Reducing drivers’ mental workload by means of an adaptive man–machine interface

Abstract

Modern in-vehicle information and communication devices are changing the nature of the driving task. Drivers take it for granted that they are able to divide their attention between the primary task of driving and secondary tasks like monitoring information displays or using mobile phones. While it is commonly accepted that driver information overload can compromise traffic safety, attempts to introduce attention management within the vehicle are nowadays limited to restrictive decisions by legislative bodies. In an increasing number of countries, the use of hands-free phones is enforced by law. In some countries, the use of phones while driving is prohibited altogether. We argue that there is a more intelligent solution to the information overload issue, namely an adaptive man–machine interface that filters information presentation according to situational requirements. We implemented such a filter as a projective real-time computational workload estimator which is based on the assessment of traffic situations detected from an on-board geographical database. Workload estimates are refined by data from sensors that monitor the traffic environment and variables of driving dynamics. The prototype system is operational in a demonstrator vehicle. Whenever the workload estimate exceeds a threshold value, incoming telephone calls are automatically redirected to the telephone mailbox without notifying the driver. An evaluation field experiment that employed objective and subjective methods of assessing workload yielded promising results in terms of the possibilities of reducing workload by means of the adaptive interface. The results are in favour of the idea of a futuristic, situation-aware vehicle which has the potential to enhance comfort and safety while driving.