Travel speed and the risk of serious injury in vehicle crashes.

While there is a large quantity of prior research on speed and road safety, no previous studies have quantified the absolute risk of serious injury in a crash relative to travel speed. This study aimed to produce risk curves that relate travel speed to the risk of serious injury in light vehicle impacts in order to contribute to the process of selecting acceptable travel speeds. Serious injury was defined in this study as any injury having a maximum abbreviated injury scale (MAIS) of three or greater, or a fatal injury (MAIS3+F). In the context of a crash, travel speed is defined as the vehicle's speed before the driver reacts to the crash situation. Travel speed was determined by selecting the highest pre-impact speed recorded by an Event Data Recorder (EDR) in the seconds before the crash. A total of 1,618 light vehicle impacts were analysed using logistic regression. Individual risk curves were produced for front, head on, side, rear and single vehicle impacts. The analysis found significant positive relationships between the risk of serious injury and travel speed for all of these impact types. The travel speeds at which the risk of serious injury reached one per cent were 63 km/h across all impacts, 17 km/h for head on impacts, 48 km/h for single vehicle impacts, 58 km/h for side impacts, 81 km/h for front impacts and 96 km/h for rear impacts. These results have implications for the setting of speed limits and other measures that influence the speed at which vehicles travel.

Impact speed and the risk of serious injury in vehicle crashes.

The current guiding philosophies in road safety have stated aims of zero deaths and serious injuries. Speed has previously been highlighted as a key factor in the outcome of a crash but the literature to date has yet to provide a robust relationship between impact speed and the risk of serious injury for crashes other than pedestrian crashes. This study aimed to determine the relationship between impact speed and the risk of serious injury in light vehicle crashes. Crash data from the US based National Automotive Sampling System - Crashworthiness Data System collected from 2011 to 2015 were used in the analysis when there was a known impact speed from an event data recorder (EDR) and a known injury outcome. The analysis was conducted at the vehicle level. Data from a total of 1274 vehicles were used in logistic regressions, with the presence or absence of a serious injury as the binary dependent variable, and impact speed as the continuous independent variable. Individual risk curves were produced for front, side, rear and head on impacts. Impact speed was found to have a highly significant positive relationship to risk of serious injury for all impact types examined. The risk of serious injury reaches 1% at 28 km/h for head on impacts, 51 km/h for side impacts, 64 km/h for front impacts, and 67 km/h for rear impacts. The results emphasise the importance of measures that reduce impact speeds, be they road designs, vehicle technologies or enforced speed limit reductions, and highlight the need to prevent head on impacts.

Trends in the crash involvement of older drivers in Australia.

Research from the USA and Great Britain indicates that the number of fatal crashes (as well as the rates of crashes of all levels of injury and property damage) involving older drivers declined between approximately 1997 and 2010 despite increases in the number of older drivers on the road and in their driving exposure. Differing results have been found in Australian research with the number of older driver fatalities having been steady and even slightly increasing between 2004 and 2013. The present study further examined trends in the crash involvement of older drivers in Australia to determine whether their involvement has been increasing or decreasing, and how this compares to trends for younger aged drivers. Crash, injury, population and licensure data were examined by age group for the years 2003-2012. There were increases in the population and licensure of drivers aged 65 years and older, while the total crashes, serious injuries, and fatalities remained steady for drivers aged 65-84 and increased for the oldest group (85+) between 2003 and 2012. Increasing trends were also found for drivers 85 and older for rates of serious or fatal injuries per head of population and per licensed driver. Population and licensure among younger age groups also increased but their crash numbers and crash rates remained steady or declined. The stable or slightly increasing fatal crash involvement of older drivers in Australia contrasts with the declining trends in the USA and Great Britain. Therefore, greater attention should be given to the road safety of older drivers in Australia.

A trial of retrofitted advisory collision avoidance technology in government fleet vehicles.

In-vehicle collision avoidance technology (CAT) has the potential to prevent crash involvement. In 2015, Transport for New South Wales undertook a trial of a Mobileye 560 CAT system that was installed in 34 government fleet vehicles for a period of seven months. The system provided headway monitoring, lane departure, forward collision and pedestrian collision warnings, using audio and visual alerts. The purpose of the trial was to determine whether the technology could change the driving behaviour of fleet vehicle drivers and improve their safety. The evaluation consisted of three components: (1) analysis of objective data to examine effects of the technology on driving behaviour, (2) analysis of video footage taken from a sample of the vehicles to examine driving circumstances that trigger headway monitoring and forward collision warnings, and (3) a survey completed by 122 of the 199 individuals who drove the trial vehicles to examine experiences with, and attitudes to, the technology. Analysis of the objective data found that the system resulted in changes in behaviour with increased headway and improved lane keeping, but that these improvements dissipated once the warning alerts were switched off. Therefore, the system is capable of altering behaviour but only when it is actively providing alerts. In-vehicle video footage revealed that over a quarter of forward collision warnings were false alarms, in which a warning event was triggered despite there being no vehicle travelling ahead. The surveyed drivers recognised that the system could improve safety but most did not wish to use it themselves as they found it to be distracting and felt that it would not prevent them from having a crash. The results demonstrate that collision avoidance technology can improve driving behaviour but drivers may need to be educated about the potential benefits for their driving in order to accept the technology.

Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types.

OBJECTIVE: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data. METHOD: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels. RESULTS: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes. CONCLUSIONS: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.

Semiquantitation of Axonal Injury in Traumatically Damaged Brains Using Color Deconvolution.

INTRODUCTION: In traumatic brain injury biomechanics, macroscale biomechanical events need to be correlated with microscale neuropathologic changes and improved quantitation of microscopic axonal injury is an essential component of lesion evaluation. OBJECTIVES: To develop a novel technique for automatically identifying injured amyloid precursor protein immunopositive axons and aggregating these observations over a macroscopic brain dissection. METHODS: A color deconvolution method was adapted into Matlab to identify clusters of pixels with colors typical of amyloid precursor protein positive tissue from large-scale brain dissection. RESULTS: The methodology is demonstrated in the brain of a sheep subjected to a controlled cortical indentation. CONCLUSIONS: The technique will be of interest to pathologists and bioengineers seeking to quantitate brain injury over macroscales.