Abstract
This paper outlines the preliminary application of a quantitative method for assessing field of view using spherical projections of categorical visual information overlaid by occlusion maps based on vehicle geometry. The project goal was to quantitatively assess not only where a vehicle operator can see but what visual information is available in the operator’s field of view. By creating a driving environment dataset coded for visual information, we can indicate the probability of a type of visual information appearing in the operator’s field of view in a given vehicle. Next, we overlay probability maps with vehicle and operator eye height-specific occlusion maps, giving us a quantitative representation of visible information. This method was applied to three vehicles: a midsized sedan, a light-duty pickup truck, and a full-sized pickup truck using eye heights corresponding to those of 5th percentile females, 50th percentile females, 50th percentile males, and 95th percentile males.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
RAMSIS Cognitive, http://www.human-solutions.com/mobility/front_content.php?idcat=325
Marshall, R., Summerskill, S., Cook, S.: Development of a volumetric projection technique for the digital evaluation of field of view. Ergonomics 56(9), 1437–1450 (2013)
Ray, S., Teizer, J.: Computing 3D blind spots of construction equipment: implementation and evaluation of an automated measurement and visualization method utilizing range point cloud data. Autom. Constr. 36, 95–107 (2013)
Bostelman, R., Teizer, J., Ray, S., Agronin, M., Albanese, D.: Methods for improving visibility measurement standards of powered industrial vehicles. Saf. Sci. 62, 257–270 (2014)
Cook, S., Summerskill, S., Marshall, R., Richardson, J., Lawton, C., Grant, R., …, Clemo, K.: The development of improvements to drivers’ direct and indirect vision from vehicles—Phase 2. Technical Report, Loughborough University (2011)
TIGER/Line Shapefile, 2013, 2010 nation, U.S., 2010 Census Urban Area National, http://www2.census.gov/geo/tiger/TIGER2013/UAC10/tl_2013_us_uac10.zip
Moller, R., Trumbore, B.: Fast, minimum storage ray-triangle intersection. J. Graphics Tools 2(1), 21–28 (1997)
Lagae, A., Dutre, P.: An efficient ray-quadrilateral intersection test. J. Graph. GPU Game Tools 10(4), 23–32 (2005)
Acknowledgments
Effort sponsored by the Engineering Research and Development Center under Cooperative Agreement number W912HZ-15-2-0004. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Engineering Research and Development Center or the U.S. Government. The authors would also like to acknowledge the invaluable efforts of Patience Judy and Maverick Smith for their many hours of assistance manually coding the images in the driving environment database.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing Switzerland
About this paper
Cite this paper
King, M.D., Jinkerson, J., Garrison, T., Irby, D., Carruth, D.W. (2017). A Quantitative Comparison of Operator Field of View for Vehicle Design. In: Duffy, V. (eds) Advances in Applied Digital Human Modeling and Simulation. Advances in Intelligent Systems and Computing, vol 481. Springer, Cham. https://doi.org/10.1007/978-3-319-41627-4_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-41627-4_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41626-7
Online ISBN: 978-3-319-41627-4
eBook Packages: EngineeringEngineering (R0)