A Model for Capacity Considering the Interference by Pedestrian Traffic at Signal Intersections

The capacity is impacted badly by pedestrians' violation behavior at signal intersections. In order to quantify the impact,the time-headway and the vehicular speed from start-up to reach the stable saturation flow with and without pedestrian traffic are used as the direct measurements. Using the statistical analysis,the timeheadway of saturation flow is mainly affected by the position of pedestrians and the degree of pedestrians 'influence is classified into four levels. Then the speed-time profile for the vehicular acceleration at each level is fitted by Curve Fitting Software. Based on the effect to the time-headway and acceleration time,the model of capacity influenced by pedestrians is established and the influence is quantified, which enriches the fundamental theory of traffic engineering. The result shows that the vehicular capacity can be decreased by 14%at the worst case( level I). The conclusions obtained in this paper are valuable for better management of the signal intersection.

Transit Bus and Pedestrian Safety Analysis in the Context of Operator Improvements and Traffic Volume Assessment

Pedestrian safety related to public bus transit is an integral part of promoting sustainability especially in the urban setting. This concept has received significant attention within the last decade as transit agencies strive to make their systems more sustainable and safer at the same time. This study examined pedestrian collisions related to public transit buses in Philadelphia over a three-year study period from 2008 to 2011. The objective is to perform a detailed analysis on crash records, which provides the foundation on statistics for bus-pedestrian collision to allow for future studies in modeling work in this field. Results of this research provided insights on bus-pedestrian collisions in terms of bus maneuver, cause of crash, impact point of bus, and relation to hourly traffic volume. A strong correlation was found between traffic volume and bus-pedestrian collision rate in terms of hours of the day. For any given hour, an increase in collision frequency was found if the traffic volume exceeds a threshold of 5% of its average annual daily traffic. This serves as an indicator of locations that pedestrians are vulnerable at. Analyses were conducted to the fullest extent allowable by the limited dataset. This study presents findings that can be future developed and investigated in future studies. Additionally, countermeasures are recommended in each section that presents a critical area to address.

Multi-Stage Pedestrian Crossings and Two-Stage Bicycle Turns: Delay Estimation and Signal Timing Techniques for Limiting Pedestrian and Bicycle Delay

Signalized intersections sometimes involve multistage pedestrian crossings, in which pedestrians cross to one or more islands and then wait there for a signal to continue. When signals are timed without attention to pedestrian progression, pedestrian delay at multistage crossings can be very long. This paper addresses two issues. First, pedestrian delay at multistage crossings is rarely evaluated because there are no tools in the industry for that purpose except microsimulation. We present a numerical method for determining crossing delay with any number of stages and with the possibility of multiple WALK intervals per cycle. The same method can be applied to single stage crossings, to diagonal two-stage crossings where pedestrians may have path choice, and bicycle two-stage turns. This method has been implemented in a freely available online tool. Second, we describe several signal timing techniques for improving pedestrian and bicyclist progression, and thus reducing their delay, through multistage crossings. They include reservice for selected crossing phases, left turn overlaps, having pedestrian phases overlap each other, and bidirectional bicycle crossings which create path options for two-stage turns. Examples show the potential for large reductions in pedestrian delay, often with little or no increase in vehicular delay. In one example, the addition of a short pedestrian overlap phase reduced average pedestrian delay at a 3-stage crossing by 82 s while average vehicular delay increased by only 0.5 s.

Traffic Calming in Historic District Conservation

The Historic Conservation District(HCD) is an important target for urban heritage protection in China. The spatial characteristics of its road system,formed before the appearance of automobile,do not adapt to the car traffic. In the context of very rapid motorization in Chinese cities,the increase in car traffic brings an inevitable trouble for the protection of HCDs. Road widening and pedestrianization are two popular solutions to this problem in current practices; however,both of them may lead to negative consequences. Inspired by the development of Zone 30 in European cities,this paper firstly cleared up first some misunderstandings of the concept of traffic calming,then taking the inner city of Paris as an example,explained how traffic calming measures can be implemented in HCDs and what effects will be generated. Finally,it discussed the possible application of traffic calming measures in HCDs projects in China and pointed out the specific situations of Chinese cities to which the planners should pay more attention.

Spatial Regression Analysis of Pedestrian Crashes Based on Point-of-Interest Data

Pedestrian safety has recently been considered as one of the most serious issues in the research of traffic safety. This study aims at analyzing the spatial correlation between the frequency of pedestrian crashes and various predictor variables based on open source point-of-interest (POI) data which can provide specific land use features and user characteristics. Spatial regression models were developed at Traffic Analysis Zone (TAZ) level using 10,333 pedestrian crash records within the Fifth Ring of Beijing in 2015. Several spatial econometrics approaches were used to examine the spatial autocorrelation in crash count per TAZ, and the spatial heterogeneity was investigated by a geographically weighted regression model. The results showed that spatial error model performed better than other two spatial models and a traditional ordinary least squares model. Specifically, bus stops, hospitals, pharmacies, restaurants, and office buildings had positive impacts on pedestrian crashes, while hotels were negatively associated with the occurrence of pedestrian crashes. In addition, it was proven that there was a significant sign of localization effects for different POIs. Depending on these findings, lots of recommendations and countermeasures can be proposed to better improve the traffic safety for pedestrians.

Safety analysis of pedestrian and roadway dimensional-dividing buildings

The safety performance of pedestrian and roadway dimensional-dividing buildings under seismic excitations are analysed. Considering the large displacement of the isolator bearing during earthquake, the gravity force becomes the dominant forces because of the accumulated permanent deformations in the building, which results in the structure collapse due to lateral instability. A mod- el is established based on an inelastic time history analysis to consider P - z~ effects in multi-degree- of-freedom. A safety criterion of the system is defined. The influence of the stiffness of an independ- ent column is revealed and compared with the influence of the shear force of the independent column to analyze the safety of the structures. Numerical results show that the special structure of pedestrian and roadway dimensional-dividing buildings can reduce the risk of the building in earthquake. The suitable section and height of the independent column greatly affect the building safety.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

基于FP-growth的老年行人交通事故损伤致因研究

为研究老年行人交通事故相关因素及其对损伤程度的影响,以中国交通事故深度调查数据库中2013—2023年710起机动车-老年行人事故为分析对象,利用FP-growth算法挖掘出4类影响因素28个类型变量共5594项关联规则。研究结果表明:行人年龄、碰撞速度、事故时间段及事故地点是影响老年行人事故死亡率的显著因素。特别是,行人年龄和碰撞速度对死亡率有显著影响,随着碰撞速度的增加,死亡率显著上升;60岁及以上老年行人年龄每增加1岁,其死亡率提升0.037倍。此外,事故发生在夜间、郊区或村庄的死亡率更高。研究结果可为提高老年行人交通安全,制定相关安全措施提供一定参考。

双足运动微观视角下单列行人流建模与仿真研究

为从双足运动的微观视角直接呈现行人的移动特性,本文分析行人连续交替步伐行为的运动机理,建立单列行人流迈步运动模型,模拟行人位置在迈步周期内的非线性变化过程。模型根据行人重心和双足中心相对位置,将每次迈步周期内的迈步过程分为单支撑与双支撑阶段,并根据双足瞬时速度具备的波形时序特性,确定迈步周期内任意时刻的位置坐标。基于单列行人流实验数据,标定单列行人流迈步模型中的相关参数,每个行人根据前向距离确定下一次迈步运动所需的步长与步时,并进一步考虑行人的迈步调整行为,避免与前方行人发生踩踏。模拟仿真结果表明:模型能够较好呈现行人迈步运动的微观特性,并复刻了基本图与时空特性;根据行人迈步速度的波形特征,本文基于模拟结果计算步进动力学特性参数,发现行人在面对拥挤空间时,倾向于采用低步长与低步频的迈步风格;模型呈现人群同步自组织现象,发现全局密度为1.9 ped·m^(-1)时,同步现象发生概率最高。行人迈步模型的有效建立,可为行人运动状态评估与预测工作提供参考。

城市道路全要素设计研究——以广州市为例

城市道路设计主要强调机动交通的工程性指标,缺乏对人本需求下的街道要素进行系统分析与梳理,无法满足出行者对高品质街道空间的需求。在对国内外街道设计研究进行总结的基础上,提出城市道路全要素设计技术要点,通过构建人群行为与街道品质的交互规律及其与街道要素间的深层映射关系,实现对城市街道空间的精细化设计与优化。《广州市城市道路全要素设计手册》探索建立了一套人本需求下道路分类—功能模块—全要素匹配的城市道路全要素设计体系,形成7大类23小类道路-街道功能分类体系,并总结9个功能模块的推荐形式、适用范围以及设计要点,梳理街道6大系统90项要素的设计指引。以广州市街道改造实践项目为例,阐述了以人为本理念下街道品质评价、步行和非机动车交通优先设计以及协同一体化设计方法的应用。

基于改进YOLOv7的复杂行人检测系统研究

在智慧交通系统中,行人的安全和便利性同样是重要关注点。针对行人交通场景中由光照、遮挡、目标小以及背景复杂等因素导致的目标检测精度低、易出现漏检和误检问题等情况,提出了一种基于改进YOLOv7的行人目标检测算法。该算法在主干网络中嵌入动态稀疏注意力机制BiFormer,以增强特征提取能力;将三尺度检测头输出改为双检测头输出,以提升模型训练和推理速度;运用迁移学习初始化权重配值方法,以减少模型训练时间。实验结果表明,相比改进前的YOLOv7算法,所提出的改进算法在人员遮挡区和远距离小目标行人检测时具有更高的识别率,满足了复杂行人检测要求。

环岛出口道人车冲突影响因素分析

为有效降低行人与车辆之间冲突的潜在风险,尽可能地避免交通事故的发生,对行人行为特性影响因素与交通冲突之间的联系进行了研究,选取了长春市人民广场处环形交叉口的3个出口道,以交通冲突数据为基础,进行有关行人因素的人车冲突严重程度分析;收集高峰时段的人车冲突数据,选取合适的交通冲突指标,聚类分析得出不同种类交通冲突的阈值以及不同类型人车冲突的严重程度,引入危险度的概念得出小型出口道危险性比大型出口道危险性大的结论;进一步探究行人特性与人车冲突的相关性,发现行人违章率与冲突之间存在正线性关系,行人在即将发生冲突时注视方向由车辆方向到过街方向会大大减少冲突发生。

人车碰撞事故中人地碰撞损伤研究进展

为了解人车碰撞事故中人地碰撞损伤的研究进展,并对可行的人地碰撞损伤防护方法做出展望。本文从人车碰撞事故特征、人体损伤评价指标、人体损伤来源、人地碰撞损伤影响因素及人地碰撞损伤防护方法5个方面回顾了已有研究成果,并对已有研究中存在的问题进行讨论,就人地碰撞防护方法的发展作出展望。人地碰撞损伤研究仍然存在许多不成熟的地方,特别是人地碰撞损伤的致伤机理和影响因素方面仍须开展深入的研究。通过回顾现有的人地碰撞损伤防护技术指出,未来可从优化车辆前部形状、安装行人安全装置以及控制车辆制动等方面来降低行人损伤风险。大部分事故中碰撞速度为中低速,而在低车速下的人地碰撞损伤不容忽视,可通过控制车辆制动降低人地碰撞损伤。此外,人地碰撞损害评价指标仍存在不足。本文可为后续更好地开展人地碰撞损伤致伤机理及防护方法的研究提供参考。

面向交通场景的轻量级行人检测算法

针对交通场景下行人检测模型网络复杂、参数量大以及难以在低性能设备上部署的问题,基于YOLOv5s网络模型提出了一种改进的轻量级行人检测算法。首先,使用Ghost模块重构YOLOv5s网络进行特征提取,降低模型的参数量和计算量,提高推理速度。其次,引入坐标注意力机制提高模型对目标特征的提取能力,提升其对小目标行人的检测效果。最后,采用SIoU损失函数加快模型的收敛速度,提高模型的识别准确率。实验结果表明,改进后的算法能保证较高的检测精度,与原始YOLOv5s算法相比参数量减少47.1%,计算量减少48.7%,提高了交通场景下行人检测的速度且易于部署。

建成环境对交叉口行人事故严重程度异质性影响

为探索建成环境及其他因素对行人事故伤害严重程度的影响,通过建立均值和方差异质性随机参数Logit模型对交叉口行人事故严重程度进行异质性分析。利用行人碰撞事故数据,从行人、驾驶员、车辆、道路、环境、时间、建成环境7个方面筛选出27个影响因素,通过弹性系数分析显著变量对事故严重程度的影响程度。结果表明:地铁站可达性为“存在”是随机参数,车辆状态为“其他”会减小该随机参数的均值,降低交叉口行人事故严重程度;方差与“下午”显著相关,此变量会使随机参数的离散程度增加,分布变宽,随机性增加;不同用地类型与交叉口类型对行人事故严重程度的影响具有显著差异,用地类型为商业区、地铁站的可达性为“存在”时,交叉口行人发生交通事故的概率与伤害严重程度降低;行人有不当行为等因素显著增加了交叉口行人事故严重程度。研究结果为制定交叉口建成环境的优化改善措施提供参考和依据。

基于多源数据的步行者交通安全环境研究——以L市老城核心片区生活性街道为例

本文以L市老城核心片区生活性街道为例,运用统计资料、现场勘测和开源数据集成等方法获取研究数据,提出实验假设并进行论证,旨在探求环境要素对步行者交通安全的影响与具体值域分布特征,为街道优化策略提供相应依据。研究发现,路段长度和出入口密度等形态要素,使用者空间权配和界面变化等空间要素,以及街道功能多样性等功能要素均为生活性街道步行者交通安全风险的重要影响因素。设计策略应注重对车速的控制和对不同类型要素的综合考虑,并尝试提出相应的指标建议,以实现对生活性街道步行安全环境的有效测评。

新能源汽车与行人交通事故严重程度分析

为探究影响新能源汽车与行人交通事故严重程度的诱因,基于英国近4 a发生的1819条新能源汽车与行人交通事故数据,从驾驶员、行人、新能源车辆、道路、时空和环境5个方面选择了19个影响因素作为协变量,并根据数据特征将因变量分为轻伤和严重伤害两类。考虑到数据异质性,首先通过因子分析法与k-means聚类进行聚类分析,然后采用Logistic模型对聚类分析得到的两类集群进一步分析,从预测准确率和协变量共线性指标两个方面确认了模型的适用度。结果表明:基于聚类分析构建的Logistic模型预测准确率均达到80%以上;变道或超车、车龄、支路及环形交叉口、双幅路(有中央分隔带)对事故伤害严重程度有异质性影响;行人年龄大于46岁和夜间行车会明显增加事故严重程度;其中,变道或超车和行人年龄对新能源汽车事故严重程度的影响比传统人-车事故更加显著。

水灾场景下的地铁车站人员疏散效率研究

为提升地铁车站在水淹倒灌情况下的人员疏散效率,制定合理的地铁疏散应急预案,本文基于Anylogic仿真软件,构建了淹水倒灌场景下的地铁站,以杭州地铁金沙湖站为例,研究不同水深情况下的地铁人群疏散效率。结果表明:水深、出入口数量等都能对人员安全疏散效率产生影响,设置导流栏能节省18%以上的疏散时间,当站内水深超过20 cm时,因行人行走速度慢导致疏散时间会超过6 min,无法满足安全疏散要求。

人非混行状态下行人心理边界的影响因素分析

探究人非混行状态下的行人心理边界影响机制,有助于从交通设计、交通管理等维度针对性地提高人非共板道路上行人的出行安全性和舒适性。为克服现有研究仅考虑行人自身人际空间范围期望的不足,根据心理包络理论,从行人期望的安全活动边界(subject mental envelope,SME)和行人期望非机动车的约束活动边界(object mental envelope,OME)2个维度,重构人非混行状态下的行人心理边界。通过引入感知威胁、感知亲密和个人特征,新增优先权作为潜在影响因素,构建人非混行状态下的行人心理边界影响机制模型。采用偏最小二乘法结构方程分析进行模型适配性检验和路径分析,模型的SRMR值为0.035,SME和OME的R2分别为0.728和0.773,表明模型拟合水平可接受,且解释力较强。研究结果表明:感知威胁和感知亲密对OME的影响大于对SME的影响,表明当行人认为非机动车有潜在威胁且不友好时,其更期望能约束非机动车的骑行范围;优先权对OME正向影响程度大于SME,表明当行人认为自己的优先权高于非机动车时,其更期望进一步约束非机动车的活动边界;非机动车交通量仅显著影响OME;OME正向影响SME,表明扩展引入的OME可进一步解释行人对自身安全活动空间的需求;个人特征中性别和身高对SME和OME均有显著影响,而每周平均骑行次数仅显著影响OME。

基于校内混合流的无信号交叉口交通严重性分析

为探究校内交通混合流的无信号交叉口危险性及交通参与者的过街风险,连续采集天津理工大学不同时段的视频数据,分别提取机动车、非机动车和行人三者的流量、位置及后侵占时间(post encroachment time,PET)等信息。区分高低流量时段后,对不同流量时段的各种类型车辆与行人的通行时间、冲突率以及侵占率进行分析,进而对其整体危险性进行排序。结果表明:校内机动车对行人流量及速度的敏感程度要高于其他参与者;平峰期较高峰期而言,整体冲突率大幅减少,但升级为严重冲突的概率有所增加。且校内流量高峰期危险性最大的是电动车,其次是机动车;平峰期危险性最大的是机动车,其次是电动车。