A statistical look at gender and age differences as related to the injury crash type on low-volume roads

The research presented here is addressed to develop only one safety performance function (SPF) from the perspective of driver gender for three identified main crash types (head-on/side collisions, rear-end collisions, single-vehicle run-offroad crashes) that is able to predict the injury crash rate on low-volume roads. According to the crash police reports, it came in sight that males and females differ in terms of their psychological attributes and, consequently, their response to the crash risk can change producing different effects on the severity. The analysis was divided into two phases: the first deals with SPF calibration, while the second concerns SPF validation. A total length of 355 km was used in the first phase involving 5 years of the crash database (2003–2007), to a total of 95 injury crashes which led to 136 injuries (63% male only drivers, 8% female only drivers and 29% female+male drivers) and 9 deaths (78% male only drivers and 22% female+male drivers). A total length of 295 km was used in the second phase involving 3 years of the crash database (2008–2010), to a total of 73 injury crashes which led to 120 injuries (68% male only drivers, 4% female only drivers and 28% female+male drivers) and 4 deaths (75% male only drivers and 25% female+male drivers). GEE was adopted to calibrate SPF. Mean width, mean speed at each analyzed road segment, and a numerical variable “SLEH” reflecting the identified road “Surface” (dry/wet), “Light” conditions (day/night), geometric “Element” (tangent segment/circular curve) and “Human” factors (gender/age/number drivers) all together when the crash happened, were introduced in the predictive safety model looking toward gender and age drivers.