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Study of Human Steering Tasks using a Neuromuscular Driver Model

The aim of this work is the creation of a realistic driver model to help develop new technologies to aid drivers in the execution of their driving tasks. A realistic driver model can reduce the time-consuming trial and error process of designing products, and thereby reduce the vehicle’s development time and cost. The overall goal of this research is to develop an interface between driver and vehicle for designing Electric Power Steering (EPS) controllers that can account for the driver’s characteristics and preferences. To develop such an interface, a predictive driver model is utilized to estimate the steering wheel angle required to follow a desired path. To provide a physiologically realistic steering manoeuvre, a musculoskeletal arm model considering the neuromuscular system is included in the driver model. This driver model can provide insights into task performance and energy consumption of the driver, including fatigue and co-contraction dynamics of a steering task. In addition, this driver model in conjunction with a high-fidelity steering model can be used to develop new steering technologies such as EPS and lane keeping.