In recent years, researchers from both academia and industry have worked on connected and automated vehicles and they have made great progress toward bringing them into reality. Compared to automated cars, bicycles are more affordable to daily commuters, as well as more environmentally friendly. When comparing the risk posed by autonomous vehicles to pedestrians and motorists, automated bicycles are much safer than autonomous cars, which also allows potential applications in smart cities, rehabilitation, and exercise. The biggest challenge in automating bicycles is the inherent problem of staying balanced. This paper presents a modified electric bicycle to allow real-time monitoring of the roll angles and motor-assisted steering. Stable and robust steering controllers for bicycle are designed and implemented to achieve self-balance at different forward speeds. Tests at different speeds have been conducted to verify the effectiveness of hardware development and controller design. The preliminary design using a control moment gyroscope (CMG) to achieve self-balancing at lower speeds are also presented in this work. This work can serve as a solid foundation for future study of human-robot interaction and autonomous driving.
The dynamic model of a four control moment gyroscope system