Intentional Abuse Avoidance System (IAAS)

Abstract

Shared micro-mobility vehicles, particularly e-scooters, have become increasingly popular in urban areas, leading to a notable rise in usage and associated accidents. This study explores the development of an anti-abuse system designed to detect and mitigate skidding and burnout behaviors in e-scooters to enhance rider safety and reduce wear and damage. Utilizing Hall effect sensors on both wheels, the system detects differences between normal riding, standstill, skidding, and burnout scenarios, notifying riders through visual and auditory signals when skidding. The project involved prototyping with 3D-printed mounts for sensors, developing software for controls and conducting tests to assess system reliability. Results showed effective detection capabilities, although the system experienced a number of “false positives”, which could impact user trust. Enhancements in sensor accuracy and data processing are proposed to address these issues. The study demonstrates the feasibility of implementing a cost-effective anti skid system for e-scooters, contributing to improved rider compliance and overall safety in the growing micro-mobility sector.