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Accident Data Analysis to Develop Target Groups for CountermeasuresMonash University Accident Research Centre - Reports 46 & 47 - 1992 Author: M. Cameron Full report in .pdf format - Volume 1: Methods and conclusions [3.1MB] + Volume 2: Analysis reports [10.8MB] Abstract:The general objective of the project was to disaggregate the road accident problem using mass accident data to find groups of road users, vehicles and road segments which would he suitable targets for countermeasures. Large data files of Police accident reports and Transport Accident Commission claims from accidents in Victoria during the 1980's were obtained and merged. Four methods of analysis to meet the objective were developed and applied to the data to address one or more key problem areas. Target groups for countermeasures were identified and, where possible, accident and injury mechanisms were suggested, and countermeasures to address these mechanisms were proposed. Volume 1 covers the specific objectives, concepts, data, methods, conclusions and recommendations of the project, as well as the Executive Summaries of the analysis reports. The full analysis reports are given in Volume 2. The conclusions recommend that new surveys of the on-road exposure of drivers, passengers, motorcyclists and pedestrians be conducted in Victoria. It is also recommended that clustering methods be applied to other key road trauma problem areas as a matter of priority, as these methods are able to identify new target groups which are currently hidden. Executive SummaryIntroductionAn important issue which emerged during the development of the 1991 Road Safety Strategy for Victoria was the need for new and better definitions of target groups for countermeasures. Research to define new target groups has not kept up with the rapid implementation of countermeasures. This report describes a major project which aimed to further develop methods of identifying target groups, and to demonstrate those methods by application to a number of key road safety problems. The general objective was to disaggregate the road accident problem using mass accident data to find groups of road users, vehicles and road segments which would be suitable targets for countermeasures. However this project was confined to identifying target groups and potential countermeasures. It has not considered fully the range of problems in the implementation of such countermeasures nor the expected benefits and costs. This would be a necessary next step. Successful development of a countermeasure requires a clear understanding of where it can potentially break the chain of events leading to traumatic injury on the road. A countermeasure is a measure which attempts to break the road trauma chain before one of the undesirable steps can occur (eg. accident involvement, injury or death). A target group for a countermeasure is a group of entities (humans, vehicles or roads) for which the chain can be broken effectively and, desirably, cost-effectively. Methods and DataMass accident data needs to be analysed to find target groups for countermeasures in a way which maximizes the chances that the countermeasure will be cost-effective. The study has developed general principles for analysis which meet this aim. These have led to four specific methods of mass data analysis, depending on the nature of the road trauma problem being addressed in the search for countermeasure target groups, namely:
Large data files of Police accident reports and Transport Accident Commission claims from accidents in Victoria during the 1980's were obtained and merged. The four methods have each been applied to the data to address one or more key problem areas. Target groups for countermeasures were identified and, where possible, accident and injury mechanisms were suggested, and countermeasures to address these mechanisms were proposed. As each was completed, the analysis reports were sent to MUARC's baseline sponsors for comments and immediate use, if appropriate. The final versions of these reports are included in Volume 2 of the project report (available on request). Volume 1 covers the methods and conclusions of the project, as well as including Executive Summaries of the analysis reports. The major findings of the analysis reports are summarised below. Articulated TrucksArticulated trucks have a high risk of casualty accident involvement compared with other types of trucks. An earlier study showed that in Australia, articulated trucks were involved in 7.4 fatal accidents per 100 million kilometres travelled, compared with an involvement rate of 1.7 for rigid trucks. Semi-trailers and their drivers were substantially over-involved in a large number of specific crash circumstances compared with rigid trucks. Many of these over-involvements were potentially explainable by the truck size and load mass differences, and by the different usage patterns of semi-trailers (relatively greater use on rural highways, in the highest speed zones, and at night). However the following factors associated with substantial over-involvements of semi-trailers are apparently not fully explainable by the above differences between the two vehicle types:
These factors represent target groups for potential countermeasures to address the high over-involvement rate of articulated trucks in casualty crashes. These countermeasures could address the crash involvement of articulated trucks, and/or also the risk of severe injury to the truck driver and other road users involved, as there appear to be high risk factors operating in both stages which influence whether a casualty crash occurs. Cars Struck by Heavy VehiclesOccupants of passenger cars struck by heavy vehicles frequently sustain much higher severity injuries compared with car occupants struck by other types of vehicle. Injured car occupants are four to seven times more likely to be killed when the striking vehicle is a heavy vehicle, compared with being struck by another car. Higher injury seventies were observed in the higher speed zones and when the heavy vehicle was a semi-trailer. A large number of other environmental, crash, occupant, vehicle and impact factors were also found to be related to higher levels of injury severity of the car occupants. These factors define target groups for countermeasures which should be designed to reduce injury severity, with priority given to severity reduction in the specific circumstances and characteristics of the target group. The target groups also define car/truck crash types and circumstances which should be priority areas for countermeasures aimed at preventing collisions involving trucks. An exponentially increasing relationship between injury severity and the truck to car mass ratio was found. The analysis also found that nearly 40% of car occupants killed or seriously injured in car/truck collisions resulted from front to front impacts. Some 60% of these collisions involved impacts with the front corners of the truck, with more than half of these corner impacts being to the right front corner. A priority area for a countermeasure to reduce car occupant injury severity is improved frontal structures of trucks, especially the front corners outside the frame side members and especially the right front corner. There are developments in Europe to improve the front corners of trucks by structures which absorb energy and also reduce over-ride of the struck car in off-set front to front impacts. A study of these developments has recently been completed by MUARC. MotorcyclistsA number of target groups for the motorcycle accident problem were identified by finding sub-groups which were over-involved in the following crash situations which previous research had shown to be of high risk: novice motorcyclists, motorcyclists on curves, and intoxicated motorcyclists. Further target groups were added by identifying sub-groups which were associated with higher injury severity than the overall average for all injured motorcyclists. The target groups were reviewed collectively and mechanisms for the crashes or injuries occurring were suggested. This in turn led to a number of potential countermeasures for motorcyclist trauma, which included the following: 1. Random breath testing supported by publicity emphasising the focus on motorcyclists, during the "alcohol times" (and slightly earlier) on weekends in Spring and Summer, targeting riders of the larger and older motorcycles, and including licence checks. The problem is greatest for motorcyclists operating in residential areas of Melbourne and in rural areas outside towns. 2. A curve treatment program aimed at motorcycle accident black spots on curves, involving warning signs, improved skid resistance and super-elevation, increased roadside recovery areas and the removal or shielding of fixed objects. As part of the cost-benefit assessment of this proposal, an investigation is needed of the extent to which such curves are also accident black spots for other vehicles. 3. Visible mobile police patrols and stationary enforcement of speeding and BAC levels, located in the residential streets of the outer suburbs of Melbourne. 4. (a) Inclusion or increased emphasis in the motorcycle pre-licence testing manual of the dangers due to the low conspicuity of motorcycles, and the need to compensate for braking difficulties while gaining experience 4. (b) Adding a higher speed curve negotiation test to the skills test for a Probationary motorcycle licence 5. A requirement that motorcycles be operated with front headlamps alight at all times. Intoxicated PedestriansPrevious research has shown that there is a 15 times higher risk of serious injury for pedestrians who are intoxicated (ie. those with a BAC above 0.15) compared with those who are sober. Sub-groups of intoxicated pedestrians who were substantially over-involved in accidents compared with sober pedestrians were identified as suitable targets for countermeasures. The mechanisms explaining the over-involvement of each target group were suggested. The target groups could be addressed through VIC ROAD's existing Pedestrian Safety Program. The focus of each of the three program strategies aimed at intoxicated pedestrians should include: Strategy 1: To prevent pedestrians reaching high blood alcohol levels
Strategy 2: To prevent intoxicated pedestrian exposure
Strategy 3: To reduce intoxicated pedestrian risk
Elderly PedestriansElderly pedestrians aged 60 and above have a high rate of casualty accident involvement which reaches three times the rate of younger adults for pedestrians aged in the mid-70's. Injury severity also increases with age, with pedestrians aged 65 and above having substantially higher rates of death or hospitalisation when injured in accidents. Very few factors were found to be related to the over-involvement of the elderly pedestrians. However, a large number of factors were found to be related to the injury severity of pedestrians aged 65 and above who were killed or injured during the same period. These factors define sub-groups of the elderly pedestrian accident problem which should be target groups for countermeasures. The target groups related to substantially higher injury seventies were examined and mechanisms to explain their accident involvement or high severity were suggested. The target groups should be addressed through countermeasures in four general categories, with the focus in each category being as follows: Category 1: Education of elderly pedestrians
Category 2: Education of drivers
Category 3: Enforcement of driving offences
Category 4: Road engineering
Speeding DriversDrivers involved in serious casualty accidents were categorised into three populations of crashes considered likely to be speed related :
Eight large clusters of drivers were found within Population 1 and six large clusters for each of both Populations 2 and Population 3. For each population, the corresponding clusters together represented at least 70% of the total drivers involved in a speed related accident type. The drivers in Population 1 were involved in most of their accidents on rural roads (52%) compared with the drivers in Populations 2 and 3 (12% and 6%, respectively). These two populations of drivers were more frequently involved in accidents in the inner and middle areas of the Melbourne Statistical Division (MSD). Population 1 drivers were also more likely to be aged 18-25 (52%), have a BAC above zero (43%), to crash at night (55%) or on wet roads (32%), and to drive older cars (48% more than ten years old) than the other populations. The largest cluster in Population 1, representing 21% of the total drivers running off the road on curves, was:
The largest cluster in Population 2, representing 31% of drivers hitting another vehicle in the rear, was:
The largest cluster in Population 3, representing 29% of drivers hitting pedestrians resulting in death or serious injury, was
Speed enforcement supported by mass media publicity, if focussed on the identified clusters and aimed at deterring excessive speeding behaviour, would be expected to be effective. Unrestrained OccupantsOccupants of cars and station wagons involved in crashes and considered by the recording Police officer to be unrestrained were clustered into homogeneous groups to form the basis of countermeasures. The occupants were clustered on the basis of their age, sex, and seating position, and the time of day, day of week, speed zone and location of the crash. The seven largest clusters covered 69% of the unrestrained occupants. The total group of unrestrained occupants were 58% male and spanned all age groups with 39% aged 17 to 25. Drivers represented 41%, left front passengers 26% and rear passengers 32% of the total. 61% crashed in speed zones up to 75 km/h, and 63% of their crashes occurred in the Melbourne Statistical Division (MSD) while 28% occurred on the open road in rural areas. Weekdays accounted for 62% of the unrestrained occupants, while 59% were involved in crashes during daytime. The two largest clusters, which together covered 24% of the unrestrained occupants, were both mostly drivers crashing in speed zones up to 75 km/h, but they differed in other characteristics. The largest cluster mostly crashed at night and more often at weekends than the total group of unrestrained occupants. The second largest cluster were mostly male occupants and mostly crashed during the day. In other respects, these two clusters resembled the total group of unrestrained occupants. The other five identified clusters each covered 8-10% of the unrestrained occupants. Each differed from the total group in relatively unique ways, but the clusters were homogeneous in themselves. Each of these clusters provide suitable targets for integrated enforcement and publicity aimed at encouraging restraint use. Countermeasures which aim at reducing the impact severity or preventing the crash involvements of each of the cluster groups should also be considered. Sponsoring Organisation: Baseline Research Program - Australian Road Research Board, Department of Justice, Transport Accident Commission, Royal Automobile Club of Victoria (RACV) Ltd, VicRoads |