Due to an increase in the use of cars and the growing complexity of driving situations, the number of people injured in traffic accidents has increased to 50 million. One of the most crucial factors contributing to accidents is driver’s behavior. A driver state which is known to provoke risky driver behavior is haste. Haste is defined as the state where the driver has feelings of urgency or pressure due to a lack of temporal resources. If it would be possible to automatically detect when a driver starts hurrying for being late for an appointment, this could be used to develop novel accident-prevention systems. The research reported on in this paper aims at exploring knowledge for the development and implementation of a car subsystem that can reliably detect driving in haste. Identification of indicators of haste has not received much attention in research so far. In this paper we present how we gathered the necessary knowledge and qualified indicators by contrasting the findings of a literature study with that of five focus group sessions, involving drivers and experts. These explorative studies have confirmed our assumption that haste not only manifests in changed human behavior, but it also influences human-car interaction, the state of the car and the car-environment interaction. Accordingly, we have sorted the proposed indicators into groups, and validated them from several aspects. This knowledge provides a good basis for the follow-up research cycles, in which we will test the strongest indicators, investigate the opportunities of detecting them within cars, and propose a technical solution for detecting driving in haste.

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