Towards Vehicular Cloud Computing for Assistive Navigation: A Wireless Collaborative Vision Prototype

Helping visually impaired users navigate an athletic track for running is a challenging task that requires a highly reliable, low-latency, real-time navigation system. In this study, we propose a vision-based assisted navigation framework that integrates a camera, a tactile feedback belt, and a computing unit (either an external computer or an on-board embedded device) to detect the running lane and provide real-time directional guidance along the track. Our preliminary experiments relied on a direct Wi-Fi connection between the sensing and processing units. However, the system exhibited severe latency issues and bandwidth limitations, which prevented it from operating effectively in real-time conditions. To overcome these challenges, we propose leveraging vehicular cloud computing as a communication and processing backbone. This approach is expected to significantly reduce latency, improve scalability, and enable more robust real-time navigation assistance for visually impaired runners.