Acute injuries resulting from accidents involving powered mobility devices (PMDs)—Development and outcomes of PMD-related accidents in Sweden

Objective: Powered mobility devices (PMDs) are commonly used as aids for older people and people with disabilities, subgroups of vulnarable road users (VRUs) who are rarely noted in traffic safety contexts. However, the problem of accidents involving PMD drivers has been reported in many countries where these vehicles have become increasingly popular.

The aim of this study is to extract and analyze national PMD-related accident and injury data reported to the Swedish Traffic Accident Data Acquisition (STRADA) database. The results will provide valuable insight into the risks and obstacles that PMD drivers are exposed to in the traffic environment and may contribute to improving the mobility of this group in the long term.

Methods: The current study is based on data from 743 accidents and 998 persons. An analysis was performed on a subset of data (N?=?301) in order to investigate the development of accidents over a period of 10 years. Thereafter, each accident in the whole data set was registered as either single (N?=?427) or collision (N?=?315).

Results: The results show that there was a 3-fold increase in the number of PMD-related accidents reported to STRADA during the period 2007–2016.

With regard to single accidents, collisions, as well as fatalities, the injury statistics were dominated by males. Single accidents were more common than collisions (N?=?427 and N?=?316, respectively) and the level of injury sustained in each type of accident is on par.

The vast majority of single accidents resulted in the PMD driver impacting the ground (87%), due to either PMD turnover (71%) or the driver falling out of the PMD (16%). The reason for many of the single accidents was a difference in ground level (34%, typically a curb).

Cars, trucks, or buses were involved in 67% of collision events; these occured predominantly at junctions or intersections (70%).

Abbreviated Injury Scale (AIS) 3+ injuries were dominated by hip and head injuries in both single accidents and collision events.

Conclusions: The present study shows that further research on PMD accidents is required, with regard to both single accidents and collision events. To ensure that appropriate decisions are made, future work should follow up on injury trends and further improve the quality of PDM-related accident data. Improved vehicle stability and design, increased usage of safety equipment, proper training programs, effective maintenance services, and development of a supporting infrastructure would contribute to increased safety for PMD drivers.     

斑马线“人-车”博弈仿真

我国自2017年开展“车让人”活动以来,斑马线事故得到有效控制。但本文经统计发现,近两年交通事故量并未明显降低,即“车让人”虽有效控制了斑马线事故,但并未明显影响整体交通安全形势。为此论文设计了3种人车博弈仿真实验,分析不同典型情况下的礼让司机心态:在没有规定车让人时,积极礼让率约20%;在规定车让人时,积极礼让率约50%;当给予司机正向反馈时,积极礼让率约70%,仿真结果验证了:如果没有很好地兼顾司机情绪,“车让人”并不能实现本质安全,即大量交通事故只不过是从斑马线推移到了公路的其他地方(事故外溢)。论文最后建议在斑马线处分别设计给司机和行人阅读的2套标语,综合调控司机心境,有效防控“斑马线事故外溢”。     

The effect of right-turn-on-red on pedestrian and bicyclist accidents

Right-Turn-on-Red (RTOR), in its “Western” version allows motorists to turn right on a red signal after stopping and yielding, unless specifically prohibited by a sign. The objective of this study was to determine the effect of Western RTOR on pedestrian and bicycle accidents in selected jurisdictions adopting the rule in the mid-1970s. The results showed significant increases in pedestrian and bicyclist accidents involving right-turning vehicles at signalized locations following the introduction of Western RTOR. These increases were: 40 % for pedestrians and 82 % for bicycles in New York State; 107 % for pedestrians and 72 % for bicycles in Wisconsin; 57 % for pedestrians and 80 % for bicycles in Ohio; and 82 % for pedestrians in New Orleans. Analysis of police accident reports suggested that drivers stopped for a red light are looking left for a gap in traffic and do not see pedestrians and bicyclists coming from their right. Countermeasure research and development was recommended to deal with this well defined problem which involves between 1 % and 3 % of all pedestrian and bicycle accidents.     

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

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

Walking when intoxicated: An investigation of the factors which influence individuals’ drink walking intentions

Annually, in Australia, 10-15% of all road-related fatalities involve pedestrians. Of those pedestrians fatally injured, approximately 45% were walking while intoxicated or ‘drink walking’. Drink walking is increasing in prevalence and younger persons may be especially prone to engage in this behaviour and, thus, are at heightened risk of being injured or killed. Presently, limited research is available regarding the factors which influence individuals to drink walk. This study explored young people’s (17-25 years) intentions to drink walk, using an extended Theory of Planned Behaviour (TPB). Participants (N = 215), completed a self-report questionnaire which assessed the standard TPB constructs (attitude, subjective norm, perceived behavioural control) as well as the extended constructs of risk perception, anticipated regret, and past behaviour. It was hypothesised that the standard TPB constructs would significantly predict individuals’ reported intentions to drink walk and that the additional constructs would predict intentions over and above the TPB constructs. The TPB variables significantly predicted 63.2% of the variance in individuals’ reported intentions to drink walk, and the additional variables, combined, explained a further 6.1% of the variance. Of the additional constructs, anticipated regret and past behaviour, but not risk perception, were significant predictors of drink walking intentions. As one of the first studies to provide a theoretically-based investigation of factors influencing individuals’ drink walking intentions, the current study’s findings have potentially significant implications for understanding young people’s decisions to drink walk and the design of future countermeasures to ultimately reduce this behaviour.     

Factors affecting pedestrian behaviors at signalized crosswalks: An empirical study

Introduction: Safety of pedestrians depends, among other factors, on their behavior while crossing the road. This study aims to assess behaviors of pedestrians at signalized crosswalks. Method: Following a literature review and a pilot study, 25 vital pedestrian crossing factors and behaviors were determined. Then data was randomly collected for 708 pedestrians at 10 lighted crossings in Sharjah (UAE), five at road intersections and five mid-block crossings. Results: Results indicated that 17.4% of pedestrians observed crossed partly or fully on red and that crossing speed was 1.22 m/s, on the average, which is slightly faster than most speeds recorded in the literature. Moreover, female pedestrians were more likely to cross while chatting with others, less likely to cross on red, and more likely to walk slower than male pedestrians. Results also showed that pedestrians who crossed at road intersections walked slower than those who crossed at mid-block crossings. It was also found that longer red pedestrian times and narrower roads tended to encourage pedestrians to cross on red and that the majority of pedestrians did not look around before crossing. Practical implications: Use of the Health Belief Model for pedestrian safety are discussed.     

Identifying an appropriate driving behaviour scale for the occupational driving context: The DBQ vs. the ODBQ

Self reported driving behaviour in the occupational driving context has typically been measured through scales adapted from the general driving population (i.e., the Manchester Driver Behaviour Questionnaire, (DBQ), Reason et al., 1990). However, research suggests that occupational driving is influenced by unique factors operating within the workplace environment, and thus, a behavioural scale should reflect those behaviours prevalent and unique within the driving context. To overcome this limitation, Newnam et al. (2011) developed the Occupational Driver Behaviour Questionnaire ((ODBQ), Newnam et al., 2011) which utilises a relevant theoretical model to assess the impact of the broader workplace context on driving behaviour. Although the theoretical argument has been established, research is yet to examine whether the ODBQ or the DBQ is a more sensitive measure of the workplace context. As such, this paper identifies selected organisational factors (i.e., safety climate and role overload) as predictors of the DBQ and the ODBQ and compares the relative predictive value in both models. In undertaking this task, 248 occupational drivers were recruited from a community-oriented nursing population. As predicted, hierarchical regression analyses revealed that the organisational factors accounted for a significantly greater proportion of variance in the ODBQ than the DBQ. These findings offer a number of practical and theoretical applications for occupational driving practice and future research.     

Fatal pedestrian crashes on interstates and other freeways in the United States

Introduction: More than 800 pedestrians die annually in crashes on interstates and other freeways in the United States, but few studies have examined their characteristics. Method: Data from the Fatality Analysis Reporting System on pedestrians fatally injured during 2015–2017 were analyzed. Chi-square tests compared characteristics of pedestrians killed on interstates and other freeways with those that died on other roads, and across crash types among freeway deaths. Land use characteristics of locations where pedestrians were killed while crossing freeways in a large state (California) were identified using Google Earth. Results: A larger proportion of pedestrians killed on freeways died on dark and unlit roads (48% vs. 32%), were male (78% vs. 68%), or were ages 20–44 (55% vs. 32%) compared with pedestrians killed on other roads. Crossing (42%) was the most common crash type among pedestrian deaths on freeways, followed by disabled-vehicle-related crashes (18%). Pedestrians who died while crossing more often had blood alcohol concentrations ≥ 0.08 g/dL (40%) than those in disabled-vehicle-related (22%) or other crashes (34%). Deaths in crossing crashes were more likely than other freeway deaths to occur on urban roads (81%), at speed limits ≤50 mph (13%), or between 18:00 and 23:59 (49%), and 58% of crossing crashes analyzed for land use were located between residential and other (e.g., commercial, recreational) uses. Over a third (37%) of deaths in disabled-vehicle-related crashes occurred at speed limits ≥70 mph. Conclusions: A surprising proportion of pedestrian deaths occur on controlled-access roads not designed for walking. Countermeasures for these crashes need to be implemented to see meaningful reductions in pedestrian fatalities overall. Practical applications: Improving roadway and vehicle lighting, requiring reflective warning devices for marking disabled vehicles, constructing pedestrian overpasses and underpasses in areas frequently crossed, and promoting alternative means of traveling between residential and commercial areas could help.     

Distracted walking: cell phones increase injury risk for college pedestrians

Introduction

Distraction on cell phones jeopardizes motor-vehicle driver safety, but few studies examine distracted walking. At particular risk are college students, who walk frequently in and near traffic, have increased pedestrian injury rates compared to other age groups, and frequently use cell phones. Method: Using an interactive and immersive virtual environment, two experiments studied the effect of cell phone conversation on distraction of college student pedestrians. In the first, we examined whether pedestrians would display riskier behavior when distracted by a naturalistic cell phone conversation than when undistracted. We also considered whether individual difference factors would moderate the effect of the distraction. In a second experiment, we examined the impact of three forms of distraction on pedestrian safety: (a) engaging in a cell phone conversation, (b) engaging in a cognitively challenging spatial task by phone, and (c) engaging in a cognitively challenging mental arithmetic task by phone. Results: Results revealed that cell phone conversations distracted college pedestrians considerably across all pedestrian safety variables measured, with just one exception. Attention to traffic was not affected by the naturalistic phone conversation in Experiment 1, but was altered by the cognitively-demanding content of some types of conversation in Experiment 2. The content of the conversation did not play a major role in distraction across other variables; both mundane and cognitively complex conversations distracted participants. Moreover, no significant associations between individual difference factors and susceptibility to distraction emerged. Impact on Industry: Results may inform researchers, policy makers, and pedestrians themselves. Educational campaigns might discourage telephone conversations in pedestrian environments.     

Modeling pedestrian gap crossing index under mixed traffic condition

IntroductionThere are a variety of challenges faced by pedestrians when they walk along and attempt to cross a road, as the most recorded accidents occur during this time. Pedestrians of all types, including both sexes with numerous aging groups, are always subjected to risk and are characterized as the most exposed road users. The increased demand for better traffic management strategies to reduce the risks at intersections, improve quality traffic management, traffic volume, and longer cycle time has further increased concerns over the past decade.MethodThis paper aims to develop a sustainable pedestrian gap crossing index model based on traffic flow density. It focusses on the gaps accepted by pedestrians and their decision for street crossing, where (Log-Gap) logarithm of accepted gaps was used to optimize the result of a model for gap crossing behavior. Through a review of extant literature, 15 influential variables were extracted for further empirical analysis. Subsequently, data from the observation at an uncontrolled mid-block in Jalan Ampang in Kuala Lumpur, Malaysia was gathered and Multiple Linear Regression (MLR) and Binary Logit Model (BLM) techniques were employed to analyze the results.Results and conclusionsFrom the results, different pedestrian behavioral characteristics were considered for a minimum gap size model, out of which only a few (four) variables could explain the pedestrian road crossing behavior while the remaining variables have an insignificant effect. Among the different variables, age, rolling gap, vehicle type, and crossing were the most influential variables. The study concludes that pedestrians’ decision to cross the street depends on the pedestrian age, rolling gap, vehicle type, and size of traffic gap before crossing.Practical applicationsThe inferences from these models will be useful to increase pedestrian safety and performance evaluation of uncontrolled midblock road crossings in developing countries.     

Investigation of key factors for accident severity at railroad grade crossings by using a logit model

Although several studies have used logit or probit models and their variants to fit data of accident severity on roadway segments, few have investigated accident severity at a railroad grade crossing (RGC). Compared to accident risk analysis in terms of accident frequency and severity of a highway system, investigation of the factors contributing to traffic accidents at an RGC may be more complicated because of additional highway–railway interactions. Because the proportional odds assumption was violated while fitting cumulative logit modeled by the proportional odds models with stepwise variable selection to ordinal accident severity data collected at 592 RGCs in Taiwan as suggested by Strokes et al. [Strokes, M.E., Davis, C.S., Koch, G.G., 2000. Categorical Data Analysis Using the SAS System, second ed. SAS Institute, Inc., Cary, NC, p. 249], a generalized logit model with stepwise variable selection was used instead to identify explanatory variables (factors or covariates) that were significantly associated with the severity of collisions. Hence, the fitted model was used to predict the level of accident severity, given a set of values in the explanatory variables. Number of daily trains, highway separation, number of daily trucks, obstacle detection device, and approaching crossing markings significantly affected levels of accident severity at an RGC (p-value = 0.0009, 0.0008, 0.0112, 0.0017, and 0.0003, respectively). Finally, marginal effect analysis on the number of daily trains and law enforcement camera was conducted to evaluate the effect of the number of daily trains and presence of a law enforcement camera on the potential accident severity.     

Personal exposure risk factors in pedestrian accidents in Bahrain

Pedestrians are involved in traffic accidents due to many reasons. It is generally thought that personal background of pedestrians has an effect on their involvement rate in the road traffic accidents. Identifying these characteristics would lead to a better understanding of pedestrian accident pattern so that the resources in the field of education, engineering, and enforcement could be used in better ways. This study attempts to test the hypothesis mentioned earlier. The investigated personal background includes the following characteristics: gender, type, age, nationality, and educational background. The data was reduced from vast number of pedestrian injury accident reports in the Kingdom of Bahrain. The actual accident records were categorized according to these characteristics and compared to their exposure risk. It was assumed that the exposure risk, which is the expected number of accidents for each category of the pedestrians, was in proportion to their presence in the pedestrian population. Another study was carried out in parallel to observe the pedestrian characteristics in Bahrain. The results of the two studies were analyzed statistically using Chi-square method to compare the actual to the expected accident frequencies. The whole Kingdom of Bahrain population statistics were used wherever the information on the pedestrian population was not available. The findings revealed that personal characteristics considered in this study have significant influence on pedestrian’s involvement in traffic accidents. The results also showed that pedestrians with the following characteristics were probably showing risk to exposure to accidents more than other categories: male, young (0–12 years) and old (50 years and over), non-local, and those with low educational background.     

Reliability analysis of pedestrian safety crossing in urban traffic environment

This paper describes the pedestrian safety crossing behaviour at signalized crosswalks in an urban traffic environment based on human reliability analysis. In our research, pedestrians’ waiting durations are modelled by a non-parametric and two parametric reliability models that recognize the effects of covariates. The covariates include pedestrian personal characteristics and urban traffic conditions in order to reflect the effects of human factors and internal environment comprehensively. The results indicate that most pedestrians show distinct time-dependent reliability but a few pedestrians are too impatient to wait for the lights changes.     

A comparison of required coefficient of friction for both feet in level walking

The required coefficient of friction (RCOF) is one of the critical elements in determining whether a slip incident might occur. Most researchers, when measuring RCOF, do not differentiate between the two feet of the same participant under the same walking condition. Results from a recent study (Chang et al., 2010) indicated that the stochastic distributions of the RCOF of both feet were different in 76% of the cases. Using the previous data (Chang et al., 2010), this paper presents a comparison of the RCOF for both feet of 50 participants under four level walking conditions resulting from two footwear types and two walking speeds using a t-test, commonly used by safety professionals to compare two pools of data. The current results indicated that 78% of the RCOF data showed a statistically significant difference between the RCOF from two feet for the same participant under each walking condition. The results of the logistic regression analysis used to identify factors that contributed to the outcome of the t-test indicated that the walking speed was the only factor with a statistical significance (p = 0.044).     

The effect of overtaking behavior on unidirectional pedestrian flow

We present a model of overtaking behavior that can be used to simulate unidirectional pedestrian flow in routine. All pedestrians have the ability to determine whether or not to overtake other pedestrians according to their desired velocity and position. Although existing models such as cellular automata models, lattice gas models, social force models, etc., can be used to predict evacuation performance, most of these models are either computationally inefficient or do not account for some crucial elements of human behavior in a moving crowd. Furthermore, these models use either empirical equations developed from experiments or mechanical system analogies to determine movement decisions. The pedestrian flow patterns simulated by these models may deviate significantly from reality. In reality, pedestrians walk at different velocities and pedestrians with a higher walking velocity are accustomed to overtaking other pedestrians with a lower walking velocity and this paper aims to mimic this behavior as the original social force model developed by Helbing et al. does not reflect this pattern of collective pedestrian behavior. In this paper, we propose modifications of the social force model that reflects how overtaking behavior operates in routine. The comparison of the pedestrian flow pattern between the original social force model and the modified social force models with the real data collected by the camcorder is also performed in order to demonstrate our modified social force model can be used to achieve reasonable simulations of overtaking behavior among pedestrians.     

Pedestrian distraction: The effects of road environment complexity and age on pedestrian’s visual attention and crossing behavior

Introduction: Little is known about how characteristics of the environment affect pedestrians’ road crossing behavior. Method: In this work, the effect of typical urban visual clutter created by objects and elements in the road proximity (e.g., billboards) on adults and children (aged 9–13) road crossing behavior was examined in a controlled laboratory environment, utilizing virtual reality scenarios projected on a large dome screen. Results: Divided into three levels of visual load, results showed that high visual load affected children’s and adults’ road crossing behavior and visual attention. The main effect on participants’ crossing decisions was seen in missed crossing opportunities. Children and adults missed more opportunities to cross the road when exposed to more cluttered road environments. An interaction with age was found in the dispersion of the visual attention measure. Children, 9–10 and 11–13 years old, had a wider spread of gazes across the scene when the environment was highly loaded—an effect not seen with adults. However, unexpectedly, no other indication of the deterring effect was found in the current study. Still, according to the results, it is reasonable to assume that busier road environments can be more hazardous to adult and child pedestrians. Practical Applications: In that context, it is important to further investigate the possible distracting effect of causal objects in the road environment on pedestrians, and especially children. This knowledge can help to create better safety guideline for children and assist urban planners in creating safer urban environments.     

Driving and telephoning: Relative accident risk when using hand-held and hands-free mobile phones

Experimental research shows that using mobile phones while driving leads to impaired driving, and it has been suggested that this driving impairment to a large extent is a result of cognitive, rather than physical, distractions. This notion is partly supported by empirical data showing that use of hands-free phones is associated with impaired driving in much the same way as use of hand-held phones. In the present study, accident risk when using hand-held and hands-free phones was investigated in a sample of 4307 drivers who were involved in accidents in 2007. In addition, data from a similar survey from 1997 (N = 5007) were used in order to get more observations. Relative risk was estimated using “quasi-induced exposure” in multiple-vehicle accidents. Results from the two surveys combined showed a significant increase in accident risk for hand-held mobiles and for hand-held and hands-free phones together. A non-significant tendency towards increased risk for hands-free mobiles was also detected. However, analyses of data from 2007 separately did not result in statistically significant relative risk estimates for any of the mobile types. Hand-held users were more inclined to attribute the accident to mobile phone use than were hands-free users.     

大城市无信号控制人行横道行人过街延误分析

从心理学角度,以大城市无信号控制人行横道过街行人为研究对象,对行人过街延误进行定量分析研究。以北京市两个典型无信号控制人行横道为实例进行交通调查分析,计算行人的临界穿越间隙,安全穿越间隙出现的概率,及行人穿越该处的总延误时间。计算结果表明:观测路段车流中提供的安全穿越间隙的概率比较低;行人强行穿越的重要原因是行人过街延误超出了行人等待心理极限;验证了模型的精度;找出了观测路段交通秩序混乱的原因。针对大城市无信号控制人行横道的分析结果,提出了具体的改进建议和交通改善措施,为国内大城市行人交通安全管理提供了决策依据和有益参考。     

Analysis of recent trends in bus and coach safety in Britain

We examine in detail trends from 1966 to 1990 and the fitting of statistical models to assess whether significant changes have taken place in casualty rates since local bus deregulation in 1986.The major source of data is the ‘Stats 19’ collated from police reports by the Department of Transport.The evidence indicates that no significant change in casualty rates for bus and coach occupants (defined as those killed or seriously injured) has occurred since local bus deregulation, although the previous trend of reduction in fatality rates has not been maintained.International comparisons have been made between Britain and a sample of other West European countries. Britain appears to have a higher occupant fatality rate. However, other countries′ data do not always include casualties to bus and coach occupants other than those in which vehicular collisions occur. Better comparative data is available for accidents involving buses and coaches with other road users, notably for Britain and Germany. These suggest that such accidents tend to reflect the national pattern of road casualty rates — for example, Germany has a higher level of collisions between buses and coaches, and other road vehicles, while Britain has a relatively high incidence of casualties involving pedestrians.Differences in accident rates between Britain and other European countries and the extent to which they reflect real differences, as distinct from those due to differences in recording of data, are evaluated, along with policy implications.     

"The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis" Comments

A previously published meta-analysis of the predictive power of the Manchester Driver Behaviour Questionnaire (DBQ) versus road traffic crashes is criticized upon a number of counts, including the incomplete handling of common method variance, failure to control for exposure and how the correction for unreliability of the accident variable was undertaken. It is concluded that the results reported, and the conclusions drawn from these, are too favorable to the DBQ, despite the effect sizes being

Common method variance

The main problem associated with the interpretation of the DBQ/accidents association is common method variance (i.e., systematic biases in the self-reports used), which create part or all of the associations found (Chang et al., 2010, Podsakoff et al., 2003). Common method variance may be due to a number of different factors, and in some studies, substantial effects have been found (e.g., Hessing, Elffers, &; Weigel, 1988; for reviews see Cote and Buckley, 1987, Podsakoff et al., 2003). This

Conclusions

To summarize, we believe that the meta-analysis of de Winter and Dodou is somewhat too favorable to the DBQ by failing to make the above points. Yet we paradoxically agree with de Winter and Dodou in one of their conclusions and recommendations; more studies using other-source criteria are needed. The self-report-source only data are not reliable, and conclusions about the predictive power of the DBQ factors versus traffic safety are not yet possible to draw.