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Modeling microstructure of drivers' task switching behavior
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DOI：10.1016/j.ijhcs.2018.12.007.png)
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Abstract
En 中文
A computational model is created to simulate drivers' task switching behavior, or dynamic allocation of visual attention, while they are driving and engaging in a secondary task. The model takes the following into account: uncertainty about the roadway, task structure, and individual differences. The first factor, uncertainty, means a lack of information about the roadway that plays a significant role in switching attention back to the roadway. The second factor, task structure, reflects the driver's tendency to switch visual attention from the secondary task to the roadway at subtask boundaries as well as the tendency to continue to perform task to reach subtask boundaries. Lastly, the model considers the variability of performance speed across the driver population. The factors jointly influence the probability of switching attention in the model. We use the ABC-MCMC (Approximate Bayesian Computation-Markov Chain Monte Carlo) method to estimate model parameters that produce the microstructure of task switching. The fitted model generates glance patterns at a micro level that are consistent with those generated by participants in an experiment.
Keywords:
Driver distraction
Multitasking
Task switching
Computational modeling
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