Task Decomposition for Learning Advanced Driving Skills

The introduction of drive-by-wire systems and advances in vehicle automation have enabled new possibilities of what a vehicle can do. Research has pushed vehicle automation to a level that only skilled drivers can achieve in racing and drifting, and decoupled systems can act as a guardian, protecting the driver in extreme situations. Introducing these systems has the potential to improve safety of the car and driver combined system, but could also lead to deskilling and over-reliance by the driver. This manuscript presents an approach to address this through leveraging task decomposition to teach advanced driving skills, namely drifting a circular donut. Using Model Predictive Control, task decomposition is achieved by allowing drivers to learn steering and throttle control independently, enabling the driver to isolate learning individual skills to enhance skill acquisition. A user study was conducted with 11 participants to experimentally validate the approach. Results reflect that the group subject to task decomposition demonstrated enhanced mastery of the skill.