Acciphilia on the road: An analysis of severe collisions

Introduction

Although prior studies of road traffic accidents have found between-group differences in risk, little attention has been given to the encounter between drivers involved in severe collisions.

Method

The present study empirically evaluates two different possible causes of "social accidents," which are defined as collisions between two or more drivers where some faulty social interaction might be assumed, and which are the most prevalent cause of road injuries. The analyses use merged Israeli collision records from 1983 to 2004 with data from two national censuses, thus providing an unprecedented empirical basis to study the social foundations of car accidents. The data are used to adjudicate between two alternative hypotheses: the heterogeneity hypothesis (socially different drivers tend to collide) versus the homogeneity hypothesis (socially similar drivers tend to collide).

Results

Multivariate analyses provide preliminary support for the latter hypothesis. Given an accident, there are more collisions among drivers from the same broad educational group, and the factors that influence this correlation are independent of geography. The paper thus leads to the idea that severe collisions reflect a sociological or ecological process that is akin to acciphilia.

Impact on Industry

The preliminary findings suggest that variation between drivers may be preferable to similarity, since apparently there is a greater tendency toward collisions between similar drivers.     

Overview of motorcycling in the United States: a national telephone survey

Objectives

Motorcycle registrations have risen in recent years. Although motorcyclist crash fatalities in 2009 were 16% lower than in 2008, they were double the number of deaths in 1997. The present study examined current motorcyclists’ travel patterns and views of motorcycle helmets and other safety topics.

Methods

Motorcycle drivers were interviewed in a national telephone survey conducted in 2009. A weighted sample of 1,606 motorcyclists resulted from adjusting for the oversampling of those younger than 40 and those in the three states without a motorcycle helmet use law (Illinois, Iowa, New Hampshire). All analyses were based on the weighted sample, which was intended to result in a nationally representative sample of motorcyclists.

Results

About one-quarter of respondents said they did not always wear helmets. Of these respondents, 57% said a law requiring helmet use would persuade them to do so, and 27% said nothing would. Ninety-four percent of respondents in states with universal helmet laws said they always ride helmeted, compared with about half of respondents in other states. About half of all respondents favored these laws. About three-quarters said they believe helmets keep riders safer, including two-thirds of respondents who oppose universal laws and almost half of drivers who rarely/never wear helmets. Drivers ages 18–29 and drivers of sport/unclad sport, sport touring, and super sport motorcycles were more likely to always wear helmets, support universal helmet laws, and believe helmets keep riders safer. About half of respondents said antilock braking systems (ABS) enhance safety and that they would get ABS on their next motorcycle. Less than one-quarter thought an airbag would protect a motorcyclist in a crash, and even fewer would consider getting one on their next motorcycle. Forty-three percent of motorcyclists said they had crashed at least once; 62% of the most recent crashes involved no vehicles besides the motorcycle. Respondents reported riding their motorcycles about 5,400 miles, on average, during the past year. Drivers ages 18–29 reported riding fewer miles, on average, than older drivers and more often rode at night and to/from work or school. Drivers of touring and sport touring motorcycles traveled more miles and took more long trips.

Conclusions

Motorcyclists’ travel patterns and views vary widely, but there are distinct patterns by driver age and motorcycle type. Drivers who believe helmets keep riders safer are more likely to always wear them, but this belief appears insufficient to motivate some drivers to wear them. However, universal helmet laws appear effective in increasing helmet use. Many drivers are receptive to purchasing ABS on their next motorcycle.

Impact on industry

States should be encouraged to enact universal helmet laws, and motorcycle manufacturers should be encouraged to offer ABS.     

Random parameter models for accident prediction on two-lane undivided highways in India

Introduction

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.

Method

The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.

Results

The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.

Conclusions

The paper is concluded with a discussion on modeling results and the limitations of the present study.     

On the development of a new hybrid risk assessment process using occupational accidents’ data: Application on the Greek Public Electric Power Provider

The occupational accidents have a major impact upon human integrity and also bring about high costs for the social health and insurance system of a country. In addition, risk analysis is an essential process for the safety policy of a company, having as main aim the effacement of any potential of damage in a productive procedure, while the quantified risk evaluation is the most crucial part of the whole procedure of assessing hazards in the work. The main goal of this study is double: a) the development and presentation of a new hybrid risk assessment process (HRAP) and b) the application of HRAP in the Greek Public Power Corporation (PPC) (the unique electric power provider and the largest industry in Greece), by using occupational accidents that have been recorded, during the 12-year period of 1993-2004. The new process consists of four distinct phases a) the hazard sources’ identification phase, b) the risk consideration phase, c) the risk-evaluation phase, and d) the phase of the risk assessment and safety-related decision making. The results show that in some cases the risk value has been calculated in PPC to be higher than 500 (in the risk rating of 0-1000), which imposes the taking of suppressive measures for abolishing the danger source, while the fatal accident frequency rate (per 10⁸ man-hrs) is FAFR ≅ 2.4.     

过水性湖泊水质长期演变趋势及驱动因素：以骆马湖为例

过水性湖泊——骆马湖是南水北调东线工程的重要调蓄湖泊,具有防洪抗旱、饮用水供给和生态维护等多种功能.为了解骆马湖水质演变及驱动因素,基于2009～2020年长序列逐月实测数据,结合1996～2008年历史资料,分析了骆马湖总氮(TN)、总磷(TP)、高锰酸盐指数和氨氮(NH⁺₄-N)等指标的长期演变、季节动态和空间格局,探究了气象和水文因子对湖泊水质的影响机制.结果表明,近25年来,骆马湖水质总体处于Ⅳ～劣Ⅴ类.ρ(TN)变化明显(1.06～3.49 mg·L^-1),历经波动下降(1996～2002年)、显著的年际波动(2002～2015年)和显著上升(2015～2020年)这3个阶段,是骆马湖的主要污染因子.高锰酸盐指数显著下降(2.97～6.38 mg·L^-1),ρ(TP)和ρ(NH⁺₄-N)波动相对较小,分别介于0.024～0.076 mg·L^-1和0.11～0.69 mg·L^-1. 2017～2020年夏...     

亚热带城市河流浮游细菌群落的季节演替及构建机制

细菌是河流生态系统的重要组成部分,在污染物降解、物质循环和能量流动等方面扮演着重要角色.然而亚热带城市河流细菌群落的季节演替和构建机制(确定性和随机性过程)仍不明晰.以流溪河及广州珠江段为研究对象,采用16S rRNA高通量测序分析探讨了不同季节(丰水期和枯水期)水体细菌群落的变化及其构建机制.结果表明：不同季节水体细菌群落的组成存在显著差异,丰水期,变形菌门和异常球菌-栖热菌门的丰度更高;而枯水期,拟杆菌门和厚壁菌门的丰度更高.细菌群落的α和β多样性同样具有显著的季节差异,T、NH₄⁺-N、TOC、pH、EC、DO、NO₃^--N和DSi是影响细菌群落季节变化的主要环境因子.水体细菌群落的生态网络具有典型的模块化结构,物种间以正相关作用(合作关系)为主,且丰水期物种间的合作关系强于枯水期.随机性过程主导了细菌群落的构建,尤其以扩散限制贡献最大,且细菌群落在枯水期面临的扩散限制要高于丰水期.     

重庆市O3污染日的大气环流分型与传输特征

通过分析重庆市主城区2015~2019年O₃浓度和气象要素观测数据,发现主城区O₃超标日数、超标日O₃中位值和90百分位浓度值均呈现逐年升高趋势,O₃与温度成正相关、与相对湿度成负相关,高O₃浓度对应每日最高温度区间为35℃以上以及相对湿度区间70%以下.采用T-mode主成分分析法(PCT)对2015~2019年的4~9月850hPa低层位势高度场和风场进行分型,总结出重庆市O₃污染期间主要有8种天气类型,其中有利于出现高浓度O₃现象的天气类型分别是低压西北侧型(T1)、低压后部型(T4)和高压西侧(T3),对应O₃平均超标率分别为34.6%、17.0%和14.2%.利用HYSPLIT4模型后向轨迹聚类方法和潜在源贡献算法(PSCF),计算得到O₃污染日的气团主要以中短距离输送为主,主要传输轨迹来自北、东北、南以及西南四个方向,从2015~2019年,主要污染来源有一个明显的从北转南的趋势,O₃污染的潜在源贡献分析结果与全市工业源NO_x、VOCs排放量空间分布的一致性较高.     

基于GSK-AdaBoost-LightGBM的交通事故死亡人数预测研究

交通事故预测研究有助于降低交通事故发生的概率。为提高交通事故预测模型的精度,首先应用网格搜索法获得LightGBM模型的最优超参数,并进行5折交叉验证提升模型的抗拟合能力,建立优化的LightGBM(GSK-LightGBM)模型;然后基于AdaBoost算法训练多个GSK-LightGBM模型,加权组合得到AdaBoost-LightGBM增强集成模型,并采用网格搜索法结合5折交叉验证,实现了AdaBoost-LightGBM模型的参数优化,构建了GSK-AdaBoost-LightGBM模型;最后基于采集到的1953—2018年我国道路交通事故死亡人数相关样本数据训练模型,得到基于GSK-AdaBoost-LightGBM的交通事故死亡人数预测模型,并引入均方误差、平均绝对误差和平均绝对百分误差3项评估指标评估了模型的预测性能,探究了模型的优化效果。结果表明:GSK-AdaBoost-LightGBM模型的3项评估指标值分别为0.014、0.00035和0.077,低于LightGBM模型、GSK-LightGBM模型和AdaBoost-LightGBM模型的评估指标值,说明该模型的预测精度较高,且明显优于LightGBM模型、GSK-LightGBM模型和AdaBoost-LightGBM模型。     

城市不同类型高架快速路噪声影响

参照《城市快速路设计规程》(CJJ 129—2009)并用Cadna/A软件对3种类型的城市高架快速路进行声场模拟;对高架类型、道路限速、预测点噪声值三者进行方差分析并评判高架类型对预测点噪声值的影响程度。结果表明,高架声影区只对高度低于高架且与高架距离较近的预测点影响较大,地面道路对1~2层预测点的噪声值影响较大;双层分离式在1~8层表现出更强的噪声污染性,噪声最大值出现在第6层附近,单层分离式及整体式产生的噪声最大值所在楼层数随建筑物与高架之间距离的增大而升高,单层分离式对各楼层的噪声污染程度都较小。高架类型、道路限速对噪声值的影响显著,道路交通量的大小可以改变高架类型及道路限速对于预测点噪声的效应量大小。