Road Surface Detection for Autonomous Smart Wheelchair

Utaminingrum, Fitri; Mayena, Sri; Karim, Corina; Wahyudi, Slamet; Huda, Fais Al; Lin, Chih-Yang; Shih, Timothy K.; Thaipisutikul, Tipajin

doi:10.1109/wsce56210.2022.9916050

Cited by 1 publication

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“…Notably, the terrains navigated by wheelchairs tend to be more complex than conventional vehicular roads [7,10]. The human visual system excels at interpreting these terrain nuances, often surpassing the discernment of standard machine sensors.…”

Section: Introductionmentioning

confidence: 99%

Shared eHMI: Bridging Human–Machine Understanding in Autonomous Wheelchair Navigation

Zhang,

Song,

Huang

et al. 2024

Applied Sciences

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As automated driving system (ADS) technology is adopted in wheelchairs, clarity on the vehicle’s imminent path becomes essential for both users and pedestrians. For users, understanding the imminent path helps mitigate anxiety and facilitates real-time adjustments. For pedestrians, this insight aids in predicting their next move when near the wheelchair. This study introduces an on-ground projection-based shared eHMI approach for autonomous wheelchairs. By visualizing imminent motion intentions on the ground by integrating real and virtual elements, the approach quickly clarifies wheelchair behaviors for all parties, promoting proactive measures to reduce collision risks and ensure smooth wheelchair driving. To explore the practical application of the shared eHMI, a user interface was designed and incorporated into an autonomous wheelchair simulation platform. An observation-based pilot study was conducted with both experienced wheelchair users and pedestrians using structured questionnaires to assess the usability, user experience, and social acceptance of this interaction. The results indicate that the proposed shared eHMI offers clearer motion intentions display and appeal, emphasizing its potential contribution to the field. Future work should focus on improving visibility, practicality, safety, and trust in autonomous wheelchair interactions.

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Section: Introductionmentioning

confidence: 99%