An examination of the increases in pedestrian motor-vehicle crash fatalities during 2009–2016

Hu, Wen; Cicchino, Jessica B.

doi:10.1016/j.jsr.2018.09.009

Cited by 67 publications

(43 citation statements)

References 24 publications

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“…Motor vehicle drivers 1150 14,599 9 [6,16] Motor cycle drivers 786 13,021 13 [8,21] Pedal cyclists 196 3042 11 [8,18] Pedestrians 365 5007 10 [6,18] Abbreviations: N = number, Q = Quartile.…”

Section: N Total Words Injury Event Description Median [Q1 Q3] Numbementioning

confidence: 99%

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

2021

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Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010–2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.

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Section: N Total Words Injury Event Description Median [Q1 Q3] Numbementioning

confidence: 99%

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

2021

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“…Several studies show that larger motor vehicles pose a much greater safety hazard for pedestrians and cyclists than smaller, conventional sedans (Anderson, 2008;Lefler & Gabler, 2004;Paulozzi, 2005;Sandt, 2018). The greater weight and higher, wider, blunter fronts of Sport Utility Vehicles (SUVs), pickup trucks, and minivans are more likely to cause severe injury and death in crashes with pedestrians and cyclists (Hu & Chiccino, 2018;Lefler & Gabler, 2004;Oikawa, Matsui, Nakadate, & Aomura, 2019;Wang, Wang, Otte, Han, & Peng, 2018). Such personal light trucks accounted for 72% of total new personal vehicle sales in the USA in 2018, compared to 27% in Denmark, 28% in the Netherlands, 36% in Germany, and 39% in the UK (Bieker, Tietge, Rodríguez, & Mock, 2019;ORNL, 2020).…”

Section: Vehicle Sizementioning

confidence: 99%

The growing gap in pedestrian and cyclist fatality rates between the United States and the United Kingdom, Germany, Denmark, and the Netherlands, 1990–2018

Buehler

Pucher

2020

Transport Reviews

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Using official national data for each country, this article calculates trends in walking and cycling fatalities per capita and per km in the USA, the UK, Germany, the Netherlands, and Denmark. From 1990 to 2018, pedestrian fatalities per capita fell by 23% in the USA vs. 66%-80% in the other countries; cyclist fatalities per capita fell by 22% in the USA vs. 55%-68% in the other countries. In 2018, pedestrian fatality rates per km in the USA were 5-10 times higher than in the other four countries; cyclist fatality rates per km in the USA were 4-7 times higher. The gap in walking and cycling fatality rates between the USA and the other countries increased over the entire 28-year period, but especially from 2010 to 2018. Over that 8-year period, per-capita fatality rates in the USA rose by 19% for pedestrians and 11% for cyclists; per-km fatality rates rose by 17% for pedestrians and 33% for cyclists. By comparison, fatality rates either fell or remained stable in the four European countries. We reviewed the relevant literature to identify factors that might help explain the much lower walking and cycling fatality rates in Europe compared to the USA. Possible explanatory factors include better walking and cycling infrastructure; lower urban speed limits; fewer vehicle km travelled; smaller and less powerful personal motor vehicles; and better traffic training, testing, and enforcement of traffic regulations. We recommend that the USA consider implementing an integrated package of mutually reinforcing safety measures such as those that have been successfully implemented in the Netherlands, Denmark, and Germany to reduce pedestrian and cyclist fatality rates.

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“…Since pedestrians do not have a vehicle’s structure to protect them, small increases in vehicle speeds have an especially large impact on the risk of a serious injury or fatality to a pedestrian involved in a crash 6. In the USA, pedestrian deaths overall rose by 46% from 2009, the lowest point, to 2016 and increased at a higher rate in urban areas (54%) 7. Over 70% of pedestrian deaths occurred in urban areas during 2009–2016.…”

Section: Introductionmentioning

confidence: 99%

Lowering the speed limit from 30 mph to 25 mph in Boston: effects on vehicle speeds

Cicchino

2019

Inj Prev

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IntroductionEffective 9 January 2017, the default speed limit on Boston streets was reduced from 30 mph to 25 mph. This study evaluated the effects of the speed limit reduction on speeds in Boston.MethodVehicle speeds were collected at sites in Boston where the speed limit was lowered, and at control sites in Providence, Rhode Island, where the speed limit remained unchanged, before and after the speed limit change in Boston. A log-linear regression model estimated the change in vehicle speeds associated with the speed limit reduction. Separate logistic regression models estimated changes in the odds of vehicles exceeding 25 mph, 30 mph and 35 mph associated with the lower speed limit.ResultsThe speed limit reduction was associated with a 0.3 % reduction in mean speeds (p=0.065), and reductions of 2.9%, 8.5% and 29.3 % in the odds of vehicles exceeding 25 mph, 30 mph and 35 mph, respectively. All these reductions were statistically significant.ConclusionsLocal communities should consider lowering speed limits to reduce speeds and improve safety for all road users. The current practice of setting speed limits according to the 85th percentile free-flow speeds, without consideration of other characteristics of the roadway, can be a hurdle for local communities looking to lower speed limits. Updated state laws that allow municipalities to set lower speed limits on urban streets without requiring costly engineering studies can provide flexibility to municipalities to set speed limits that are safe for all road users.

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An examination of the increases in pedestrian motor-vehicle crash fatalities during 2009–2016

Cited by 67 publications

References 24 publications

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

The growing gap in pedestrian and cyclist fatality rates between the United States and the United Kingdom, Germany, Denmark, and the Netherlands, 1990–2018

Lowering the speed limit from 30 mph to 25 mph in Boston: effects on vehicle speeds

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