A controlled riderless bicycle is desired for the purpose of testing autonomous vehicles ability to detect and recognise cyclists. The bicycle, which is a highly unstable system with complex dynamics have been subject to research for over a century, and in the last decades, controllers have been developed for autonomous bicycles. The controllers are often only evaluated in simulation, but some complex controllers have been developed on real-life bicycles as well. The goal of this work is to validate sensors and subsystems of an instrumented bicycle and to develop a robust controller which can balance a bicycle by using actuation on the steering axis alone. Using an iterative design process, the sensor measuring the lean angle and the steering system are improved and validated. By sensing the lean angle, the handlebar is manipulated to make the bicycle stable. For this purpose, a P, PD, two different PID, an LQR and a fuzzy controller are developed, evaluated and compared. The results show that the bicycle can ride without human interaction on a bicycle roller in different velocities. Additionally, numerous experiments are conducted in an outdoor environment in several different terrains, where the proposed control structure manages to balance and steer the bicycle.

A conventional bicycle is a stable system given adequate forward velocity. However, the velocity region of stability is limited and depends on the geometric parameters of the bicycle. An autonomous bicycle is just not about maintaining the balance but also controlling where the bicycle is heading. Following paths has been accomplished with bicycles and motorcycles in simulation for a while. Car-like vehicles have followed paths in the real world but few bicycles or motorcycles have done so. The goal of this work is to follow a planned path using a physical bicycle without overcoming the dynamic limitations of the bicycle. Using an iterative design process, controllers for direction and position are developed and improved. Kinematic models are also compared in their ability to simulate the bicycle movement and how controllers in simulation translate to outdoors driving. The result shows that the bicycle can follow a turning path on a residential road without human interaction and that some simulation behaviours do not translate to the real world.