A Wizard-of-Oz Experiment: How Drivers Feel and React to the Active Interaction of AI Empowered Product in the Vehicle

• Published in: HCI in Mobility, Transport, and Automotive Systems Vol. 12791; pp. 382 - 400
• Main Authors: Huang, Qihao, Wang, Ya, Wang, Xuan, Lin, Zijing, He, Jian, Luo, Xiaojun, Wang, Jifang
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2021; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Active interaction; AI-empowered product; Driving; In-vehicle; Scenario-based recommendations; Wizard-of-oz
• ISBN: 9783030783570; 303078357X
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-78358-7_26

While driving, the drivers have to put their hands on the steering wheel and keep their eyes on the forward. Besides, the distance from the driver to the screen of the central control panel (center stack) of a vehicle is also limited, which lowers the precision of the interaction between drivers and the wireless communication, entertainment, and driver assistance systems in the vehicle. Fortunately, the idea of Active Interaction of AI-Empowered Product, which enables the systems to provide scenario-based recommendations, could be a solution, which is aiming to enhance the user experience of the interaction between the drivers and the systems in the vehicle during driving. So how could it be created to better meet the behavior habits of drivers? Twenty-four drivers were recruited as participants and were asked to give subjective evaluations about their satisfaction and the degree of disturbance of the scenario-based recommendation function. We simulated the AI Empowered Product, which provides a precise recommendation to meet the drivers’ needs in the vehicle through a Wizard-of-Oz Experiment, and explored factors which we proposed that may have an influence on the drivers feeling and reaction to the active interaction of AI-Empowered Product in the vehicle, including (a) the real-time traffic conditions outside, (b) the in-vehicle driver distraction, for instance, whether the driver was listening to music or not, (c) the content of the suggested information, and (d) different ways of information transmission. Furthermore, we also observed and analyzed the drivers’ reactions to the active interaction. With the ANOVAs of the satisfaction scores and the degree of disturbance evaluated by participants, combined with the analysis of the participants’ reactions, the results show that (a) regarding safety, drivers are not willing to accept recommendation during a traffic jam in which the drivers have to focus on the road conditions; (b) they are more reluctant to be bothered while listening to music; (c) they prefer to accept information that helps them boost driving efficiency (d) they like audio message best, because it is the most efficient way for them to acquire and understand the information, and it would be better if with the visual presentation, such as pictures, to improve the efficiency of information acquisition. Based on the experimental results and behavior analysis, we concluded suggestions for the product design process.