Developing complex crash warning simulations for Human Factors evaluations
Authors: Paul Green.
In traditional vehicle warning experiments, each subject sees each warning once, and warning comparisons are between subjects, a very inefficient approach. Driving simulator experiments for the recent RDCW and IVBSS projects used within-subjects designs, with each subject responding to a warning about once per minute. That presentation rate and the scenarios developed seemed reasonable to independent Human Factors experts who experienced them and the simulations were often able to distinguish differences of interest. What made the simulations reasonable was (1) the use of real world crash data as a starting point for scenarios, (2) the large number of scenarios employed, each of which had both normal and crash-related outcomes, (3) the presence of three to five vehicles in the scene, each requiring the driver-s attention, (4) the use of real on-road data to select gaps, closing rates, etc., and (5) work-arounds when scenarios did not go according to plan. For developing and communicating the plan, option tables and storyboards were particularly useful.