Driving is an intermittent control task during which drivers manage their work across a number of driving and non-driving sub-tasks. The multitasking nature forces drivers to adopt situated safety margins (tolerances) in terms of time-headway (THW), time-to-collision (TTC), time-to-line-crossing (TLC), etc. Unacceptable situations (i.e., violations of safety margins defined here as events) are characterized by corrective maneuvers or actions. The frequency with which corrective actions are necessary (bandwidth), the hazard level of the situation that inspired these actions (performance), and the rate and magnitude of the responses to these situations (effort) provide a rich signature of how drivers manage their task(s). The authors hypothesize that drivers' perception of performance and effort are founded in the characteristics of experienced events. This is explored by comparing driving characteristics of bus drivers who drive on the shoulder of a highway with and without the support of a haptic lateral support system (LSS). Subjective performance and effort scores extracted from a usability questionnaire and objective ones from the event-based analysis show highly significant correspondence when comparing supported versus unsupported driving. This provides validating support for the adopted event-based approach. The proposed approach offers not only sensitive metrics of driver performance and effort to evaluate intelligent transportation system (ITS) applications but also explanatory power by exposing the various strategically different ways drivers are affected by these systems. This method of quantifying and analyzing driver data affords new opportunities to evaluate driver responses to ITS applications.
Abstract