Research on interaction optimization methods for AR games in autonomous driving: Based on contextual awareness and virtual avatar design

Abstract

With the continuous development of artificial intelligence and autonomous driving technology, cars are transitioning from traditional transportation to user-centered intelligent mobile spaces. In order to enhance drivers’ road safety awareness and entertainment experience, this study explores the design of multi-modal games in smart cockpits in the context of L3-L4 autonomous driving based on the theory of Situation Awareness (SA). First, using SA and KANO models, key scenarios and design elements are identified, and a method combining context-awareness and avatar design is proposed. Second, typical driving scenarios are identified through user interviews and evaluation scales, and experimental studies are conducted to analyze and refine the multi-modal game interaction information in the smart cockpit environment. Finally, based on Pokémon-style, an AR game design solution suitable for a smart cockpit was developed. The 2 (with and without game interaction) × 4 (vision, vision + hearing, vision + touch, vision + hearing + touch) mixed factorial experimental design was designed, and the proposed design scheme was evaluated using a driving simulator. The experimental results demonstrate that the game interaction design for L3-L4 autonomous driving conditions significantly enhances driver perception of road and environmental information, reduces reaction time in emergencies, improves user experience, and increases trust in the autonomous driving system compared to the non-game interaction design.