Beyond Vision: Non-Visual Sensory Channels Assist Blind Passengers in Understanding Driving Environments and Vehicle Behavior

Abstract

In the context of the development of autonomous driving technology, the intelligent cockpit's ability to process information has gradually increased, becoming an important carrier for obtaining driving information and understanding the traffic environment. Unlike traditional human-computer interaction methods dominated by vision, this study focuses on how to provide blind people with relevant information on vehicle status and environmental changes through sensory channels such as touch and hearing during autonomous driving, in order to support their formation of basic cognition of driving situations. The research aims to explore the role of multimodal interaction methods in enhancing the perception ability and riding safety of blind people. The experiment focuses on constructing typical usage scenarios for 10 common scene elements in autonomous driving, using interactive methods such as tactile gloves and car machine prompts as the main sensory channels for transmitting information. By collecting data on users' situational perception ability, scene judgment accuracy, judgment grasp degree, etc., evaluate users' perception ability under different sensory channels. The results indicate that multimodal information feedback can significantly enhance the perception of blind people during autonomous driving, help them better understand vehicle behavior and driving status, and enhance their predictability of the system operation process, providing a reference design basis for barrier free interaction design for blind people in autonomous driving scenarios.

Keywords: Autonomous Driving Technology, Multi-channel Interaction, Situational Awareness, Barrier Free Travel, Non Visual Interaction

DOI: 10.54941/ahfe1008044