An analysis of motorcyclist injury severity under various traffic control measures at three-legged junctions in the UK

The effects various junction control measures have on accident frequencies among vehicles have been investigated by previous studies through the use of statistical modelling techniques but such effects on motorcyclist injury severity, given that a junction-type accident has occurred, have received little attention in literature. This paper attempts to estimate econometric models of motorcyclist injury severity under different control measures at three-legged junctions in the UK, as a function of demographic, vehicle and environmental factors. Separate ordered probit models were estimated for unsignalised and signalised junctions, using the data extracted from the STATS19 accident injury database (1999–2004). Also examined in the models are collision partners’ aggressiveness toward motorcyclists and the impacts various crash configurations have on injury severity. The modelling results uncover several combined factors that were deadly to motorcyclists: for example, injuries tended to be much more severe while motorcyclists involving in approach-turn collisions at signalised junctions than at unsignalised junctions. This study ultimately offers insights into potential countermeasures that could be undertaken to help lessen motorcyclist injury severity at three-legged junctions in the UK.     

Motorcyclist injury severity in angle crashes at T-junctions: Identifying significant factors and analysing what made motorists fail to yield to motorcycles

Evidence in literature suggested that motorists’ failure to give way to motorcycles at junctions is the main contributory factor to motorcycle–car accidents that involve gap acceptance (i.e., approach-turn and angle crashes). This paper attempts to examine how motorist’s failure to give way affects motorcyclist injury severity in angle crashes at T-junctions, while controlling for other factors (demographic, vehicle, crash, and environmental factors). Binary logistic models of motorcyclist injury severity were estimated using the data extracted from the Stats19 accident injury database (1991–2004). Angle collisions were classified into several sub-crashes based on the manoeuvres motorcycles and cars were making prior to the accidents. The modelling results showed that injuries were greatest when a travelling-straight motorcycle on the main road crashed into a right-turn car from the minor road, particularly at stop-/yield-controlled junctions. Such crash pattern was assumed to be an accident involving right-of-way violation. Using binary logistic models, factors determining the likelihood of motorist’s failure to yield to motorcycles were also examined. The implications of the research findings of this present study were provided.     

Exploring motorcyclist injury severity resulting from various crash configurations at T-junctions in the United Kingdom--an application of the ordered probit models

OBJECTIVES: The fact that motorcycle users tend to be more vulnerable to injuries than those using other motorized vehicles may act synergistically with the complexity of conflicting movements between vehicles and motorcycles to increase injury severity in a junction-type accident. A junction-type collision tends to be more severe than a non-junction case due to the fact that some of the injurious crashes such as angle-collision commonly occur. Existing studies have applied several statistical modeling techniques to examine influential factors on the occurrences of different crashes among motorized vehicles but surprisingly very little has empirically explored whether a particular crash type, resulting from a junction-type accident, is more injurious to motorcyclists. This article attempts to investigate whether a particular collision is more deadly to motorcyclists conditioned on crash occurrence at T-junctions in the U.K., while controlling for environment, vehicle, and demographic factors. METHODS: The statistical modeling technique employed is the ordered probit models using the data extracted from the STATS19 accident injury database (1999-2004). RESULTS: The modeling found determinants of injury severity among motorcyclists at T-junctions in the U.K. For example, an approach-turn/head-on collision is much more injurious to motorcyclists; and, those riding in early morning (i.e., 0000-0659) are more likely to be severely injured. CONCLUSIONS: This study offers a guideline for future research, as well as insight into potential prevention strategies that might help moderate motorcyclist injuries.     

Analysis of driver injury severity levels at multiple locations using ordered probit models

Problem: The occurrence and outcome of traffic crashes have long been recognized as complex events involving interactions between many factors, including the roadway, driver, traffic characteristics, and the environment. This study is concerned with the outcome of the crash. Method: Driver injury severity levels are analyzed using the ordered probit modeling methodology. Models were developed for roadway sections, signalized intersections, and toll plazas in Central Florida. All models showed the significance of driver's age, gender, seat belt use, point of impact, speed, and vehicle type on the injury severity level. Other variables were found significant only in specific cases. Results: A driver's violation was significant in the case of signalized intersections. Alcohol, lighting conditions, and the existence of a horizontal curve affected the likelihood of injuries in the roadway sections' model. A variable specific to toll plazas, vehicles equipped with Electronic Toll Collection (ETC), had a positive effect on the probability of higher injury severity at toll plazas. Other variables that entered into some of the models were weather condition, area type, and some interaction factors. This study illustrates the similarities and the differences in the factors that affect injury severity between different locations.     

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.     

Highway safety assessment and improvement through crash prediction by injury severity and vehicle damage using Multivariate Poisson-Lognormal model and Joint Negative Binomial-Generalized Ordered Probit Fractional Split model

Introduction: Predicting crash counts by severity plays a dominant role in identifying roadway sites that experience overrepresented crashes, or an increase in the potential for crashes with higher severity levels. Valid and reliable methodologies for predicting highway accidents by severity are necessary in assessing contributing factors to severe highway crashes, and assisting the practitioners in allocating safety improvement resources. Methods: This paper uses urban and suburban intersection data in Connecticut, along with two sophisticated modeling approaches, i.e. a Multivariate Poisson-Lognormal (MVPLN) model and a Joint Negative Binomial-Generalized Ordered Probit Fractional Split (NB-GOPFS) model to assess the methodological rationality and accuracy by accommodating for the unobserved factors in predicting crash counts by severity level. Furthermore, crash prediction models based on vehicle damage level are estimated using the same two methodologies to supplement the injury severity in estimating crashes by severity when the sample mean of severe injury crashes (e.g., fatal crashes) is very low. Results: The model estimation results highlight the presence of correlations of crash counts among severity levels, as well as the crash counts in total and crash proportions by different severity levels. A comparison of results indicates that injury severity and vehicle damage are highly consistent. Conclusions: Crash severity counts are significantly correlated and should be accommodated in crash prediction models. Practical application: The findings of this research could help select sound and reliable methodologies for predicting highway accidents by injury severity. When crash data samples have challenges associated with the low observed sampling rates for severe injury crashes, this research also confirmed that vehicle damage can be appropriate as an alternative to injury severity in crash prediction by severity.     

A case study analysis to examine motorcycle crashes in Bogota,Colombia

IntroductionContributory factors to motorcycle crashes vary among populations depending on several aspects such as the users' profiles, the composition and density of traffic, and the infrastructure features. A better understanding of local motorcycle crashes can be reached in those places where a comprehensive analysis is performed. This paper presents the results obtained from a case study analysis of 400 police records of accidents involving motorcycles in Bogota.MethodTo achieve a deeper level of understanding of how these accidents occur, we propose a systemic approach that uses available crash data. The methodology is inspired by accident prototypical scenarios, a tool for analysis developed in France.ResultsWhen grouping cases we identified three categories: solo motorcycle accidents, motorcyclist and pedestrian accidents, and accidents involving a motorcycle and another vehicle. Within these categories we undertook in-depth analyses of 32 groups of accidents obtaining valuable information to better comprehend motorcyclists' road crashes in a local context. Recurrent contributory factors in the groups of accidents include: inexperienced motorcyclists, wide urban roads that incite speeding and risky overtaking maneuvers, flowing urban roads that encourage high speed and increased interaction between vehicles, and lack of infrastructure maintenance.Practical ApplicationsThe results obtained are a valuable asset to define measures that will be conveniently adapted to the group of accident on which we want to act. The methodology exposed in this paper is applicable to the study of road crashes that involve all types of actors, not only the motorcyclists, and in contexts different than those presented in Bogota.     

Motorcycle conspicuity: An evaluation and synthesis of influential factors

Motorcycles are overrepresented in fatal motor vehicle accidents: The death rate for motorcycle riders of about 35 per 100,000,000 miles of travel compares with an overall vehicle death rate of 2.57 per 100,000,000 miles. In the attempt to reduce the frequency of automobile-motorcycle collisions, numerous studies have manipulated motorcycle and motorcyclist characteristics to enhance conspicuity. In this paper, we give a review of studies that examined the effectiveness of these measures. Subsequently, we take a critical look at the methods used in these studies to evaluate the effectiveness of conspicuity treatments. Furthermore, we identify factors yet to be considered in the empirical research in this area that may contribute to collisions with motorcycles. These include information-processing failures at the identification and decision stage, as well as more or less permanent factors potentially responsible for different information-processing failures. Transient factors related to the failure to detect motorcycles might include alcohol, fatigue/lack of sleep, inattention, and information overload, whereas more permanent factors might include “cognitive” conspicuity and fi eld dependence.     

Factors associated with occupational injury severity in the New South Wales underground coal mining industry

The relationship between a large number of mine and mine worker characteristics and injury severity was examined using multiple regression techniques. The study was based on data extracted from the New South Wales (N.S.W.) Joint Coal Board's computer based accident/incident reporting system describing 21,372 non-fatal, lost-time injurious incidents that occurred in the N.S.W. underground coal mining industry during the 4 year period from 1 July 1986 to 30 June 1990. The number of days lost as a result of an injurious incident was the best available proxy measure of injury severity. Over the study period, the number of days lost per 100,000 tonnes of raw coal production declined by 73%. Over the same period, injurious incidents involving more than 20 days off work, which constituted only 16% of all injurious incidents in underground mines, resulted in 75% of the total days lost for the whole N.S.W. underground coal mining industry. Factors that had practical importance and that were significantly associated with injury severity included mine worker's age, part of the body injured, type of accident, agency of accident, and mine worker activity. Factors not important or not significant in their relationship with injury severity were: time into shift, previous hours worked, mine location of incident, occupation, work experience, frequency of task, shift, and mining region. This study suggests that factors related to the susceptibility of a mine worker's body tissue to damage or repair, and factors related to the concentration of energy on the mine worker by vehicle and environmental characteristics are important determinants of injury severity.     

Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study

Objective: The main objective of this study is to identify the main factors associated with injury severity of vulnerable road users (VRUs) involved in accidents at highway railroad grade crossings (HRGCs) using data mining techniques.

Methods: This article applies an ordered probit model, association rules, and classification and regression tree (CART) algorithms to the U.S. Federal Railroad Administration's (FRA) HRGC accident database for the period 2007–2013 to identify VRU injury severity factors at HRGCs.

Results: The results show that train speed is a key factor influencing injury severity. Further analysis illustrated that the presence of illumination does not reduce the severity of accidents for high-speed trains. In addition, there is a greater propensity toward fatal accidents for elderly road users compared to younger individuals. Interestingly, at night, injury accidents involving female road users are more severe compared to those involving males.

Conclusions: The ordered probit model was the primary technique, and CART and association rules act as the supporter and identifier of interactions between variables. All 3 algorithms' results consistently show that the most influential accident factors are train speed, VRU age, and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGCs.     

Correlation between crash avoidance maneuvers and injury severity sustained by motorcyclists in single-vehicle crashes

Objectives: In order to improve motorcycle safety, this article examines the correlation between crash avoidance maneuvers and injury severity sustained by motorcyclists, under multiple precrash conditions. Method: Ten-year crash data for single-vehicle motorcycle crashes from the General Estimates Systems (GES) were analyzed, using partial proportional odds models (i.e., generalized ordered logit models). Results: The modeling results show that “braking (no lock-up)” is associated with a higher probability of increased severity, whereas “braking (lock-up)” is associated with a higher probability of decreased severity, under all precrash conditions. “Steering” is associated with a higher probability of reduced injury severity when other vehicles are encroaching, whereas it is correlated with high injury severity under other conditions. “Braking and steering” is significantly associated with a higher probability of low severity under “animal encounter and object presence,” whereas it is surprisingly correlated with high injury severity when motorcycles are traveling off the edge of the road. The results also show that a large number of motorcyclists did not perform any crash avoidance maneuvers or conducted crash avoidance maneuvers that are significantly associated with high injury severity. Conclusions: In general, this study suggests that precrash maneuvers are an important factor associated with motorcyclists' injury severity. To improve motorcycle safety, training/educational programs should be considered to improve safety awareness and adjust driving habits of motorcyclists. Antilock brakes and such systems are also promising, because they could effectively prevent brake lock-up and assist motorcyclists in maneuvering during critical conditions. This study also provides valuable information for the design of motorcycle training curriculum.     

基于Logistic的不同车型碰撞行人事故严重程度致因分析

为定量分析不同车型碰撞行人事故严重程度影响因素,以美国北卡罗来纳州2007-2016年人车碰撞事故数据为样本,将其分为小轿车、SUV、货车碰撞行人事故3类,以事故严重程度为因变量,交通参与者属性、道路、环境条件和事故特征为候选自变量,分别建立累计logistic模型进行对比分析,探究人、车、路和环境因素对人车碰撞事故严...     

Effect of vehicle and crash factors on older occupants

PROBLEM: The expected substantial increase in people aged 65 or older is important for those concerned about transportation injuries. However, much of the previous research concentrates on older drivers and overlooks the fact that vehicle and crash factors may provide significant explanations of older occupant injury rates. METHOD: Differences across age groups are explored using two nationwide travel surveys, crash involvement, fatalities, and injuries from crash databases and an ordered probit model of injury severity. RESULTS AND DISCUSSION: Two noticeable differences that help explain injury risk are that older people are more likely to travel in passenger cars than younger people who frequently use light trucks, and that seriously injured older occupants are more likely to be involved in side-impact crashes than their younger counterparts. IMPACT: Increased attention to vehicle engagement in side-impact crashes and to vehicle technologies that can help drivers avoid side collisions would be particularly helpful for older occupants.     

Driver aging and its effect on male and female single-vehicle accident injuries: some additional evidence

INTRODUCTION: This study explores the differences in injury severity between male and female drivers, and across the different age groups, in single-vehicle accidents involving passenger cars. METHOD: Given the occurrence of an accident, separate male and female multinomial logit models of injury severity (with possible outcomes of no injury, injury, and fatality) were estimated for young (ages 16 to 24), middle-aged (ages 25 to 64), and older (ages 65 and older) drivers. RESULTS: The estimation results show statistically significant differences in the factors that determine injury-severity levels between male and female drivers and among the different driver age groups. CONCLUSIONS: We discuss a number of plausible explanations for the observed age/gender differences and provide suggestions for future work on the subject. IMPACT ON INDUSTRY: A better understanding of age and gender differences can lead to improvements in vehicle and highway design to minimize driver injury severity. This paper provides some new evidence to help unravel this complex problem.     

The effect of age and gender on motor vehicle driver injury severity at highway-rail grade crossings in the United States

IntroductionBased on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive database of highway-rail grade crossing accidents in the United States from 2002 to 2011, estimation results showed that there were substantial differences across age/gender groups for driver's injury severity.MethodThe study applied an ordered probit model to explore the determinants of driver injury severity for motor vehicle drivers at highway-rail grade crossings.ResultsThe analysis found that there are important behavioral and physical differences between male and female drivers given a highway-rail grade crossing accident happened.Practical applicationsOlder drivers have higher fatality probabilities when driving in open space under passive control especially during bad weather condition. Younger male drivers are found to be more likely to have severe injuries at rush hour with high vehicle speed passing unpaved highway-rail grade crossings under passive control. Synthesizing these results led to the conclusion that the primary problem with young is risk-taking and lack of vehicle handling skills. The strength of older drivers lies in their aversion to risk, but physical degradation issues which result in longer reaction/perception times and degradation in vision and hearing often counterbalance this attribute.     

The effect of motorcyclists’ age on injury severities in single-motorcycle crashes with unobserved heterogeneity

Introduction: Due to the myriad of unique characteristics associated with motorcycle operation, motorcycle safety is a public health concern as complex as it is serious. National crash data suggest motorcyclists are 28 times more likely to be killed when compared to passenger car occupants. In the state of Florida, motorcycle crashes are 1.5 times more likely to result in the death of the rider, placing Florida among the top deadliest states for motorcyclists in the nation. Using police-reported data from 2016, this study addresses the complex and interconnected nature of the many characteristics associated with motorcycle operation by investigating the effect of age on motorcyclists’ riding behavior as it relates to injury severity for single-motorcycle crashes in the state of Florida. Method: To account for unobserved heterogeneity in the crash data, mixed logit models with heterogeneity in means and variances were estimated to model three injury severity outcomes (non-visible, severe, and fatal) for three age groups (under 30, 30–49, and 50 and above). Results: Model results indicate that age affects motorcyclists’ safety perception and ability to assess risks, thereby influencing their involvement in risky behaviors. Characteristics unique to motorcycle operation—spatial characteristics, speed, motorcycle type, time of day, helmet usage, alcohol consumption, ejection from motorcycle, passenger presence, endorsement status, and lighting—are further complicated by their dependency on the characteristics of the individual motorcyclist. Age of motorcyclist indicates a relationship between motorcyclists’ behavior and perceived safety. Conclusion: The model results indicated that statistically significant parameters constituted different models and they were not equal across the age groups of motorcyclists: aged under 30, aged 30–49, and aged 50 and above. Through advanced econometric modeling, this study fills a gap in the existing literature and assists the safety professionals, motorcycle trainers, policymakers, law enforcement agencies, and roadway designers in developing countermeasures.     

A multinomial logit analysis of factors associated with severity of motorcycle crashes in Ghana

Objective: The objective of this study was to explore the factors affecting motorcycle crash severity in Ghana.

Methods: A retrospective analysis of motorcycle crash data between 2011 and 2015 was conducted using a motorcycle crash data set extracted from the National Road Traffic Crash Database at the Building and Road Research Institute (BRRI) in Ghana. Injury severity was classified into 4 categories: Fatal, hospitalized, injured, and damage only. A multinomial logit modeling framework was used to identify the possible determinants of motorcycle crash severity.

Results: During the study period, a total of 8,516 motorcycle crashes were recorded, of which 22.9% were classified as fatal, 42.1% were classified as hospitalized injuries, 29.4% were classified as slight injuries, and 5.6% were classified as damage-only crashes. The estimation results indicate that the following factors increase the probability of fatal injuries: At a junction; weekend; signage; poor road shoulder; village settlement; tarred and good road surface; and collision between motorcycle and heavy goods vehicle (HGV). Motorcycle crashes occurring during the daytime and on the weekend increases the probability of hospitalized injury. The results also suggest that motorcycle crashes occurring during the daytime, in curves or inclined portions of roads, or in unclear weather conditions decrease the probability of fatal injury.

Conclusions: This study provides further empirical evidence to support motorcycle crash modeling research, which is lacking in developing countries. The ability to understand the various factors that influence motorcycle crash severity is a step forward in providing an appropriate basis upon which informed motorcycle crash policies can be developed. Particular attention should be given to the provision of road signage at junctions and speed humps and controlling traffic during the weekend. In addition, road maintenance should be carried out periodically to address motorcycle safety in Ghana.     

超大城市昼夜交通事故严重程度致因对比分析——以深圳市为例

为研究夜间交通事故严重程度致因，基于深圳市3年3 244起交通事故数据，获取昼夜交通事故分布的时空特征；进一步选取交通事故集聚的南山区、福田区、罗湖区的1 798起交通事故，以交通事故严重程度为因变量，以事故原因、日期、事故形态等10个因素为候选自变量，构建广义有序Logit回归模型，对比分析昼夜不同严重程度交通事故的影响因素。结果表明:路口路段类型、疲劳驾驶、事故日期在夜间模型参数估计值分别为0.493，-0.363，-0.309，而在日间模型表现为不显著，道路路面材料在日间模型参数估计值为-0.232，而在夜间表现为不显著；事故原因、道路横断面渠化方式等因素在日间和夜间所引起交通事故的严重等级均存在较大差异。     

Effect of novel divergence markings on conflict prevention regarding motorcycle-involved right turn accidents of mixed traffic flow

Introduction: In Taiwan, segregated traffic flow countermeasures have long been in place. Although these facilities have decreased the numbers of motorcycle left-turn collisions, right-angle collisions, and sideswipe collisions, they have also induced serious right-turn accidents. The purpose of this research was to evaluate an intervention intended to decrease conflicts and motorcycle-involved crashes. In this study, the reasons why the motorcycle accident rate is higher at intersections with slow lanes than at those without slow lanes are presented, and the theory of the self-explaining road was applied to create divergence markings for a mixed traffic flow environment. An intervention that guides motorcycles and cars into appropriate locations at intersections was applied to three intersection approaches. Method: The intervention effectiveness was evaluated by comparing the number of accidents at the intersections before and after the implementation of improvement measures. Moreover, video recordings were used to analyze the traffic distributions at the cross-sections of intersections. T-test was adopted to examine whether the traffic flows at the cross-sections of the intersections before and after the intervention were statistically different. In addition, this research applied the post-encroachment time (PET), the time between the first road user leaving the encroachment zone and the second road user arriving in it, to evaluate traffic conflicts. Finally, the PET and severity index between a straight-through motorcycle and a right-turn vehicle were analyzed. Results: PET increased by 3.2%–20.4%, and the rates of right-turn collisions, sideswipe collisions, and rear-end collisions decreased by 64.3%, 77.3%, and 61.5% respectively. Conclusions: Eliminating the slow traffic lane and setting divergence markings may not effectively cause vehicles in different driving directions to drive in the proper locations in the lanes. However, divergence markings both reduce the rate of right-turn collisions and decrease the incidence of sideswipe and rear-end collisions. Practical applications: The proposed design method may be a good design reference for countries having a high motorcycle density.     

基于车辆事故等级分类的紧急呼救系统研究

基于交通事故紧急救援的现状,阐述建立车辆事故紧急呼救系统的新需求,提出了开发基于车辆事故严重等级分类的紧急呼救系统需要实现的功能;应用车辆碰撞安全性理论和研究成果、导航定位技术及通信技术,设计了基于事故严重等级分类的车辆事故紧急呼救决策流程;探讨车辆事故自动检测和等级分类及紧急救援的实施方案,以实现车辆事故紧急自动呼救,使车辆和伤员得到及时高效的紧急救助。