Reconciling Simultaneous Evolution of Ground Vehicle Capabilities and Operator Preferences

An objective evaluation of ground vehicle performance is a challenging task. This is further exacerbated by the increasing level of autonomy, dynamically changing the roles and capabilities of these vehicles. In the context of decision making involving these vehicles, as the capabilities of the vehicles improve, there is a concurrent change in the preferences of the decision makers operating the vehicles that must be accounted for. Decision based methods are a natural choice when multiple conflicting attributes are present, however, most of the literature focuses on static preferences. In this paper, we provide a sequential Bayesian framework to accommodate time varying preferences. The utility function is considered a stochastic function with the shape parameters themselves being random variables. In the proposed approach, initially the shape parameters model either uncertain preferences or variation in the preferences because of the presence of multiple decision makers. We consider this utility distribution as the prior and update it to a posterior with feedback that can be acquired from actual system use. The framework improves the utility function and thereby the decisions made for the next generation systems, allowing continuous improvement. We present our approach on a ground vehicle selection problem.

• Record URL:
  https://doi.org/10.4271/2020-01-0172
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
• Supplemental Notes:
  • Abstract reprinted with permission of SAE International.
• Authors:
  • Slon, Christopher
  • Pandey, Vijitashwa
  • Gorsich, David
  • Jayakumar, Paramsothy
• Conference:
  • WCX SAE World Congress Experience
  • Location: Detroit Michigan, United States
  • Date: 2020-4-21 to 2020-4-23
• Publication Date: 2020-4-14

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • SAE Technical Paper
  • Publisher: Society of Automotive Engineers (SAE)
  • ISSN: 0148-7191
  • EISSN: 2688-3627
  • Serial URL: http://papers.sae.org/

Subject/Index Terms

• TRT Terms: Automated vehicle control for ground vehicles; Bayes' theorem; Ground vehicle operators; Ground vehicles; Vehicle performance
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01739236
• Record Type: Publication
• Source Agency: SAE International
• Report/Paper Numbers: 2020-01-0172
• Files: TRIS, SAE
• Created Date: May 15 2020 11:07AM