Towards a framework of driver fitness

Abstract

Whereas driver fitness is widely recognized as a prerequisite for safety, the construct lacks a formal framework. We present the first steps towards its operationalization. We interpret availability and allocation of cognitive and physiological resources as fitness dimensions, and risk factors fatigue/drowsiness, distraction/inattention, intoxication, sudden incapacitation and speeding as state variables loading on these dimensions. We collect and synthesize US crash data, and calculate Relative Risks RR and Population Attributable Fractions AFp. Sudden incapacitation (RR = 32.112) is the most detrimental to individual safety, followed by alcohol intoxication (RR=11.277), fatigue/drowsiness (RR=4.966), speeding (RR=2.743), and inattention/distraction (RR=0.241). Taking into account prevalence, alcohol intoxication has the largest impact (AFp=0.068), followed by speeding (AFp=0.065), fatigue/drowsiness (AFp=0.059), incapacitation (AFp=0.013) and inattention/distraction (AFp=−0.416). Alcohol intoxication plays a major role in fatal crashes (RR=47.341, AFp=0.247), followed by speeding (RR=9.364, AFp=0.25). The analysis emphasizes the dangers of intoxicated driving and speeding, but also reveals shortcomings in census data, notably an under-representation of inattention, as well as the need for specific data collection on intoxication, reckless driving and sudden incapacitation in crashes. Taken together, the conceptual model and data synthesis provide a first step towards a framework of driver fitness; formalizing hypotheses on causal relations and providing crude estimates of factor loadings. This framework has practical applications as a model for multimodal driver monitoring systems, and to calculate risk factor impacts to inform policy makers.