A Machine Vision Approach for Geofence-based Adaptive Friction Modulation in Connected Semi-autonomous Vehicles

Authors

  • Ushaa Eswaran
  • Vivek Eswaran
  • Keerthna Murali
  • Vishal Eswaran

Keywords:

Geofence-based friction modulation, machine vision, semi-autonomous vehicles, vulnerable road users (VRUs), fail-safe velocity governance

Abstract

Safeguarding vulnerable road user (VRU) safety necessitates fail-safes preventing collisions from semi-autonomous vehicles. Geofencing allows service-zones definition but introduces friction discouraging adoption. This paper details an onboard vision model detecting VRUs by helmet status, triggering reactionary neuro-modulations of vehicle maneuverability. The architecture encompasses a YOLOv3 detector determining pedestrian/bicyclist crossing intent through path extrapolations, calibrated using lidar-fusion correcting distance estimates. The subsequent velocity governor adapts acceleration profiles based on predicted exposure risks, verified through hardware-in-loop testing. Ease-of-use implementations will encourage voluntary adoption of potentially life-saving technologies meeting pedestrian fatality reduction goals.

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Published

2023-12-21

Issue

Vol. 13 No. 3 (2023)

Section

Articles

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