International Conference · 2025

Lightweight Safety Assistance System for E-Scooters: Current Results and Future Directions

Congzhi Ren , Hamada Rizk , Tatsuya Amano , Hirozumi Yamaguchi

The 19th International Symposium on Spatial and Temporal Data. Doctoral Symposium. 2025.

Published Version (DOI)

DOI: 10.1145/3748777.3748804

Abstract

Electric scooters (e-scooters) are reshaping urban mobility, providing eco-friendly and cost-effective transport.However, the surge in their usage in mixed-traffic environments poses significant safety risks, especially for vulnerable road users (VRUs).This paper presents a lightweight vision-based safety assistance system optimized for real-time inference on edge devices.The core modules include semantic segmentation enhanced by semi-supervised learning, accurate bird's-eye view (BEV) transformation, real-time motion prediction, and adaptive path planning.Extensive evaluations demonstrate high segmentation accuracy and low-latency execution suitable for resource-constrained hardware.Future research directions include knowledge distillation for model adaptability, cooperative multi-scooter perception, intersection-based AI infrastructure, and the application of large language models (LLMs) to optimize urban traffic flows.

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