Application of Virtual Reality to Investigate Driver’s Route Choice in an Interstate Freeway

Route choice models are essential to predict traffic levels and to provide real-time traffic information. Yet, developing predictive models that are sensitive to the contextual factors are rare or impossible with the conventional type of data collection. This study proposes the use of virtual reality (VR) for generating context-aware and high-fidelity data related to drivers’ route choice behavior. In this study, VR experimental platforms combined with a driving simulator are used as the test-bed to generate the initial inputs regarding drivers and their route choice behavior. This approach provides the chance to consider the impact of a specific contextual factor as well as the combination of sets of factors on drivers’ decision making. Moreover, it enables to incorporate human-related factors into the models and advance a more customizable research tool for future predictions and evaluations of roadway congestion. The study presents ten experimental scenarios aggregating several contextual factors (i.e. traffic condition, journey type, and social impact) and repeated measurements were collected from forty-one subjects (20 male and 21 females; age: 31.44±7.97). The authors applied a specific regression model using generalized estimating equation (GEE) to analyze the response data and make inferences on the model parameters.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 129-136

Subject/Index Terms

Filing Info

  • Accession Number: 01708129
  • Record Type: Publication
  • ISBN: 9780784482421
  • Files: TRIS, ASCE
  • Created Date: Jun 13 2019 3:02PM