Vehicle and Driver At-Fault Comparisons
David B. Brown, PhD, P.E. firstname.lastname@example.org
Randy Smith, PhD email@example.com
Presented at the 40th International Traffic Safety Information Systems Conference
St. Louis, MO
October 27, 2014
This report illustrates some of the ways that CAPS turns data into information. One of the most critical bits of information in crashes that involve two different vehicles (or vehicles and pedestrians) is the issue of who is most often at-fault in these types of crashes. For example, if passenger vehicles are most often causing most car-truck crashes, the placing undue emphasis on the truck driver would waste resources. In all cases resources should be applied in both directions, but the question is: where should the major emphasis be placed?
The following give a brief explanation of the various vehicles, drivers and crash types that were compared:
Please note the norm. All other things being equal we should expect half of the crashes to be caused by one type of vehicle/driver and 50% to be caused by the other. This is only reasonable, since this assumes equal skill and integrity on both classes of drivers, so that the cause of any given crash becomes a 50-50 matter of chance. Obviously, it is not expected that any vehicle/driver type will cause all of the crashes. The following is one part of the study that illustrates that causation usually changes with the severity of the crash.
- Truck Involved – this compared heavy trucks, generally large commercial motor vehicles with passenger vehicles of all types. “Trucks” in this case would include all tractor trailer trucks and all vehicles larger than normal pick-up trucks.
- Pedestrians – this covered all crashes that involved pedestrians, answering the question of whether the pedestrian or the motor vehicle was typically at fault.
- Motorcycles – this considered all motorcycle crashes with other types of motor vehicles.
- Bicycles – comparable to the motorcycle analysis, but involving bicycles as opposed to motorcycles.
- Age 16-20 – all crashes where one of the drivers was in this age range.
- Age 65+ – all crashes in which one of the drivers was of an age greater than 64.
- Age 75+ – all crashes in which one of the drivers was of an age greater than 74.
- Male-Female – crashes that involved two vehicles, one driven by a male and the other by a female.
- School Bus – all crashes in which one of the vehicles was a school bus.
- Local or 25+ Miles – local drivers were considered to be within 25 miles of their homes, and these were compared with those more than 25 miles from home.
- Out of State Drivers – similar to the “local” comparison above, but in this case one driver had an Alabama driver’s license while the other had a license that was out of state.
- Changing Lanes – one driver was reported to be changing lanes while the other was not.
- Pickup vs Passenger Car – this was for all vehicles reported to be pickup trucks in a wreck with a passenger car.
Cars or Trucks?
The above analysis indicates strongly how fault can vary significantly by severity. This is the main reason that we have subdivide the results by severity. Typically the vehicle that is “of concern” will have the bar to the left (orange bar), which the one on the right will apply to all other vehicles or drivers. Note that the total for all severity classifications (and those of Unknown severity is given at the right. Important: no inference should be made about the relative severity of the different types of crashes below by the heights of the bars in the graph. The orange and the blue bars within every severity classification sum to 1.00 (100%). Thus it is impossible to derive any conclusions with regard to how many truck related fatalities (either absolutely or relatively) from these charts. See the final section of this report (Frequency of Crashes by Severity) for this information.
True or False? In fatal crashes between cars and trucks, it is the truck that is most often at fault? The chart below shows that this is false. Heavy trucks only caused about 22% of the fatal crashes in which they were involved. The general driving public has a sense that the truck causes the crash because of its size. No doubt the disparity in size between trucks and cars accounts for a higher fatality rate than what occurs in crashes between two vehicles of equivalent weight. However, this analysis was of who caused the crash in terms of driver errors (not what caused the severity to be so high). It is reasonable that professional drivers would have a higher driving skill level due to their experience. However, in the lower severity classification the heavy truck drivers are over-represented in causation. Perhaps this is due to their skill in mitigating the crash so that it will not cause a fatality. Clearly heavy trucks are much more difficult to control, and so there might be the natural expectation that they cause more two-vehicle crashes.