角后区域相比,行人密度变化对转角内区域的行人速度的影响更小,单位流量的影响更大;由于观测实验中行人停留、拍照等行为的存在,相同密度下转角后区域行人运动速度、单位流量均低于P&M平直通道模型;适当的激励作用有助于减轻行人拥堵,提高通行效率,当行人速度达到较高水平后效果不再显著。     

广州市机动车人行横道让行行为及影响因素分析

为了探索广州市机动车驾驶员人行横道处让行行为的特征与其影响因素,采用实地调查、问卷调查和卡方检验等方法,对广州市3处典型人行横道处进行现场观测,发放并收集434份有效问卷,开展机动车让行率、行人和驾驶员对于让行行为的认知及态度、驾驶员特征因素对让行行为频率的影响等方面的统计分析。研究结果显示,广州市机动车在人行横道处减速或停车让行的比例低于15%;女性驾驶员、年龄较大的驾驶员和受教育程度高的驾驶员更倾向于在人行横道处让行。     

考虑结伴行为的双出口超市元胞自动机模型

为研究结伴行为以及障碍物对疏散过程的影响,建立考虑2人结伴行为的双出口元胞自动机疏散模型.模型在静态场中引入危险度模拟行人路径选择,设置个体和2人结伴疏散人群,研究不同行人密度下二者的疏散过程,比较疏散效率;分析相同密度下不同结伴比例的行人疏散过程,得到最优比例;设置横向、竖向和横竖3种障碍物排列方式,模拟个体疏散和结...     

一种基于社会力的行人-自行车混合疏散模型及模拟研究

当公共安全事件发生时,借助自行车进行疏散是一种重要方式。针对这种情况,开展了行人-自行车混合疏散建模和模拟研究。为了更好量化自行车的超越行为,引入了临时期望运动方向,改变自行车的自驱力,实现对自行车避让超越行为的细致描述;修改了单车模型来更新自行车的运动,建立了一种多层次的自行车运动子模型。将该模型与行人社会力模型相结合,得到一种基于社会力的行人-自行车混合疏散模型“MixSF”。模拟发现,MixSF能够较好地再现混合疏散中的超越行为。在实验条件下,发现个体密度小于0.548人/m2时,自行车占比的增加能加快疏散;相对密度大于0.81时,自行车失去疏散速度优势。     

Simulation of pedestrian contra-flow by multi-agent DEM model with self-evasive action model

A pedestrian contra-flow can be seen frequently in urban spaces such as a pedestrian crossing, an open space and a concourse. A pedestrian simulation with taking a pedestrian contra-flow into account will be a rational tool for designing urban pedestrian facilities. The objective of our research is to develop a microscopic model for a pedestrian contra-flow. Although we have been developing a DEM (Distinct Element Method)-based microscopic model of crowd behavior, this conventional crowd behavior model does not necessarily provide satisfactory agreement with an observation in a pedestrian crossing with heavy commute traffic. In this paper, we newly develop a self-evasive action model, which can describe either a collision avoidance or an alignment behavior between adjacent pedestrians. The multi-agent DEM model with the self-evasive action model shows good predictions of the characteristics of pedestrian contra-flow.     

The effect of overtaking behavior on unidirectional pedestrian flow

We present a model of overtaking behavior that can be used to simulate unidirectional pedestrian flow in routine. All pedestrians have the ability to determine whether or not to overtake other pedestrians according to their desired velocity and position. Although existing models such as cellular automata models, lattice gas models, social force models, etc., can be used to predict evacuation performance, most of these models are either computationally inefficient or do not account for some crucial elements of human behavior in a moving crowd. Furthermore, these models use either empirical equations developed from experiments or mechanical system analogies to determine movement decisions. The pedestrian flow patterns simulated by these models may deviate significantly from reality. In reality, pedestrians walk at different velocities and pedestrians with a higher walking velocity are accustomed to overtaking other pedestrians with a lower walking velocity and this paper aims to mimic this behavior as the original social force model developed by Helbing et al. does not reflect this pattern of collective pedestrian behavior. In this paper, we propose modifications of the social force model that reflects how overtaking behavior operates in routine. The comparison of the pedestrian flow pattern between the original social force model and the modified social force models with the real data collected by the camcorder is also performed in order to demonstrate our modified social force model can be used to achieve reasonable simulations of overtaking behavior among pedestrians.     

A pedestrian's smile and drivers' behavior: When a smile increases careful driving

IntroductionResearch has reported that smiles facilitate social relationships. However, the effect of a smile on driving behavior has received less interest.MethodThis study attempts to evaluate how a pedestrian's smile influences an oncoming driver's behavior. In the first part of our study, male and female research assistants waiting at several pedestrian crossings were asked to smile or not at oncoming drivers.ResultsIt was found that a smile increases the number of drivers who stop. The same effect was observed when the pedestrian tries to cross outside the pedestrian crossing. Finally, this study shows that motorists drive slower after they see a pedestrian smile, suggesting that a smile can induce a positive mood.Practical ApplicationsThis leads to motorists stopping more readily and driving more carefully. These results also suggest that pedestrians may increase their own safety by using appropriate nonverbal signals toward drivers.     

Spillover effects of yield-to-pedestrian channelizing devices

A great number of pedestrians are killed or injured in traffic crashes every year in the US. Vehicle crashes involving pedestrians are often more severe than other crashes because pedestrians are unprotected and are hence more likely to suffer injuries or death if struck by a motor vehicle. To improve pedestrian safety, a variety of treatments such as overhead flashing beacons, in-street crossing signs, in-roadway warning lights, and traffic calming measures have been used. One treatment, in-street yield-to-pedestrian channelizing devices (YTPCD), has been used in many states, including Pennsylvania, where approximately 10% of traffic crash fatalities are pedestrians each year.In an effort to improve pedestrian safety, the Pennsylvania Department of Transportation (PennDOT) has widely deployed YTPCD. This study examines the spillover (indirect) effects of such devices on motorist and pedestrian behavior. With data collected from eight sites that did not have but were in the vicinity of YTPCD implementations, analysis results show that such devices have significantly positive spillover effects on pedestrian safety at intersections, but they tend to have negative spillover effects at mid-block locations. Overall, the YTPCD appear to have a positive impact on changing motorist and pedestrian behavior, and merit consideration for future usage of this type of device.     

How do children learn to cross the street? The process of pedestrian safety training

Objective: Pedestrian injuries are a leading cause of child death and may be reduced by training children to cross streets more safely. Such training is most effective when children receive repeated practice at the complex cognitive–perceptual task of judging moving traffic and selecting safe crossing gaps, but there is limited data on how much practice is required for children to reach adult levels of functioning. Using existing data, we examined how children's pedestrian skills changed over the course of 6 pedestrian safety training sessions, each composed of 45 crossings within a virtual pedestrian environment.

Methods: As part of a randomized controlled trial on pedestrian safety training, 59 children ages 7–8 crossed the street within a semi-immersive virtual pedestrian environment 270 times over a 3-week period (6 sessions of 45 crossings each). Feedback was provided after each crossing, and traffic speed and density were advanced as children's skill improved. Postintervention pedestrian behavior was assessed a week later in the virtual environment and compared to adult behavior with identical traffic patterns.

Results: Over the course of training, children entered traffic gaps more quickly and chose tighter gaps to cross within; their crossing efficiency appeared to increase. By the end of training, some aspects of children's pedestrian behavior was comparable to adult behavior but other aspects were not, indicating that the training was worthwhile but insufficient for most children to achieve adult levels of functioning.

Conclusions: Repeated practice in a simulated pedestrian environment helps children learn aspects of safe and efficient pedestrian behavior. Six twice-weekly training sessions of 45 crossings each were insufficient for children to reach adult pedestrian functioning, however, and future research should continue to study the trajectory and quantity of child pedestrian safety training needed for children to become competent pedestrians.     

行人违章过街行为心理成因分析及预测

为深入了解行人在交叉口违章过街行为,调查影响行人在长周期信号控制交叉口违章过街的心理成因,采用计划行为理论(TPB)制作了行人违章过街心理行为问卷。利用此问卷,对上海居民进行过街违章心理研究,得到250个覆盖各年龄层的有效样本。信度效度分析验证了行人违章过街心理行为问卷能够用来解析行人的违章过街心理成因。在对问卷中自述违章过街行为和心理要素的聚类分析筛除明显隐瞒自身违章过街行为的行人后,对心理要素和现实行为违章行为进行判别分析。结果表明:问卷中2个TPB的心理要素:知觉行为控制和行为意向能够用来推测行人的实际违章行为,准确率为73.9%。其中,代表行人对交叉口交通情况和自身时间约束的心理要素知觉行为控制对行人违章行为有关键的影响。     

生化恐怖袭击情境下引导疏散中行人行为仿真研究

恐怖袭击事件发生在人员密集、环境复杂的公共场所时,极易造成大量的人员伤 亡。为了研究行人行为特征对应急引导过程的影响,采集疏散行人行为特征数据以SPSS 统计软件分析,并将分析结果导入基于社会力原理建立的疏散模型进行仿真实验。研究 结果表明:行人的性别、受教育程度及疏散经验个体特征的差异对引导疏散的结果具有 直接的影响,关系到引导疏散过程的成功与否。应急管理方案制定中,应针对性的为各 类行人指定安全预案以及提供培训演练。     

考虑儿童运动特性的小学教学楼楼梯间人员疏散研究

为研究小学教学楼楼梯间人员运动行为以及影响人员疏散的因素，开展人员疏散实验并构建疏散模拟场景。基于疏散实验研究不同实验场景的出口流量和人员运动速度，通过疏散仿真模拟，分析不同人员运动速度、人员数量及疏散策略对疏散的影响。结果表明:排队下楼的人员运动速度比紧急疏散人员低22.7%，自由上楼人员运动速度比排队上楼人员高8%；人员总疏散时间随人员运动速度的增加而降低，但总疏散时间随速度增加而降低的幅度变小；加入分层疏散策略会增加人群疏散总时间，但整个疏散过程人员分布均匀，在建筑瓶颈不易产生人员过度拥挤现象，因而在疏散过程中应适当采用分层疏散策略。     

信号控制交叉口行人过街等待时间研究

为保护行人过街时的安全及减少行人违章行为,通过分析行人过街的等待规律,构建了信号控制行人过街等待的生存分析方法。对上海市典型交叉口的行人过街等待行为的观测及分析,得到了行人等待的生存曲线,建立了行人违章危险度随行人自身及环境因素影响的COX风险回归模型。结果表明:行人在路边等待过街最大可忍受等待时间为90s,在中间安全岛的最大可忍受等待时间仅为50s;行人等待时间与行人年龄、红灯时间、穿越车道数、冲突方向车流量、是否二次过街相关,与行人性别无关;合理的交叉口设计和信号控制能提高行人的遵章率、降低违章危险度。笔者建议:信号控制交叉口行人红灯时间不超过90s,行人在安全岛最大等待时间不超过50s。     

不同入口位置的行人进入流实验研究

为了研究行人进入流运动规律,寻找合理的入口位置,对不同入口位置(中间、右侧)进行了不同人数(10人、20人、30人、40人)的可控实验。分析了行人进入流的时间、速度和空间分布,并统计了空间分布影响因素——入口避让、边界吸引、分布角度和空间关系的规律。结果表明,入口位于中间的设计更好,进入时间和稳定时间较短,速度更快,空间分布更合理。这些影响因素的统计,也为行人进入流的模型建立提供了实验基础。     

行人过街空间违章行为特性及安全影响分析*

为探究提前右转车道处不同因素与人车冲突的相关性,以及行人空间违章对过街安全的影响。采集2 062个行人及人车冲突的样本数据,获取行人和机动车的时空信息,对比分析不同类型行人过街轨迹的特征;综合考虑人车冲突时间和速度指标构建人车冲突严重度指标,从行人生理特征、车流条件、道路环境等方面选取8个因素作为自变量,构建人车冲突严重度的多元有序Logistic模型。研究结果表明:空间违章过街的行人平均过街速度和速度离散程度都明显高于其他行人;年龄、车速、人行横道长度、车辆到达率以及过街轨迹类型都是影响人车冲突严重程度的重要因素。各类型空间违章行为使严重冲突占比均提升75%以上。研究结果有助于交管部门采取措施保障行人过街安全。     

某地下商场紧急情况下人员疏散实验研究

地下商场紧急情况下人员疏散过程非常复杂,受到众多因素的影响,如人员自身因素、环境因素等。通过设计并实施人员疏散实验,同时对实验参与人员开展问卷调查,分析了地下商场紧急情况下人员疏散特性及借用相邻防火分区防火门作为安全出口对疏散过程的影响;从疏散演习实验过程中人员出口选择、疏散时间及出口流率、疏散行为等三方面内容对实验结果进行了分析和讨论。     

考虑行为特征的人群疏散模拟研究*

为研究聚集活动中的行人在移动过程中所表现出的行为特征对人群整体移动过程的影响,通过实验观察与计算机仿真模拟的方法对人员移动进行研究。通过对实验视频的观察分析,在CTM模型基础上建立考虑人员跟随行为与保持距离行为特性的移动模型,并在简单无障碍和复杂多障碍的场景进行仿真实验。结果表明:模型能有效地描述行人的运动特征,而且拥挤程度和行人间排斥作用越大时行人移动越慢,整个疏散过程花费时间越长;障碍物的存在会影响人群在出口处的“成拱现象”,对理解人员的运动规律和防止拥挤踩踏事故具有一定理论和现实意义。     

乘客登机离港情景下的首都机场T3航站楼行人流特征

为了解决机场类公众聚集场所乘客群体行为及其控制的难点问题,以首都机场T3航站楼作为仿真对象,利用MassMotion软件,对T3航站楼内部行人交通组织与登机离港服务关键情景进行仿真模拟,揭示了在工作日和假期情景下,首都机场T3航站楼进站与登机离港时行人流特征。研究结果,首都机场T3航站楼行人流量与密度在水平通道处呈二元函数关系,速度与密度的关系相比密度与流量的关系更为复杂,密度适中时,两者呈线性关系;密度较大,行人拥挤时,呈对数关系;密度较小时,呈指数关系。因此,科学预测节假日高峰期行人流平均密度是机场类公众聚集场所风险控制的关键措施。     

Children’s fear in traffic and its association with pedestrian decisions

Introduction: Research on risk for child pedestrian injury risk focuses primarily on cognitive risk factors, but emotional states such as fear may also be relevant to injury risk. The current study examined children's perception of fear in various traffic situations and the relationship between fear perception and pedestrian decisions. Method: 150 children aged 6–12-years old made pedestrian decisions using a table-top road model. Their perceived fear in the pedestrian context was assessed. Results: Children reported greater emotional fear when they faced quicker traffic, shorter distances from approaching traffic, and red rather than green traffic signals. Children who were more fearful made safer pedestrian decisions in more challenging traffic situations. However, when the least risky traffic situation was presented, fear was associated with more errors in children’s pedestrian decisions: fearful children failed to cross the street when they could have done so safely. Perception of fear did not vary by child age, although safe pedestrian decisions were more common among the older children. Conclusions: Children’s emotional fear may predict risk-taking in traffic. When traffic situations are challenging to cross within, fear may appropriately create safer decisions. However, when the traffic situation is less risky, feelings of fear could lead to excessive caution and inefficiency. Practical applications: Child pedestrian safety interventions may benefit by incorporating activities that introduce realistic fear of traffic risks into broader safety lessons.     

汽车行人碰撞接触中行人运动学规律仿真研究

基于交通事故模拟分析PC-Crash软件及其内嵌多体系统动力学分析MADYMO模块,建立并验证了车辆多体模型和行人多体模型;对汽车与行人碰撞接触阶段的行人运动学具有较大影响的因素展开广泛分析,并构建汽车行人碰撞仿真试验方案;通过选取对汽车与行人碰撞接触阶段具有较大影响的因素作为仿真试验的自变量,对不同碰撞环境下汽车与行人碰撞接触过程中的行人运动学规律(包括运动姿态和对应的碰撞车速阈值)进行深入研究;汽车行人碰撞仿真与真实事故以及碰撞试验对比具有较好的规律吻合性和一致性。研究表明,笔者采用的计算机建模仿真方法在汽车行人碰撞运动学研究中具有实用价值。