Modeling driver control behavior in both routine and near-accident driving

Building on ideas from contemporary neuroscience, a framework is proposed in which drivers’ steering and pedal behavior is modeled as a series of individual control adjustments, triggered after accumulation of sensory evidence for the need of an adjustment, or evidence that a previous or ongoing adjustment is not achieving the intended results. Example simulations are provided. Specifically, it is shown that evidence accumulation can account for previously unexplained variance in looming detection thresholds and brake onset timing. It is argued that the proposed framework resolves a discrepancy in the current driver modeling literature, by explaining not only the short-latency, well-tuned, closed-loop type of control of routine driving, but also the degradation into long-latency, ill-tuned open-loop control in more rare, unexpected, and urgent situations such as near-accidents.