The effect on accidents of technical inspections of heavy vehicles in Norway

This paper presents a study of the effects on accidents of technical inspections of heavy vehicles (trucks and buses) in Norway. Multiple regression analysis is applied in order to estimate the effects of technical inspections, controlling for annual trend in accident rate, the number of new drivers and annual economic growth. It is found that abolishing inspections may result in an increase of 5–10% in the number of heavy vehicles involved in injury accidents; increasing the number of inspections by 100% is associated with a similar reduction in the number of accidents. These results are not statistically significant and highly uncertain. The study clearly illustrates many of the difficulties often encountered in non-experimental accident research.     

The influence of the infrastructure characteristics in urban road accidents occurrence

This paper summarizes the result of a study regarding the creation of tools that can be used in intervention methods in the planning and management of urban road networks in Portugal.     

The evaluation of effects on driver behavior and accidents of concentrated general enforcement on interurban roads in Israel

The study deals with the evaluation of the effects of a new deployment of the National Traffic Police in Israel--a concentrated general enforcement on 700 km of interurban roads, which contain 60% of all rural accidents and about half of the severe accident locations. The enforcement project began in April 1997 and lasted for 1 year, aiming at a 10% reduction of severe accidents on those roads. The evaluation study consisted of three main parts: (a) monitoring of everyday police operations on the project roads; (b) periodic evaluation of the project's influence on drivers' behavior and attitudes; and (c) the evaluation of accident changes within the project area, at the end of the project year. Speed measurements, performed before the police project launch, demonstrated that, depending on road type, up to 85% of drivers violated the rural road speed limits. Two rounds of field observations, before and during the project, took place at 32 sites throughout the project area and comprised eight behavior types: turning performance; signaling while turning; compliance with 'stop' and 'yield' signs; safety belt use by drivers and front-seat passengers, at the intersections; 'keeping to the right' on dual carriageway roads; and 'not-crossing of the white separating line' at single carriageway roads. A comparison revealed a general reduction in violation rates of most behaviors, during-the-project, except for compliance with 'stop' signs and signaling. Concurrently, two rounds of driver surveys were performed which examined the project's influence on the drivers' attitudes towards the police enforcement effectiveness and risk connected with traffic rule violations. An improvement was identified in perceived general level of police activity, during the project, whereas a lower or similar risk of apprehension was attributed by drivers to most specific violations of the traffic rules. Three groups of indices of police activity were estimated monthly during the study: inputs; outputs; and efficiency indices, which characterized the police presence on the project roads, the citations produced and the usage rates of the vehicle fleet and the enforcement tools. Analyzing these indices, two periods in the project performance were determined, and three criteria were proposed to subdivide the project roads into two groups, according to the level of enforcement intensity. Both periods and enforcement levels, as well as geographic zone, were accounted for in the analysis of accident trends on the project roads. For the accident analysis, a statistical model combining the odds ratio and longitudinal methods, was developed and applied to the severe accident counts, all injury accidents and severe casualties. A statistically significant reduction in severe accidents and severe casualties, as opposed to the comparison group, was found on the highly enforced roads in the center of the country. At the same time, since the police project began, an increase in accidents was observed on most interurban roads, including the northern parts of the project area. However, it was noted that in four of the five project road groups the mean value of the odds ratio was much less than one. Thus, although the enforcement project did not attain its full purpose, it seemed to be a deterrent factor for the increasing accident trend that appeared that year on the interurban roads. The findings pointed out that the National Traffic Police did not exhaust its potential in the project's performance and needs more flexible enforcement and deployment tactics.     

Risk factors affecting the severity of single vehicle traffic accidents in Hong Kong

A population-based case-control study was conducted to examine factors affecting the severity of single vehicle traffic accidents in Hong Kong. In particular, single vehicle accident data of three major vehicle types, namely private vehicles, goods vehicles and motorcycles, which contributed to over 80% of all single vehicle accidents during the 2-year-period 1999-2000, were considered. Data were obtained from the newly implemented traffic accident data system (TRADS), which was developed jointly by the Transport Department, Police Force and Information Technology Services Department, Hong Kong. The effect of district, human, vehicle, safety, environmental and site factors on injury severity of an accident was examined. Unique risk factors associated with each of the vehicle types were identified by means of stepwise logistic regression models. For private vehicles, district board, gender of driver, age of vehicle, time of the accident and street light conditions are significant factors determining injury severity. For goods vehicles, seat-belt usage and weekday occurrence are the only two significant factors associated with injury severity. For motorcycles, age of vehicle, weekday and time of the accident were determined to be important factors affecting the injury severity. Identification of potential risk factors pertinent to the particular vehicle type has important implications to relevant official organisations in modifying safety measures in order to reduce the occurrence of severe traffic accidents, which would help to promote a safe road environment.     

The impact of mental health symptoms on heavy goods vehicle drivers’ performance

High levels of psychological distress in fulltime employees are prevalent (4.5% per month). Symptoms of impaired mental health include difficulties with attention, concentration, motivation, decision-making, visuo-motor control, and psychomotor reaction times. There is limited research on the impact these symptoms have on heavy goods vehicle (HGV) drivers’ performance. In this study 1324 HGV drivers were surveyed using the Depression, Anxiety, Stress Scale (DASS) and the Health and Performance at Work Questionnaire (HPQ). Depression, anxiety and stress had little effect on driver absenteeism rates or self-rated driving performance. However, severe (1.5% of drivers) and very severe (1.8% of drivers) depression was associated with an increased odds ratio (OR = 4.5 and 5.0, respectively) for being involved in an accident or near miss in the past 28 days. This odd ratio is akin to driving with a blood alcohol content of about 0.08%. Given the number of HGV vehicles and the prevalence of depression this equates to 10,950 HGV drivers with an increased statistical risk of an accident or near miss. As the impact of HGV accidents is potentially large, including loss of life, it would be sensible to extend the research findings here into an action plan.     

Traffic safety assessment and development of predictive models for accidents on rural roads in Egypt

This paper starts by presenting a conceptualization of indicators, criteria and accidents' causes that can be used to describe traffic safety. The paper provides an assessment of traffic safety conditions for rural roads in Egypt. This is done through a three-step procedure. First, deaths per million vehicle kilometers are obtained and compared for Egypt, three other Arab countries and six of the G-7 countries. Egypt stands as having a significantly high rate of deaths per 100 million vehicle kilometers. This is followed by compiling available traffic and accident data for five main rural roads in Egypt over a 10-year period (1990-1999). These are used to compute and compare 13 traffic safety indicators for these roads. The third step for assessing traffic safety for rural roads in Egypt is concerned with presenting a detailed analysis of accident causes. The paper moves on to develop a number of statistical models that can be used in the prediction of the expected number of accidents, injuries, fatalities and casualties on the rural roads in Egypt. Time series data of traffic and accidents, over a 10 years period for the considered roads, is utilized in the calibration of these predictive models. Several functional forms are explored and tested in the calibration process. Before proceeding to the development of these models three ANOVA statistical tests are conducted to establish whether there are any significant differences in the data used for models' calibration as a result of differences among the considered five roads.     

The impact of traffic violations on the estimated cost of traffic accidents with victims

We analyse accidents with victims and calculate the influence of traffic violations on the probability of having a serious or fatal accident, compared to a slight accident. Traffic violations related to speed limitations, administrative infringements or faults related to the driver are considered. Data were obtained from all available reports on accidents with victims that occurred in Spain from 2003 to 2005. A multinomial logistic regression model is specified to find the probability that an accident with victims is slight, serious or fatal, given the presence/absence of thirty different types of traffic violations. The average cost per victim and the average number of victims per accident are then used to find the estimated cost of an accident with victims, given the information on the traffic violations incurred. This demonstrates which combinations of traffic violations lead to higher estimated average costs, compared to cases in which no traffic violation occurred. We conclude with some recommendations on the severity of penalties, and suggest that regulators penalize the occurrences of some specific combinations of traffic violations more rigorously.     

The experiences and perceptions of heavy vehicle drivers and train drivers of dangers at railway level crossings

Heavy vehicle–train collisions have the potential to be catastrophic in terms of fatalities, environmental disaster, delays in the rail network, and extensive damage to property. Heavy vehicles, such as ‘Road Trains’ and ‘B-Doubles’, are vulnerable road users due to their size and mass and require specific risk management solutions. The present study aimed to capture the experiences of heavy vehicle drivers and train drivers at road–rail level crossings, with a view to exploring the contributing factors toward such accidents. A series of semi-structured focus groups was conducted, with a total of 17 train drivers and 26 heavy vehicle drivers taking part. Though there were some differences between the groups in perceptions of the causes of heavy vehicle-level crossing incidents, discussion in both groups centred on design issues and behavioural issues. With regard to design, the configuration of level crossings was found to affect heavy vehicle driver visibility and effective vehicle clearance. With regard to behaviour, discussion centred around wilful violation of crossing protocols, often as a time-saving measure, as well as driver complacency due to high levels of familiarity. The implications of these factors for future level crossing safety initiatives are discussed.     

The effects of vehicle model and driver behavior on risk

We study the dependence of risk on vehicle type and especially on vehicle model. Here, risk is measured by the number of driver fatalities per year per million vehicles registered. We analyze both the risk to the drivers of each vehicle model and the risk the vehicle model imposes on drivers of other vehicles with which it crashes. The "combined risk" associated with each vehicle model is simply the sum of the risk-to-drivers in all kinds of crashes and the risk-to-drivers-of-other-vehicles in two-vehicle crashes. We find that most car models are as safe to their drivers as most sport utility vehicles (SUVs); the increased risk of a rollover in a SUV roughly balances the higher risk for cars that collide with SUVs and pickup trucks. We find that SUVs and to a greater extent pickup trucks, impose much greater risks than cars on drivers of other vehicles; and these risks increase with increasing pickup size. The higher aggressivity of SUVs and pickups makes their combined risk higher than that of almost all cars. Effects of light truck design on their risk are revealed by the analysis of specific models: new unibody (or "crossover") SUVs appear, in preliminary analysis, to have much lower risks than the most popular truck-based SUVs. Much has been made in the past about the high risk of low-mass cars in certain kinds of collisions. We find there are other plausible explanations for this pattern of risk, which suggests that mass may not be fundamental to safety. While not conclusive, this is potentially important because improvement in fuel economy is a major goal for designers of new vehicles. We find that accounting for the most risky drivers, young males and the elderly, does not change our general results. Similarly, we find with California data that the high risk of rural driving and the high level of rural driving by pickups does not increase the risk-to-drivers of pickups relative to that for cars. However, other more subtle differences in drivers and the driving environment by vehicle type may affect our results.     

基于汉信码的快批行业防伪系统设计与研究

本文通过分析汉信码技术和研究快消产品在生产、流通、消费、监管方面的特点,提出一套基于汉信码技术的快批行业防伪系统,并重点介绍了汉信码的数据格式设计及防伪系统的架构。通过系统的设计与应用,快批企业可以较好的提高防伪能力。     

Dynamic compositional modeling of pedestrian crash counts on urban roads in Connecticut

Uncovering the temporal trend in crash counts provides a good understanding of the context for pedestrian safety. With a rareness of pedestrian crashes it is impossible to investigate monthly temporal effects with an individual segment/intersection level data, thus the time dependence should be derived from the aggregated level data. Most previous studies have used annual data to investigate the differences in pedestrian crashes between different regions or countries in a given year, and/or to look at time trends of fatal pedestrian injuries annually. Use of annual data unfortunately does not provide sufficient information on patterns in time trends or seasonal effects. This paper describes statistical methods uncovering patterns in monthly pedestrian crashes aggregated on urban roads in Connecticut from January 1995 to December 2009. We investigate the temporal behavior of injury severity levels, including fatal (K), severe injury (A), evident minor injury (B), and non-evident possible injury and property damage only (C and O), as proportions of all pedestrian crashes in each month, taking into consideration effects of time trend, seasonal variations and VMT (vehicle miles traveled). This type of dependent multivariate data is characterized by positive components which sum to one, and occurs in several applications in science and engineering. We describe a dynamic framework with vector autoregressions (VAR) for modeling and predicting compositional time series. Combining these predictions with predictions from a univariate statistical model for total crash counts will then enable us to predict pedestrian crash counts with the different injury severity levels. We compare these predictions with those obtained from fitting separate univariate models to time series of crash counts at each injury severity level. We also show that the dynamic models perform better than the corresponding static models. We implement the Integrated Nested Laplace Approximation (INLA) approach to enable fast Bayesian posterior computation.     

The influence of heavy metals on the polymorphs of dicalcium silicate in the belite-rich clinkers produced from electroplating sludge

The purpose of this study is to utilize an electroplating sludge for belite-rich clinker production and to observe the influence of heavy metals on the polymorphs of dicalcium silicate (C₂S). Belite-rich clinkers prepared with 0.5–2% of NiO, ZnO, CuO, and Cr₂O₃ were used to investigate the individual effects of the heavy metals in question. The Reference Intensity Ratio (RIR) method was employed to determine the weight fractions of γ-C₂S and β-C₂S in the clinkers, and their microstructures were examined by the transmission electron microscopy (TEM). The results showed that nickel, zinc, and chromium have positive effects on β-C₂S stabilization (Cr³⁺ > Ni²⁺ > Zn²⁺), whereas copper has a negative effect. The addition of up to 10% electroplating sludge did not have any negative influence on the formation of C₂S. It was observed that γ-C₂S decreased while β-C₂S increased with a rise in the addition of the electroplating sludge. Moreover, nickel and chromium mainly contributed to stabilizing β-C₂S in the belite-rich clinkers produced from the electroplating sludge.     

Motorcycles entering from access points and merging with traffic on primary roads in Malaysia: Behavioral and road environment influence on the occurrence of traffic conflicts

This paper uses data from an observational study, conducted at access points in straight sections of primary roads in Malaysia in 2012, to investigate the effects of motorcyclists’ behavior and road environment attributes on the occurrence of serious traffic conflicts involving motorcyclists entering primary roads via access points. In order to handle the unobserved heterogeneity in the small sample data size, this study applies mixed effects logistic regression with multilevel bootstrapping. Two statistically significant models (Model 2 and Model 3) are produced, with 2 levels of random effect parameters, i.e. motorcyclists’ attributes and behavior at Level 1, and road environment attributes at Level 2. Among all the road environment attributes tested, the traffic volume and the speed limit are found to be statistically significant, only contributing to 26–29% of the variations affecting the traffic conflict outcome. The implication is that 71–74% of the unmeasured or undescribed attributes and behavior of motorcyclists still have an importance in predicting the outcome: a serious traffic conflict. As for the fixed effect parameters, both models show that the risk of motorcyclists being involved in a serious traffic conflict is 2–4 times more likely if they accept a shorter gap to a single approaching vehicle (time lag <4 s) and in between two vehicles (time gap <4 s) when entering the primary road from the access point. A road environment factor, such as a narrow lane (seen in Model 2), and a behavioral factor, such as stopping at the stop line (seen in Model 3), also influence the occurrence of a serious traffic conflict compared to those entering into a wider lane road and without stopping at the stop line, respectively. A discussion of the possible reasons for this seemingly strange result, including a recommendation for further research, concludes the paper.     

Modelling the effects of land use and temporal factors on child pedestrian casualties

This study investigates the suitability of land use variables in predicting the number of child pedestrian casualties; a subject of concern in Great Britain despite sustained improvements in road safety over the past decade. The relationship between land use and transport is used to establish a link between land use and child pedestrian travel; trip attractors and generators are considered as variables that lead child pedestrians to exposure to high risk environments. Casualty records for Newcastle upon Tyne are analysed to reveal trends of temporal variation of child pedestrian casualty numbers. Land use data is combined with the casualty data using GIS techniques to generate relevant inputs for the analysis. Six Generalized Linear Models (GLMs) are developed to analyse the association of child pedestrian casualty numbers and trip attractor land use types. Two are the main models; the first investigates all types of casualty data including slight, serious and fatal events and the second uses only KSI (Killed or Seriously Injured) data in the analysis. The other four models are developed to investigate the temporal variation of child pedestrian KSI and slight casualties over the day (school time and non-school time) and week (weekday and weekend). The results show that secondary retail and high density residential land use types are associated with all child pedestrian casualties. In addition, educational sites, junction density, primary retail and low density residential land use types are also associated with child casualties at different time periods of the day and week. The study findings are found to concur with the current child road safety policies in Great Britain and will, in fact, provide some guidance for local authorities to deliver successful child road safety audits.     

The impact of autonomous vehicle technologies on product recall risk

Complex Advanced Driving Assistance Systems (ADAS) and Autonomous Vehicle (AV) technology are increasing the number of vehicle recalls. At the same time, financial risks resulting from extensive product recall events can severely affect vehicle manufacturers and their suppliers, exposing the automotive supply chain to business continuity, legal and reputational risk. However, these risk implications are under-appreciated by large segments of the supply chain. This study shows that product recall events are increasing in general but recall events associated with ADAS/AV technology form an increasingly large percentage of these recall events. Based on this analysis, we describe ADAS/AV-specific aspects of risk mitigation and present a multidimensional approach, combining production-centric risk mitigation avenues in the automotive supply chain with the transfer of residual financial risks via insurance. We find that this comprehensive risk mitigation approach benefits in higher transparency of total production costs and increased resilience of the automotive supply chain. Against the background of an increasing product recall risk resulting from the increasing automation and interconnectedness of modern vehicles, we therefore suggest a closer, more strategic cooperation between insurance companies, car manufacturers and automotive suppliers for the benefit of all parties.     

Framing the approval to test self-driving cars on public roads. The effect of safety and competitiveness on citizens' agreement

Regulating self-driving cars poses a dilemma for policy-makers. Early testing of self-driving cars on public roads is necessary to accumulate data and driving experience. While approval procedures with high safety standards could harm manufacturers' ability to innovate by delaying tests, low safety standards could put human lives at risk. This study presents an issue framing experiment that directly addresses how citizens evaluate the alleged trade-off between safety and economic competitiveness. The experiment was conducted on representative online samples of citizens in the USA, Japan, and Germany. Results show that citizens' agreement to pilot self-driving cars on public roads is significantly higher in a safety frame, even if safety is explicitly associated with a loss in competitiveness. Socio-demographic characteristics and technology attitudes affect citizens' agreement to pilot self-driving cars primarily in a competitiveness frame, while political attitudes have no impact. Finally, the results show few country differences, indicating room to harmonize self-driving cars' safety regulations internationally.     

EPMA/EDS在交通事故油漆物证检验中的应用

利用EPMA/EDS检测交通事故油漆物证。列举2案例,其结果为公安交警部门办案提供科学依据。     

The influence of vehicle damage on injury severity of drivers in head-on motor vehicle crashes

Data from crashes investigated through the Crash Injury Research and Engineering Network (CIREN) Program were used to assess differences in injury patterns, severity, and sources for drivers, protected by safety belts and deploying steering wheel air bags, in head-on frontal impacts. We studied whether exterior vehicle damage with a different distribution (wide vs. narrow) across the front vehicle plane influenced injury characteristics. Drivers from both impact types were similar on the basis of demographic characteristics (except age), restraint use, and vehicle characteristics. There were significant differences in the type of object contacted and intrusion into the passenger compartment at the driver's seat location. The mean delta V (based on the kilometers per hour change in velocity during the impact) was similar for drivers in both (wide vs. narrow) impact types. There were no significant differences in injury patterns and sources except that drivers in wide impacts were almost 4 times more likely (odds ratio (OR)=3.81, 95% confidence limits (CL) 1.26, 11.5) to have an abbreviated injury scale (AIS) 3 serious or greater severity head injury. Adjusted odds ratios showed that drivers in wide impacts were less likely (OR=0.54, 95% CI 0.37, 0.79) to have severe injury (based on injury severity score (ISS)>25) when controlling for intrusion, vehicle body type, vehicle curb weight, age, proper safety belt use, and delta V. Drivers with intrusion into their position or who were driving a passenger vehicle were almost twice more likely to have severe injury, regardless of whether the frontal plane damage distribution was wide or narrow. Our study supports that the type of damage distribution across the frontal plane may be an important crash characteristic to consider when studying drivers injured in head-on motor vehicle crashes.     

The influence of vehicle front-end design on pedestrian ground impact

Accident data have shown that in pedestrian accidents with high-fronted vehicles (SUVs and vans) the risk of pedestrian head injuries from the contact with the ground is higher than with low-fronted vehicles (passenger cars). However, the reasons for this remain poorly understood. This paper addresses this question using multibody modelling to investigate the influence of vehicle front height and shape in pedestrian accidents on the mechanism of impact with the ground and on head ground impact speed. To this end, a set of 648 pedestrian/vehicle crash simulations was carried out using the MADYMO multibody simulation software. Impacts were simulated with six vehicle types at three impact speeds (20, 30, 40 km/h) and three pedestrian types (50th % male, 5th % female, and 6-year-old child) at six different initial stance configurations, stationary and walking at 1.4 m/s.     

The social accident: a theoretical model and a research agenda for studying the influence of social and cultural characteristics on motor vehicle accidents

The paper develops a sociological model to explain collisions between two drivers or more. The "Social Accident" model presented here integrates empirical findings from prior studies and extant sociological theories. Sociological theory posits that social groups have unique cultural characteristics, which include a distinctive world view and ways of operating that influence its members. These cultural characteristics may cause drivers in different groups to interpret a given situation differently; therefore, they will make conflicting decisions that may possibly lead to road accidents. The proposed model may contribute to an understanding of the social mechanism related to interactions and communication among drivers by presenting new directions for understanding accidents and collisions. The paper concludes with suggestions for future research that will employ the model to assess its predictive and practical utility.