Combining driving performance information in an index score: a simulated curve-taking experiment

Abstract

This study investigated the relative performance of (car) drivers at the individual level, using data from a driving simulator, in order to identify the best drivers within the sample and to gain insight into the most problematic behavior of each driver. To this end, 38 participants varying in age and gender were enrolled to take part in a particular simulator scenario (i.e., curve taking) and their speed, acceleration and lateral position – the three most important driving performance indicators based on literature review – were monitored at various points (before, during and after the curve). As a widely accepted tool for performance monitoring, benchmarking and policy analysis, the concept of composite indicators (CIs), which combines single indicators into one index score, was employed, and the technique of data envelopment analysis – an optimization model for measuring the relative performance of a set of decision making units, or drivers in this study – was used for the index construction. Based on the results, all drivers were ranked, and best performers were distinguished from underperforming drivers. Moreover, by analyzing the weights allocated to each indicator from the model, the most problematic parameter (e.g., lateral position) and point along the curve (e.g., at curve end) were identified for each driver, leading to specific driver improvement recommendations (e.g., training programs).