Effects of affective states on driver situation awareness and adaptive mitigation interfaces: focused on anger

Abstract

Research has suggested that affective states have critical effects on various cognitive processes and performance. Evidence from driving studies has also emphasized the importance of driver situation awareness (Endsley, 1995b) for driving performance and safety. However, to date, no research has investigated the relationship between affective effects and driver situation awareness. Two studies examined the relationship between a driver's affective states and situation awareness. In Experiment 1, 30 undergraduates drove in a simulator after either anger or neutral affect induction. Results suggested that an induced angry state can degrade driver situation awareness and driving performance more than the neutral state. Interestingly, the angry state did not influence participants' perceived workload. Experiment 2 explored the possibilities of using an "attention deployment" emotion regulation strategy as an intervention for mitigating angry effects on driving, via an adaptive speech-based system. 60 undergraduates drove the same scenario as in Experiment 1 after affect induction with different intervention conditions: anger with no sound; anger with the ER system: directive/ command style emotion regulation messages; anger with the SA system: suggestive/ notification style situation awareness prompts; or neutral with no sound. Results showed that both speech-based systems can not only enhance driver situation awareness and driving performance, but also reduce the anger level and perceived workload. Participants rated the ER system as more effective, but they rated the SA system as less annoying and less authoritative than the ER system. Based on the results of Experiment 2, regression models were constructed between a driver's affective states and driving performance, being mediated by situation awareness (full mediation for speeding and partial mediation for collision). These results allow researchers to construct a more detailed driver behavior model by showing how an affective state can influence driver situation awareness and performance. The practical implications of this research include the use of situation awareness prompts as a possible strategy for mitigating affective effects, for the design of an affect detection and mitigation system for drivers.