Conference Proceeding

Developing a Driver-Centric Roadway Classification System with
Multidimensional Scaling

Authors
  • Stacy Balk (Science Applications International Corporation (SAIC), McLean, VA)
  • Vaughan Inman (Science Applications International Corporation (SAIC), McLean, VA)
  • William Perez (Science Applications International Corporation (SAIC), McLean, VA)

Abstract

Various systems exist to classify roadway environments; however most do not consider driver-relevant perceptual components. A perceptually based roadway classification system has the potential to support the placement of signage (or removal of extraneous clutter) in the right-of-way as a means to enhance driver performance. The present study sought to determine which environmental factors are attended to by roadway users. Thirteen participants first rated the similarity of 14 roadway environments and then rated each environment on 5 different descriptors (built-up, clutter, openness, aesthetically pleasing, organized/predictable). The resultant data were analyzed using a methodology rarely taken advantage of in the field of transportation: Multidimensional Scaling (MDS). MDS revealed the participants relied on two primary dimensions when rating the similarity of the roadway environments. These two dimensions related closely with: 1) organization/predictability and 2) clutter and aesthetics. This methodology provides a simple way to gain access to drivers’ perceptions of the roadway environment and appears to be a promising first step toward developing a user-focused roadway classification system.

How to Cite:

Balk, S. & Inman, V. & Perez, W., (2011) “Developing a Driver-Centric Roadway Classification System with
Multidimensional Scaling”, Driving Assessment Conference 6(2011), 158-164. doi: https://doi.org/10.17077/drivingassessment.1392

Rights: Copyright © 2011 the author(s)

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Published on
28 Jun 2011
Peer Reviewed