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Background: Studies from Finland and Taiwan have shown that walking against traffic was beneficial for reducing pedestrian crashes and fatalities. This study examined whether such beneficial effects are consistent across various circumstances. Methods: This study aimed to investigate pedestrian fatalities in walking-against or with-traffic crashes by analysing the UK STATS19 crash data for the period between 1991 and 2020. We firstly employed Chi-square tests to examine risk factors for pedestrian injury severity. These variables were then incorporated into stepwise logistic regression models with multiple variables. We subsequently conducted joint effect analysis to investigate whether the beneficial effects of walking against traffic on injury severity vary across different situations. Results: Our data contained 44,488 pedestrian crashes, of which 16,889 and 27,599 involved pedestrians walking against and with traffic, respectively. Pedestrians involved in with-traffic crashes were more likely to sustain fatalities (adjusted odds ratio [AOR] = 1.542; confidence interval [CI] = 1.139–1.927) compared with those in walking against-traffic crashes. The detrimental effect of walking with traffic on fatalities appeared to be more pronounced in darkness-unlit conditions (AOR = 1.48; CI = 1.29–1.70), during midnight hours (00:00–06:59 am) (AOR = 1.60; CI = 1.37–1.87), in rural areas (AOR = 2.20; CI = 1.92–2.51), when pedestrians were elderly (≥ 65 years old) (AOR = 2.65, CI = 2.16–3.26), and when heavy goods vehicles were crash partners (AOR = 1.51, CI = 1.28–1.78). Conclusions: Walking against traffic was beneficial in reducing pedestrian fatalities compared with walking with traffic. Furthermore, such a beneficial effect was more pronounced in darkness-unlit conditions, at midnights (00:00–06:59 am), in rural areas, when pedestrians were elderly, and when heavy goods vehicles struck pedestrians. [ABSTRACT FROM AUTHOR]

This paper assesses pedestrian crossing behavior and critical gaps at a two-way midblock crossing location. A critical gap is the shortest gap that a pedestrian accepts when crossing a road. A dataset was collected in 2017 in Edinburgh (UK). The analysis was performed using the fuzzy logic system. The adopted membership function of the fuzzy logic system is of a triangular form since it has a simple and convenient structure. The input variables that are used in the analysis are the number and length of rejected gaps and length of accepted gaps at the crossing location. The output variables are the critical gaps. The results show that assessing critical gap estimation of pedestrians crossing using fuzzy logic is achievable and produces reasonable values that are comparable to values that are reported in the literature. This outcome improves the understanding of pedestrian crossing behavior and could therefore have implications for transport infrastructure design. Further analysis using additional parameters including waiting time and demographic characteristics and alternative forms for membership functions are strongly encouraged. [ABSTRACT FROM AUTHOR]

Objectives: Over half of pedestrians killed and seriously injured in Great Britain in 2015 were involved in crashes at junctions. This study investigates the nature of these crashes. Methods: A study was conducted into pedestrian casualty crashes at priority controlled junctions, roundabouts and signalised junctions in England between 2005 and 2015 using information from the UK STATS19 accident database, the UK National Travel Survey and the UK National Census. Consideration was given to coding frequencies of contributory factors, exposure (in terms of miles walked or driven) as well as age, gender and the resident deprivation index of the road users involved. Results and Conclusions: In terms of indicative blame, the coding frequencies of subjectively determined pedestrian actions and behaviour factors which might have contributed to pedestrian casualty crashes were found to be between 1.6 and 2.8 times the frequencies of driver actions and behavioural factors. Substantial social gradients were found in pedestrian casualty rates per miles walked and in the driver involvement rates per mile driven with those from the most deprived quintile having higher rates. In addition, it was found that female pedestrians, aged 60 years and over, had higher pedestrian casualty rates, per billion miles walked, for all three junction types, when compared with males and females under the age of 60 years, apart from male pedestrians aged 16 years and younger at priority controlled junctions. [ABSTRACT FROM AUTHOR]

Abstract: Motorcyclists tend to be more vulnerable to injuries than those using other motorised vehicles and this 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 crash can be more severe to motorcyclists than a non-junction case due to the fact that some of the injurious crashes such as angle crash commonly occur. Previous studies have applied crash prediction models to investigate influential factors on the occurrences of different crashes among motorised vehicles but statistical models of motorcyclist injury severity resulting from different collision types have rarely been developed. This paper develops injury severity models for different collision-types conditioned on crash occurrence at T-junctions in the UK. The ordered logit models are estimated using human, weather, road and vehicle factors as predictors and the data for the model estimation were extracted from the STATS19 accident injury database (1991–2004). The modelling results show that motorcyclist injury severity in specific crash types is associated with predictor variables in different ways. This study offers a guideline for future research, as well as insight into potential prevention strategies that might help prevent the most hazardous situation(s) from occurring in different collision types. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

Backover crashes cause considerable injuries especially among young children. Prior research on backover crashes has not assessed the joint effect of heavy vehicles and diminished light conditions on injuries. By analysing the United Kingdom STATS19 crash dataset from 1991 to 2020, this study focused on backover crashes involving paediatric cyclists or pedestrians aged ≤17 years and other motorised vehicles. By estimating the adjusted odds ratio (AOR) of multiple logistic regression models, pedestrians appeared to have 82.3% (95% CI: 1.78-1.85) higher risks of sustaining killed or serious injuries (KSIs) than cyclists. In addition, casualties involved in backover crashes with heavy vehicles were 39.3% (95% CI: 1.35-1.42) more likely to sustain KSIs than those involved in crashes with personal cars. The joint effect of heavy vehicles and diminished light conditions was associated with a 71% increased probability of sustaining KSIs (AOR = 1.71; 95% CI: 1.60-1.83). Other significant joint effects included young children (aged 0 to 5 years) as pedestrian (AOR = 1.92; 95% CI: 1.87-1.97), in diminished light conditions (AOR = 1.23; 95% CI: 1.15-1.31), and with heavy vehicle (AOR = 1.37; 95% CI: 1.28-1.47).

The study results serve as a reminder for parents, children, and drivers to be alert to the danger of traffic crashes on Halloween. The aim of this study was to examine whether Halloween is associated with a higher incidence of traffic injuries and whether traffic injuries sustained on Halloween are more severe than those sustained on other days. The U.K. STATS19 database, including the data of all road traffic crashes occurring from 1990 to 2017, was employed. A total of 73,587 pediatric traffic casualties (involving pedestrians, cyclists, and moped riders) were included. Between 17:00 and 19:00 (17:00~18:59) on Halloween, the number of casualties was higher than that on other public holidays and usual days. The logistic regression model revealed that, between 17:00 and 18:00 (17:00~17:59), the risk of being killed or seriously injured on Halloween was 34.2% higher (odds ratio = 1.342; 95% CI = 1.065-1.692) than that on other days. Pediatric crashes occurring on Halloween are associated with a higher number of injuries and increased injury severity.

Background: Research suggests that drivers tend to engage in risk-taking behaviours on public holidays. Studies that examined the association between holidays (or other special days) and fatal injuries are inconsistent. This study used UK STATS19 data to investigate the associations of nine public holidays on road crash casualties., Methods: This retrospective study assessed UK STATS19 crash data for 1990-2017. All casualties from two vehicle crashes were initially considered; subsequently, casualties with missing data were excluded. Multiple logistic regression was estimated to explore the associations of potential risk factors with the likelihood of killed or seriously injured (KSI) casualties and to calculate adjusted odds ratios (AORs)., Results: In total, 3,751,998 casualties from traffic accidents in the United Kingdom during 1990-2017 were included in the final data set; among these, 410,299 (10.9%) were KSI casualties, and 3,341,699 (89.1%) were slight injuries. Crashes on public holidays were 16% (AOR = 1.16; 95% confidence interval [CI] = 1.13-1.19) more likely to involve KSI casualties than were crashes on non-holidays. With other factors controlled for, crashes during the Queen's 2002 Golden Jubilee and on New Year's Day were 48% (AOR = 1.48; 95% CI = 1.06-2.07) and 36% (AOR = 1.36; 1.26-1.48) more likely to lead to KSIs, respectively., Conclusions: The proportion of crashes resulting in KSI casualties on public holidays was higher than that on non-holidays. Furthermore, crashes during the Queen's 2002 Golden Jubilee had the highest risk of KSI casualties followed by New Year's Day.