Development of Advanced Rider Assistance Systems using Rider-in-the-Loop Simulators

This paper explores the development and testing of Advanced Rider Assistance Systems (ARAS) for motorcycles using Rider-in-the-Loop (RIL) simulators. Unlike conventional safety systems, ARAS utilize advanced sensors like radar and cameras for functions such as Blind Spot Detection and Adaptive Cruise Control, enhancing both safety and comfort. Developing ARAS presents unique challenges compared to car-based ADAS, primarily due to complex motorcycle dynamics, rider interaction, and the need to preserve riding pleasure. The research proposes shifting ARAS testing "left" in the development cycle by providing a robust motorcycle simulation environment and integrating a motorcycle simulator for early rider acceptance tests. Key advancements include a 12-degree-of-freedom multibody system for realistic motorcycle dynamics and an extended lateral controller accounting for rider body movement. Initial simulation results demonstrate the impact of motorcycle-specific behaviors (e.g., rolling, pitching) on sensor performance in ARAS scenarios like Autonomous Emergency Braking. Furthermore, initial RIL simulator tests showed realistic motorcycle behavior without causing simulator sickness, confirming the potential of this approach for early-stage ARAS validation.