Modeling the development of vehicle lateral control skills in a cognitive architecture

• Compared driving performances of non-drivers, novices, and experienced drivers.
• Performance increased with driving experience.
• An ACT-R model simulated the progress of lateral control skill learning.
• The modeling results were similar to the human data.

The development of lateral control skills is crucial to driving safety. The current study examined a computational method using a cognitive architecture to model the learning process of vehicle lateral control. In a fixed-base driving simulator, an experiment compared the lateral control performance of non-drivers, novices, and experienced drivers. A cognitive model using Adaptive Control of Thought-Rational (ACT-R) was built to model the learning process of lateral control skills. The modeling results were compared with the human results. The drivers with more experience had better lateral control performance. The model produced similar results as the human results and modeled the progress of learning. The model provided a computational explanation for the mechanisms of lateral control skill learning. Implication and future studies were discussed.