title: The effects of vehicle model and driver behavior on risk.
abstract: We study the dependence of risk on vehicle type and especially on vehicle model. Here, risk is measured by the number of driver fatalities per year per million vehicles registered. We analyze both the risk to the drivers of each vehicle model and the risk the vehicle model imposes on drivers of other vehicles with which it crashes. The "combined risk" associated with each vehicle model is simply the sum of the risk-to-drivers in all kinds of crashes and the risk-to-drivers-of-other-vehicles in two-vehicle crashes. We find that most car models are as safe to their drivers as most sport utility vehicles (SUVs); the increased risk of a rollover in a SUV roughly balances the higher risk for cars that collide with SUVs and pickup trucks. We find that SUVs and to a greater extent pickup trucks, impose much greater risks than cars on drivers of other vehicles; and these risks increase with increasing pickup size. The higher aggressivity of SUVs and pickups makes their combined risk higher than that of almost all cars. Effects of light truck design on their risk are revealed by the analysis of specific models: new unibody (or "crossover") SUVs appear, in preliminary analysis, to have much lower risks than the most popular truck-based SUVs. Much has been made in the past about the high risk of low-mass cars in certain kinds of collisions. We find there are other plausible explanations for this pattern of risk, which suggests that mass may not be fundamental to safety. While not conclusive, this is potentially important because improvement in fuel economy is a major goal for designers of new vehicles. We find that accounting for the most risky drivers, young males and the elderly, does not change our general results. Similarly, we find with California data that the high risk of rural driving and the high level of rural driving by pickups does not increase the risk-to-drivers of pickups relative to that for cars. However, other more subtle differences in drivers and the driving environment by vehicle type may affect our results.
authors.affiliation: Lawrence Berkeley National Laboratory, 90R4000, 1 Cyclotron Road, Berkeley, CA 94720, USA; University of Michigan, Ann Arbor, MI 48109, USA. tpwenzel@lbl.gov
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Wenzel
authors.forename: Marc
authors.initials: M
authors.lastname: Ross
mesh_terms: D000063:Accidents, Traffic / Q000401:mortality*; D017677:Age Distribution; D001334:Automobile Driving / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D018986:Motor Vehicles / Q000145:classification* / Q000706:statistics & numerical data*; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D012424:Rural Population / Q000706:statistics & numerical data; D014481:United States / Q000453:epidemiology