Driving Simulator Validation for Speed Research Stuart T. Godley, Thomas J. Triggs, Brian N. Fildes...
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Transcript of Driving Simulator Validation for Speed Research Stuart T. Godley, Thomas J. Triggs, Brian N. Fildes...
![Page 1: Driving Simulator Validation for Speed Research Stuart T. Godley, Thomas J. Triggs, Brian N. Fildes Presented By: Ben Block Wen Lung Hii.](https://reader036.fdocuments.in/reader036/viewer/2022062600/5a4d1ba77f8b9ab0599c97a8/html5/thumbnails/1.jpg)
Driving Simulator Validation for Speed Research
Stuart T. Godley, Thomas J. Triggs, Brian N. Fildes
Presented By:Ben Block
Wen Lung Hii
![Page 2: Driving Simulator Validation for Speed Research Stuart T. Godley, Thomas J. Triggs, Brian N. Fildes Presented By: Ben Block Wen Lung Hii.](https://reader036.fdocuments.in/reader036/viewer/2022062600/5a4d1ba77f8b9ab0599c97a8/html5/thumbnails/2.jpg)
Purpose• The aim of the two
experiments conducted was to validate the MURAC (Monash University Accident Research Centre) driving simulator for research on speeding countermeasures
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Literature ReviewThe use of a modern advanced driving simulator for human factors research to take advantage of a simulators natural advantages:
1. Experimental control2. Efficiency3. Expense4. Safety5. Ease of data collection
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Theoretical Basis• Proving a simulator is a valid
tool for generating and generalizing relative speed results for experiments involving road based speeding countermeasures aiming to influence deceleration in drivers speeds
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Applicability/Practical Contribution
• Automotive fatalities continue to be a major cause of deaths in the United States
• Efforts to make the roads safer through speeding countermeasures research will help reduce these fatalities
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Theoretical Contribution
• Through this experiment speed has been clearly validated as a dependent variable for research using a simulator
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Data Collection•Data collected at 30Hz, converted to an average speed per meter of track•Measurements are taken along the area as shown below.
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Validation Approach
•Averaged relative validity analyzed using a two-factor analysis of variance to determine the impact of the rumble strips.•Interactive relative validity analyzed using a standard correlation approach to display how and when drivers reacted to the rumble strips•Canonical correlation•Assumes that the data from each 1 m segment is independent of each other
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Validation Approach• Absolute validity was analyzed using
two one-way ANOVAs• Omega squared statistic (ω2) was
used to estimate effect size because non-significant results could come from inadequate statistical power rather than actual absence of difference
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Results: Stop Sign Approach•Treatment site speed significantly slower P < 0.001•No significant interaction between the two driving environments, small ω2 = 0.002. Average relative validity established•Pattern of speed was similar for both sites. A significant correlation, R = 0.40 supports interactive relative validity. •Speed higher in simulator than instrumented car for treatment (P<0.01) and control (P<0.05) sites. No absolute validity.
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Results: Right Curve Approach•No difference in mean speed between the treatment and control sites, P = 0.063
•Significant interaction, P < 0.01. Average relative validity not established•Pattern of speed in the first three quarters was similar for both sites. A significant correlation, R = 0.52 supports interactive relative validity.
•Treatment site speeds were not significantly different, P = 0.590 and small ω2 = 0.007. Absolute validity for treatment site only.
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Results: Left Curve Approach•Treatment site speed significantly slower P < 0.001
•Speed was significantly different between the experiments P < 0.001. Average relative validity not established
•Similar pattern of speed yields a significant correlation, R = 0.50. This supports interactive relative validity.
•Speed higher in instrumented car than simulator for treatment site (P < 0.001) but not for control site (P = 0.169). Big ω2 = 0.049 suggest a significant result could been produced if there was a larger sample. No absolute validity.
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Conclusions• Speed profiles found indicate a speed
reduction when rumble strips were used compared to control roads
• There is evidence concluding that speed is a valid measure to use for experiments on the MUARC driving simulator
• Different characteristics of the road and practice hindered the validation of absolute numerical speed values
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Future Research Directions• Driving simulator validation for
different types of vehicle• Driving on the right versus driving on
the left• Effect of driving simulation on real
world driving
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Thank You