A multinomial logit model of motorcycle crash severity at Australian intersections

Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006–2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.     

A study of fatal pedestrian crashes at rural low-volume road intersections in southwest China

Objective: Although intersections correspond to a small proportion of the entire roadway system, they account for a disproportionally high number of fatal pedestrian crashes, especially on rural roads situated in low- and middle-income countries. This article examines pedestrian safety at rural intersections and suggests applicable accident prevention treatments by providing an in-depth analysis of 28 fatal pedestrian crashes from 8 low-volume roads in southwest China.

Methods: The driving reliability and error analysis method (DREAM) is a method to support a systematic classification of accident causation information and to facilitate aggregation of that information into patterns of contributing factors. This is the first time that DREAM was used to analyze pedestrian–vehicle crashes and provide suggestions for road improvements in China.

Results: The key issues adversely affecting pedestrian safety can be organized in 4 distinctive thematic categories, namely, deficient intersection safety infrastructure, lack of pedestrian safety education, inadequate driver training, and insufficient traffic law enforcement. Given that resources for traffic safety investments in rural areas are limited, it is determined that the potential countermeasures should focus on low-cost, easily implementable, and long-lasting measures increasing the visibility and predictability of pedestrian movement and reducing speeding and irresponsible driving among drivers and risk-taking behaviors among pedestrians.

Conclusions: Accident prevention treatments are suggested based on their suitability for rural areas in southwest China. These countermeasures include introducing better access management and traffic calming treatments, providing more opportunities for pedestrian education, and enhancing the quality of driver training and traffic law enforcement.     

The role of built environment on pedestrian crash frequency

This study investigates (i) the link of land use and road design on pedestrian safety and (ii) the effect of the level of spatial aggregation on the frequency of pedestrian accidents. For this purpose, pedestrian accident frequency models were developed for New York City based on an extensive dataset collected from different sources over a period of 5 years. The assembled dataset provides a rich source of variables (land-use, demographics, transit supply, road network and travel characteristics) and two different crash frequency outcomes: total and fatal-only collision counts. Among other things, it was observed that the census tract analysis (disaggregate data) provides more insightful and consistent results than the analysis at the zip code level. The results indicate that tracts with greater fraction of industrial, commercial, and open land use types have greater likelihood for crashes while tracts with a greater fraction of residential land use have significantly lower likelihood of pedestrian crashes. Moreover, census tracts that have a greater number of schools and transit stops - which are determinants of pedestrian activity - are more likely to have greater crashes. Results also show that the likelihood of pedestrian-vehicle collision increases with the number of lanes and road width. This suggests that retrofitting or narrowing the roads could possibly reduce the risk of pedestrian crashes.     

考虑驾驶员反应时间的车辆碰撞预警模型

为了保证车辆在行驶过程中的安全性,提出了一种考虑驾驶员反应时间的车辆碰撞预警模型,改进了传统模型中驾驶员反应时间定值化的缺点。首先,依据车辆的制动过程分析了驾驶员反应时间对制动距离的影响。其次,设计驾驶员反应时间的模糊推理算法,选取驾龄、疲劳强度和应变能力3个主要因素作为评价指标来计算反应时间。最后,采用分等级的预警策略建立考虑驾驶员反应时间的碰撞预警模型,并通过Carsim-Matlab/Simulink联合仿真与传统模型进行对比分析。结果表明,设计的预警模型可以对不同类型的驾驶员进行差异化碰撞预警,在30 km/h和80 km/h两种车速下实际停车距离与理论值的最大误差为8%。     

基于同时仪表进近的航空器在特情下的碰撞风险模型研究

同时仪表进近模式可有效提高平行跑道的容量,但发生特情时会造成极为严重的后果,因此研究在特殊情况下基于同时仪表进近模式的航空器碰撞风险具有重要意义。首先,与首都机场进近管制员沟通,总结了4种可能会发生的特情,其次,建立基于位置误差概率的同时仪表进近模式下的航空器在特殊情况下的碰撞风险模型,模型最关键的位置误差和速度参数根据采集的实际运行航空器航迹的ADS-B数据得到,其他参数为国际民航推荐值或本地区一线管制员的经验值,然后运用MATLAB软件进行仿真,得出发生特情时每个时刻的碰撞风险,从而得出整个过程碰撞风险的变化趋势。     

Risk factors affecting crash injury severity for different groups of e-bike riders: A classification tree-based logistic regression model

IntroductionAs a convenient and affordable means of transportation, the e-bike is widely used by different age rider groups and for different travel purposes. The underlying reasons for e-bike riders suffering from severe injury may be different in each case.MethodThis study aims to examine the underlying risk factors of severe injury for different groups of e-bike riders by using a combined method, integration of a classification tree and a logistic regression model. Three-year of e-bike crashes occurring in Hunan province are extracted, and risk factor including rider’s attribute, opponent vehicle and driver’s attribute, improper behaviors of riders and drivers, road, and environment characteristics are considered for this analysis.ResultsE-bike riders are segmented into five groups based on the classification tree analysis, and the group of non-occupational riders aged over 55 in urban regions is associated with the highest likelihood of severe injury among the five groups. The logistics analysis for each group shows that several risk factors such as high-speed roads have commonly significant effects on injury severity for different groups; while major factors only have significant effects for specific groups.Practical applicationBased on model results, policy implications to alleviate the crash injury for different e-bike riders groups are recommended, which mainly include enhanced education and enforcement for e-bike risky behaviors, and traffic engineering to regulate the use of e-bikes on high speed roads.     

Older driver crash rates in relation to type and quantity of travel

It is a well-established phenomenon that, notwithstanding their overall good crash record, older drivers have a higher than average rate of involvement in injury crashes when the rate is calculated by dividing crash numbers by distance driven. It has been hypothesised that at least some of this higher crash rate is an artefact of the different nature of driving undertaken by many older drivers. For example, driving in congested urban environments provides more opportunities for collisions than driving the same distance on a motorway. However, there have been few opportunities to investigate this theory, as relevant data are difficult to acquire. High-quality data from the New Zealand Travel Survey (1997/1998) were combined with crash data to enable a statistical model to estimate the risk of driver groups under various driving conditions characterised by the type of road used, time of day, day of week, and season of year. Despite elevated crash risks per distance driven compared with middle-aged drivers for most road types, older drivers were as safe as any other age group when driving on motorways. Accounting for the fragility of older drivers and their passengers in the risk estimates for other road types, older drivers appeared to have daytime risks comparable to 25-year-olds and night-time risks as low as any other age group. The driving patterns of older drivers (in terms of when and where they drive) were estimated to minimize their risks in comparison with the driving patterns of other age groups. These results are of interest to both policy makers and transportation planners working against the background of inevitable increases in the number of older drivers as the population ages.     

An estimate of the effectiveness of an in-vehicle automatic collision notification system in reducing road crash fatalities in South Australia

Objectives: The aim of this study was to estimate the potential effectiveness of an in-vehicle automatic collision notification (ACN) system in reducing all road crash fatalities in South Australia (SA).

Methods: For the years 2008 to 2009, traffic accident reporting system (TARS) data, emergency medical services (EMS) road crash dispatch data, and coroner's reports were matched and examined. This was done to initially determine the extent to which there were differences between the reported time of a fatal road crash in the mass crash data and the time EMS were notified and dispatched. In the subset of fatal crashes where there was a delay, injuries detailed by a forensic pathologist in individual coroner's reports were examined to determine the likelihood of survival had there not been a delay in emergency medical assistance.

Results: In 25% (N = 53) of fatalities in SA in the period 2008 to 2009, there was a delay in the notification of the crash event, and hence dispatch of EMS, that exceeded 10 min. In the 2-year crash period, 5 people were likely to have survived through more prompt crash notification enabling quicker emergency medical assistance. Additionally, 3 people potentially would have survived if surgical intervention (or emergency medical assistance to sustain life until surgery) occurred more promptly.

Conclusions: The minimum effectiveness rate of an ACN system in SA with full deployment is likely to be in the range of 2.4 to 3.8% of all road crash fatalities involving all vehicle types and all vulnerable road users (pedestrians, cyclists, and motorcyclists) from 2008 to 2009. Considering only passenger vehicle occupants, the benefit is likely to be 2.6 to 4.6%. These fatality reductions could only have been achieved through earlier notification of each crash and their location to enable a quicker medical response. This might be achievable through a fully deployed in-vehicle ACN system.     

A framework for estimating the safety effects of roadway lighting at intersections

National- and state-level guidance documents conclusively state that fixed lighting improves intersection safety. The sentiment is consistent with other design and safety manuals and is supported by a series of consistent safety findings; however, most published lighting-safety research is focused on rural, stop-controlled intersections and is limited by several methodological issues. The relationship between safety and intersection lighting at rural, signalized and urban locations is not as well documented. Methodological advancements in highway safety analysis justify new estimations of the safety effects of intersection lighting. This paper describes a proposed framework to estimate the safety effects of fixed lighting at a variety of intersection types and locations. Several key issues are explored including availability of relevant crash, lighting, and roadway inventory data; relevant data element structures; proposed analysis taxonomies to assess lighting-safety effects within and across different intersection classifications; specification and estimation of models to estimate expected crash frequencies during day and night; techniques to interpret model parameters, including variable elasticity; and tests of model transferability across states. A sample framework execution using Minnesota intersection data is provided. Results indicate a much lower overall safety benefit from lighting than published studies, but are consistent with estimates included in Highway Safety Manual research.     

A semi-automated tool for identifying agricultural roadway crashes in crash narratives

Objective: Crash reports contain precoded structured data fields and a crash narrative that can be a source of rich information not included in the structured data. The narrative can be useful for identifying vulnerable roadway users, such as agricultural workers. However, using the narratives often requires manual reviews that are time consuming and costly. The objective of this research was to develop a simple and relatively inexpensive, semi-automated tool for screening crash narratives and expediting the process of identifying crashes with specific characteristics, such as agricultural crashes.

Methods: Crash records for Louisiana from 2010 to 2015 were obtained from the Louisiana Department of Transportation (LaDOTD). Records with narratives were extracted and stratified by vehicle type. The majority of analyses focused on a vehicle type of farm equipment (Type T). Two keyword lists, an inclusion list and an exclusion list, were created based on the published literature, subject-matter experts, and findings from a pilot project. Next, a semi-automated tool was developed in Microsoft Excel to identify agricultural crashes. Lastly, the tool’s performance was assessed using a gold standard set of agricultural narratives identified through manual review.

Results: The tool reduced the search space (e.g., number of narratives that need manual review) for narratives requiring manual review from 6.7 to 59.4% depending on the research question. Sensitivity was high, with 96.1% of agricultural crash narratives being correctly classified. Of the gold standard agricultural narratives, 58.3% included an equipment keyword and 72.8% included a farm equipment brand.

Conclusion: This article provides information on how crash narratives can supplement structured crash data. It also provides an easy-to-implement method to facilitate incorporating narratives into safety research along with keyword lists for identifying agricultural crashes.     

The impact of traffic barrier geometric features on crash frequency and injury severity of non-interstate highways

Introduction: The main objective of this research is to investigate the effect of traffic barrier geometric characteristics on crashes that occurred on non-interstate roads. Method: For this purpose, height, side-slope rate, post-spacing, and lateral offset of about 137 miles of traffic barriers were collected on non-interstate (state, federal aid primary, federal aid secondary, and federal aid urban) highways in Wyoming. In addition, crash reports recorded between 2008 and 2017 were added to the traffic barrier dataset. The safety performance of traffic barriers with regards to their geometric features was analyzed in terms of crash frequency and crash severity using random-parameters negative binomial, and random-parameters ordered logit models, respectively. Results: From the results, box beam barriers with a height of 27–29 inches were less likely to be associated with injury and fatal injury crashes compared to other barrier types. On the other hand, the likelihood of a severe injury crash was found to be higher for box beam barriers with a height taller than 31 inches. Both W-beam and box beam barriers with a post-spacing between 6.1 and 6.3 inches reduced the probability of severe injury crashes. In terms of the crash frequency, flare traffic barriers had a lower crash frequency compared to parallel traffic barriers. Non-interstate roads without longitudinal rumble strips were associated with a higher rate of traffic barrier crashes.     

Responsibility of drivers, by age and gender, for motor-vehicle crash deaths

Problem: Motor-vehicle crash rate comparisons by age and gender usually are based on the extent to which drivers in a particular age/gender category are themselves injured or involved in crashes (e.g., the number of 20-year-old females in crashes). Basing comparisons instead on the extent to which drivers in various age/gender groups are responsible for deaths (including themselves) in their crashes is more revealing of their overall contribution to the problem. Methods: Data from the Fatality Analysis Reporting System (FARS, 1996–2000) were used in the analysis, which was based on crashes that involved one or two vehicles only. Drivers in fatal single-vehicle crashes were assumed to have responsibility for the crash. In fatal two-vehicle crashes, driver operator errors reported by police were used to assign crash responsibility. Results: When all crashes were considered, both the youngest and oldest drivers were most likely to be responsible for deaths in their crashes. In two-vehicle crashes, the oldest drivers were more likely than young drivers to be responsible. Young males were more likely than young females to be responsible for crash deaths, whereas females in their 50s and older were more likely than same-age males to be responsible. In terms of responsibility for deaths per licensed driver, young drivers, especially males, had the highest rates because of their high involvement rates and high responsibility rates. The majority of deaths for which young drivers were responsible occurred to people other than themselves, especially passengers in their vehicles, whereas the bulk of the deaths for which older drivers were responsible were their own. Discussion: The results highlight the contribution of young drivers to the motor-vehicle crash problem, the need for measures such as passenger restrictions in graduated licensing systems, and the need for vehicle modifications to better protect older occupants.     

CALAX: A collision taxonomy for research and traffic records

This article describes a collision taxonomy that has three main advantages. First, its coding reliability was established; coders independently coding the same cases achieved 96% agreement. Second, it has a hierarchical structure, enabling the user to choose one of three levels of detail; there are 46 collision types at the most detailed level. Third, it captures the role of the individual vehicle, a valuable feature for suggesting the driver problems involved in an accident. The taxonomy was developed after reviewing other systems and incorporates some of their better features. It uses schematic diagrams to facilitate ease of learning and use, and it was developed for use by researchers and for traffic record systems. The value of the taxonomy for suggesting driver problems in accidents was demonstrated with data indicating alcohol impairment and age effects.     

Micro-level safety risk assessment model for a two-lane heterogeneous traffic environment in a developing country: A comparative crash probability modeling approach

Introduction: There have been a number of studies that have led to the development of safety risk assessment models to quantify the probability of crash frequencies on roadway facilities (both at micro- and macro-levels), over a specified time period. However, past research has rarely focused on heterogeneous traffic conditions in developing countries. Method: This paper puts forward several models related to the traditional count approach to estimate crash frequency at a micro-level in a non-lane based bi-directional heterogeneous traffic environment. The paper shows the results of dispersion, zero-inflation, and random heterogeneity effects of different exogenous factors by comparing Poisson (P); Negative Binomial (NB); random and fixed parameter Zero-Inflated Poisson (ZIP); and Latent Class Models (LCM). The empirical analysis is based on data from a section of a major national highway in Bangladesh. The performance of the models was validated using different statistical goodness-of-fit measures that compared the estimated and observed average crash frequencies at individual locations. With the identification of the most significant influencing factors, the paper discusses the practical policy implications using partial effects analysis and spatial distribution. Results: It was found that the Zero-Inflated Random Parameter model gives a slightly better statistical fit when compared to alternative approaches. Practical applications: This micro-level modeling approach would be useful to identify significant crash risk factors; to prioritize road sections according to their safety level; to select site-specific appropriate counter-measures; and devise proactive target oriented safety management strategies. Thus, the results shown here could be a point of reference in the planning, designing, maintaining, and managing two-lane highway sections in developing countries.     

基于航空器高度保持性能的风险碰撞模型优化*

为提高Reich风险碰撞模型在“缩小垂直间隔”(Reduced Vertical Separation Minimum,RVSM)标准实施后的适用性。基于同一机型航空器的测高系统误差（Altimetry System Error,ASE）数据在超高空各高度层中并不服从相同分布且具有显著的统计学差异,针对现有的Reich模型对同一机型仍使用整个航空空域的ASE数值进行经验分布拟合的现状,对模型中ASE混合累积经验分布参数部分进行改进,添加高度层相关的参数,使原有仅根据机型进行累积的ASE经验分布细化为根据机型和高度层2部分进行累积。结果表明:改进后模型可准确体现ASE数据在不同高度层的差异性;采用改进的风险模型进行仿真计算,得到更加精确的结果;验证改进后模型的合理性和其在应用中的有效性。     

Modeling crash severity by considering risk indicators of driver and roadway: A Bayesian network approach

Introduction: Traffic crashes could result in severe outcomes such as injuries and deaths. Thus, understanding factors associated with crash severity is of practical importance. Few studies have deeply examined how prior violation and crash experience of drivers and roadways are associated with crash severity. Method: In this study, a set of risk indicators of road users and roadways were developed based on their prior violation and crash records (e.g., cumulative crash frequency of a roadway), in order to reflect certain aspect or degree of their driving risk. To explore the impacts of those indicators on crash severity and complex interactions among all contributing factors, a Bayesian network approach was developed, based on citywide crash data collected in Kunshan, China from 2016 to 2018. A variable selection procedure based on Information Value (IV) was developed to identify significant variables, and the Bayesian network was employed to explicitly explore statistical associations between crash severity and significant variables. Results: In terms of balanced accuracy and AUCs, the proposed approach performed reasonably well. Bayesian modeling results indicated that the prior crash/violation experiences of road users and roadways were very important risk indicators. For example, migrant workers tend to have high injury risk due to their dangerous violation behaviors, such as retrograding, red-light running, and right-of-way violation. Furthermore, results showed that certain variable combinations had enhanced impacts on severity outcome than single variables. For example, when a migrant worker and a non-motorized vehicle are involved in a crash happening on a local road with high cumulative violation frequency in the previous year, the probability for drivers suffering serious injury or fatality is much higher than that caused by any single factor. Practical applications: The proposed methodology and modeling results provide insights for developing effective countermeasures to reduce crash severity and improve traffic system safety performance.     

Comparative analysis of zonal systems for macro-level crash modeling

IntroductionMacro-level traffic safety analysis has been undertaken at different spatial configurations. However, clear guidelines for the appropriate zonal system selection for safety analysis are unavailable. In this study, a comparative analysis was conducted to determine the optimal zonal system for macroscopic crash modeling considering census tracts (CTs), state-wide traffic analysis zones (STAZs), and a newly developed traffic-related zone system labeled traffic analysis districts (TADs).MethodPoisson lognormal models for three crash types (i.e., total, severe, and non-motorized mode crashes) are developed based on the three zonal systems without and with consideration of spatial autocorrelation. The study proposes a method to compare the modeling performance of the three types of geographic units at different spatial configurations through a grid based framework. Specifically, the study region is partitioned to grids of various sizes and the model prediction accuracy of the various macro models is considered within these grids of various sizes.ResultsThese model comparison results for all crash types indicated that the models based on TADs consistently offer a better performance compared to the others. Besides, the models considering spatial autocorrelation outperform the ones that do not consider it.ConclusionsBased on the modeling results and motivation for developing the different zonal systems, it is recommended using CTs for socio-demographic data collection, employing TAZs for transportation demand forecasting, and adopting TADs for transportation safety planning.Practical ApplicationsThe findings from this study can help practitioners select appropriate zonal systems for traffic crash modeling, which leads to develop more efficient policies to enhance transportation safety.     

The psychological impact of traffic injuries sustained in a road crash by bicyclists: A prospective study

Objective: The objective of this study was to investigate the psychological impact of traffic injuries in bicyclists (cyclists) in comparison to car occupants who also sustained traffic injuries. Factors predictive of elevated psychological distress were also investigated.

Methods: An inception cohort prospective design was used. Participants included cyclists aged ≥17 years (mean age 41.7 years) who sustained a physical injury (n = 238) assessed within 28 days of the crash, following medical examination by a registered health care practitioner. Injury included musculoskeletal and soft tissue injuries and minor/moderate traumatic brain injury (TBI), excluding severe TBI, spinal cord injury, and severe multiple fractures. Assessment also occurred 6 months postinjury. Telephone-administered interviews assessed a suite of measures including sociodemographic, preinjury health and injury factors. Psychological impact was measured by pain catastrophization, trauma-related distress, and general psychological distress. The psychological health of the cyclists was compared to that of the car occupants (n = 234; mean age 43.1 years). A mixed model repeated measures analysis, adjusted for confounding factors, was used to determine differences between groups and regression analyses were used to determine contributors to psychological health in the cyclists 6 months postinjury.

Results: Cyclists had significantly better psychological health (e.g., lower pain catastrophizing, lower rates of probable posttraumatic stress disorder [PTSD], and lower general distress levels) compared to car occupants at baseline and 6 months postinjury. Factors predictive of cyclists' psychological distress included younger age, greater perceived danger of death, poorer preinjury health, and greater amount of time in hospital after the injury.

Conclusions: These data provide insight into how cyclists perceive and adjust to their traffic injuries compared to drivers and passengers who sustain traffic injuries, as well as direction for preventing the development of severe psychological injury. Future research should examine the utility of predictors of psychological health to improve recovery.     

Repeatability study of replicate crash tests: A signal analysis approach

Objective: To provide an objective basis on which to evaluate the repeatability of vehicle crash test methods, a recently developed signal analysis method was used to evaluate correlation of sensor time history data between replicate vehicle crash tests. The goal of this study was to evaluate the repeatability of rollover crash tests performed with the Dynamic Rollover Test System (DRoTS) relative to other vehicle crash test methods.

Methods: Test data from DRoTS tests, deceleration rollover sled (DRS) tests, frontal crash tests, frontal offset crash tests, small overlap crash tests, small overlap impact (SOI) crash tests, and oblique crash tests were obtained from the literature and publicly available databases (the NHTSA vehicle database and the Insurance Institute for Highway Safety TechData) to examine crash test repeatability.

Results: Signal analysis of the DRoTS tests showed that force and deformation time histories had good to excellent repeatability, whereas vehicle kinematics showed only fair repeatability due to the vehicle mounting method for one pair of tests and slightly dissimilar mass properties (2.2%) in a second pair of tests. Relative to the DRS, the DRoTS tests showed very similar or higher levels of repeatability in nearly all vehicle kinematic data signals with the exception of global X′ (road direction of travel) velocity and displacement due to the functionality of the DRoTS fixture. Based on the average overall scoring metric of the dominant acceleration, DRoTS was found to be as repeatable as all other crash tests analyzed. Vertical force measures showed good repeatability and were on par with frontal crash barrier forces. Dynamic deformation measures showed good to excellent repeatability as opposed to poor repeatability seen in SOI and oblique deformation measures.

Conclusions: Using the signal analysis method as outlined in this article, the DRoTS was shown to have the same or better repeatability of crash test methods used in government regulatory and consumer evaluation test protocols.