Modelling Braking and Steering Avoidance Maneuvers for Micromobility

Recent advancements in technology make it possible for advanced driving assistance systems (ADAS) to recognize micromobility vehicles (MMV) and include them in their threat assessment. However, today we lack the rider-vehicle models which are of great importance in understanding the interconnection between the MMV and its rider. These models may help ADAS predict micromobility kinematics and provide accurate threat assessments, especially when avoidance maneuvers from micromobility must be considered. In this study, we modelled avoidance maneuvers from micromobility vehicles to support ADAS threat assessment. We compared traditional bicycles (with and without assistance) with e-scooters (a small personal scooter and a large scooter) in a field test, where 36 participants avoided a stationary obstacle by either braking or steering. Kinematic data such as longitudinal and latera speed, acceleration, jerk and steering angle and rate were collected and analyzed.