Improving the safety of distracted pedestrians with in-ground flashing lights. A railway crossing field study

Introduction: Current signage at intersections is designed for attentive pedestrians who are looking ahead. Such signage may not be sufficient when distracted by smartphones. Illuminated in-ground LED lights at crossings are an innovative solution to alert distracted pedestrians. Method: We conducted a field study at a railway crossing equipped with in-ground lights to assess whether distracted pedestrians (N = 34, Mean age 33.6 ± 8.6 years) could detect these lights and how this impacted on their visual scanning and crossing behaviour. This involved a 2 × 3 repeated measures design exploring the impact of the presence (treatment) or absence (control) of in-ground lights (treatment) at a crossing, and a distractor task presented through a mobile device (none, visual, and audio) on eye movements recorded using an eye tracker, and verbal reporting of when participants detected the lights. Results: Participants engaged in the distraction tasks as evidenced by their accuracy and reaction times in all conditions. With both the audio and visual distraction tasks, participants looked at the in-ground LEDs and detected their activation as accurately as when not distracted (95%). While most participants detected the lights at their activation, visual distraction resulted in 10% of the detections occurring as participants entered the rail corridor, suggesting effectiveness in gaining pedestrians’ attention. Further, participants were significantly less likely to check for trains when visually distracted (70%), a 10% reduction compared to the no or audio distractor conditions (80% and 78% respectively). The introduction of the in-ground lights resulted in appropriate scanning of the rail tracks (77% and 78% for the visual and auditory distractor tasks respectively) similar to that of non-distracted participants for the crossing without lights (80%). Conclusions: Our findings indicate that illuminated in-ground lights could be useful in attracting the attention of distracted pedestrians at railway level crossings, and possibly at other road intersections. Practical Applications: Illuminated in-ground lights can be installed at rail and road intersections with known pedestrian distraction as a countermeasure. Further research is necessary to understand their long-term effects.     

基于APRIORI-TAN的交通事故伤害分析与预测*

为探究道路交通事故因素和事故伤害的相关性,以2 467起涉及人员伤亡的交通事故为数据集,运用Apriori算法分别挖掘事故伤害关联规则,并结合社会网络分析的可视化和核心-边缘分析构建受伤事故和死亡事故的关联规则网络。结果表明:事故伤害程度与事故时间、道路条件和交通环境等因素关系紧密,尤其死亡事故与碰撞固定物、人行横道事故、高速公路、高速道路、非市区、酒驾和超速存在高相关性。基于树型贝叶斯网络（TAN）构建事故伤害程度的预测模型,预测结果准确率可达87.56%。     

基于半定量的FRAM道路危险品运输事故分析方法研究*

为弥补事故分析法在道路危险品运输事故致因研究方面的缺失,解决传统事故分析方法分析结果不全面、防控措施不具体且针对性较差的问题,引入半定量功能共振事故模型（FRAM）,通过定量化功能上下游耦合变异性,阐述事故发生机理同时,找到系统关键功能和关键链路,制定防控措施重点监控。结果表明:基于半定量的FRAM道路危险品运输事故分析方法能够更快、更准确地找出事故发生的关键功能和关键链路,制定针对性防控措施,有效提高道路危险品运输系统安全性。研究结果可为道路事故分析提供参考。     

基于ARIMA和XGBoost组合模型的交通事故预测

近年来交通事故及其损失严重影响社会经济的发展和人民生活的提高,交通事故预测可以为交通事故预防提供数据支持。基于自回归滑动平均(ARIMA)模型和极端梯度提升(XGBoost)模型,构建时间序列组合预测模型,对交通事故相关指标进行趋势预测。根据交通事故的特点,选定"事故起数""受伤人数""死亡人数"及"损失"4个指标。首先,根据自相关、偏自相关图确定ARIMA模型参数,根据AIC(赤池信息准则)值确定最终模型;然后,对4个指标的ARIMA模型预测结果的残差构建残差序列,对其进行XGBoost建模,得出修正后的残差预测值;最后,根据残差预测值和ARIMA模型预测值得出组合模型最终的预测值。实例结果表明,4项指标的混合预测模型的预测精度均优于单一的ARIMA模型和Holt-winters模型,其中以"受伤人数"和"死亡人数"的模型改善效果最为显著,"受伤人数"指标的平均绝对百分比误差降低了5.431 7个百分点,"死亡人数"指标的平均绝对百分比误差降低了3.625 9个百分点。     

北京市交通扬尘对大气环境质量的影响

利用中尺度气象模式ARPS与空气质量模式Models-3/CMAQ的耦合模式,模拟2002年4个季节代表月份(1月、4月、8月和10月)北京市PM10浓度的时空分布.与监测数据对比分析表明,该耦合模式有很好的可靠性.设计了2种污染源情景方案,分析了北京市2002年4个季节代表月份交通扬尘对市区大气PM10的影响.结果表明,在4个代表月中,交通扬尘对北京市PM10的逐时贡献率波动较大,最高可达33%,最低为3%;交通扬尘对北京市大气PM10影响显著,4个月平均贡献率分别为16.73%、12.92%、18.56%和18.17%,平均贡献浓度分别为27.61 μg/m3、32.80 μg/m3、25.20 μg/m3和24.40 μg/m3.此外,依据模拟结果,结合交通扬尘污染特征与治理现状,提出了北京市交通扬尘的初步治理方案.     

驾驶员道路安全感评价虚拟现实技术研究

针对公路线形、交通环境与驾驶员的协调性实时检测的定量化评价方法问题,围绕虚拟现实技术和驾驶员道路安全感认知评价,在对210国道西万三级路典型路段建模生成三维模型的基础上,组织53名驾驶人员在虚拟仿真实验室中对虚拟三级路进行现场认知评价试验.采用模糊统计的方法对评价试验得到的795组数据进行分析处理,建立虚拟三级路安全性认知因素的模糊评价隶属函数.采用计算虚拟和实测道路模糊评价隶属函数的贴近度的方法,与基于实际道路的三级路安全性认知因素的模糊评价隶属函数对比,证明虚拟现实技术在驾驶员道路安全感认知评价研究中的可行性.     

Distribution of Platinum group elements in road dust in the Beijing metropolitan area, China

Dust samples collected from the Beijing metropolitan area （China） were evaluated to determine the distribution and the concentration of platinum group elements （PGEs）. The dust particles that were smaller than 100 mesh size fraction （150 μm） were analyzed after aqua regia digestion. Concentrations ofPt, Rh, and Pd were found to be between 3.96 and 356.3 ng/g, 2.76 and 97.11 ng/g, and 0.1 and 124.9 ng/g, respectively, in the urban areas of Beijing, whereas for the background samples collected from the suburbs of Beijing, the concentrations of Pt, Pd, and Rh were very low and ranged from 0.1 to 0.9 ng/g, 0.5 to 1.4 ng/g, and 0.8 to 2.2 rig/g, respectively. The distributions of PGEs in road dust were an accurate reflection of the levels of pollution and were found to match with the local traffic conditions. A strong positive correlation was established among all the dements found in road dust. This suggests that emissions of abraded fragments from vehicle exhausts may be the source of the high concentration of Pt, Rh, and Pd in road dust along the main roads of Beijing.     

行人过街信号控制路口交通噪声动态模拟与特性分析

用实验方法测定了3种不同车型单辆车在参考距离处的噪声排放量及加减速噪声修正值.然后利用微观交通仿真软件为交通噪声的模拟提供实时的交通流数据,并结合车辆噪声排放量和传播衰减模型对行人过街信号控制路口交通噪声进行了动态模拟.最后将模拟结果与实测数据进行了比较分析,结果表明:等效声级Leq的预测误差小于2dB,统计声级L10...     

行人过街设施节能减排效果评价研究及应用

随着环境质量的恶化与资源的耗竭,对城市规划中交通基础设施节能减排效果的评价愈显重要。文章提出了一套行人过街设施节能减排效果评价方法。该方法以能源的消耗量与污染物的排放量为评价指标,建立了行人过街设施节能减排效果评价模型。通过将微观仿真技术(PARAMICS)与机动车综合排放模型(CMEM)结合,构建了微观交通尾气模拟分析平台,获取了动态的污染物排放量与燃油消耗量,实现了节能减排效益的定量预评估。最后,以广州一处人行天桥修建为例进行节能减排效果评价,发现人行天桥的修建将会使天桥附近路段尾气排放综合降低82.6%、油耗降低80%,一年减少经济损失约90万元;将研究结果与天桥建成前后实测数据对比,所得结果趋势一致,这表明文章提出的方法是合理的、有效的。     

北京市典型交通环境空气甲醛污染特征研究

对北京市交通微环境(轿车内)、西三环和增光路等典型道路交通环境以及紫竹院公园非交通环境空气甲醛浓度进行监测分析,解析交通环境空气甲醛污染特征。结果显示:对于交通微环境存在早晚甲醛浓度暴露峰值。典型道路交通环境甲醛浓度明显高于非交通环境甲醛浓度,西三环中路测试甲醛平均浓度为对应时段紫竹院公园环境甲醛浓度的1.7倍。甲醛浓度与道路交通流量有着明显的正相关,不同类型道路甲醛时间分布规律与车流量的时间分布规律一致,呈现早晚峰值。