A Trajectory Optimisation Approach for Motorcycles

Trajectory planning and optimisation for motorcycles is an underdeveloped area in autonomous vehicle research. The Kinematic Bicycle Model (KBM) is popularly studied as a tool for path planning, trajectory optimisation and control in autonomous vehicle applications. However, due to the nonminimum phase properties of motorcycle systems, it is unsuitable as a model for path planning in motorcycles. As such, this paper presents an alternative trajectory planner, that makes use of a reduced order model approximation of the motorcycle dynamics to express the trajectory optimisation problem as a quadratic program that may be efficiently solved. This planner includes the nonminimum phase behaviour of motorcycles and enforces the dynamic constraints needed for safety guarantees. Tracking accuracy is assessed in a detailed non-linear motorcycle simulation, which shows a reduced root mean square error of 0.386m compared to 1.091m when using a planner based on KBM. Successful collision avoidance is also achieved when tracking, unlike when using the KBM planner. This provides a proof of concept for future research into real-time trajectory optimisation and planning for motorcycles.