Usability Study and Heuristic Evaluation of the Applied Robotics for Installations and Base Operations (ARIBO) Driverless Vehicle Reservation Application ARIBO Mobile

Abstract

This study addresses the usability of the Applied Robotics for Installations and Base Operations (ARIBO) Autonomous Warrior Transport On-base (AWTO) rider reservation and reminder system mobile application, called ARIBO Mobile. ARIBO is an on-demand transportation system that will allow Soldiers to reserve a vehicle for a specified time and at predefined pick-up and drop-off locations throughout the medical campus at Ft Bragg, North Carolina. The mobile application allows riders to request transport reservations, modify or view existing reservations, and receive reminders for upcoming reservations. A usability assessment was conducted with 7 subject matter experts to provide a heuristic evaluation of the application, feedback on the design of the application, and an objective assessment of the tool. Direct measurements including time to complete task, number of steps to complete task, errors, and requests for assistance were recorded. The usability assessment of ARIBO Mobile provides the designers with feedback that may be used to update or change the design prior to wide distribution to the Soldiers.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2017
Accession Number
AD1029412

Entities

People

  • Edward R. Straub
  • Kristin E. Schaefer

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Autonomous Systems
  • Brain Injuries
  • Cognitive Systems Engineering
  • Computer Programs
  • Computers
  • Human Systems Integration
  • Human-Computer Interaction
  • Mobile Application Software
  • Mobile Devices
  • Mobile Phones
  • North Carolina
  • Robotics
  • Tablet Computers
  • Test And Evaluation
  • Transportation
  • Unmanned Vehicles
  • Vehicles

Readers

  • Computer Networking
  • Database Systems and Applications
  • Environmental Remediation and Restoration.

Technology Areas

  • AI & ML
  • Autonomy