Improving the Usefulness and Acceptability of Automated Detection and Tracking Systems
Abstract
Automation is being introduced increasingly in an effort to improve the accuracy and timeliness of information processing within complex computer-based systems. One task that has received considerable attention in this respect is the detection and tracking of targets on sensor and tactical systems. However, initial experience with automated detection and tracking systems has been less than satisfactory. They are often seen as being unreliable and workload intensive. When they are perceived as being reliable, operators often fail to monitor them adequately. Most of the effort to improve the performance of these systems has focused on finding better algorithms. In contrast, the research presented in this paper has focused on understanding when and how operators make use of automated detection and tracking systems and the conditions under which they are likely to improve performance and reduce workload. This paper summarizes the most pertinent results of our research examining human use of a simulated automated detection and tracking system as a function of reliability, workload, and experience. Our research shows that each of these factors impacts on system performance and on the perceived and actual usefulness of the automated system. Best performance tends to be associated with a moderately reliable tracking system with a low false detection rate while perceived reliability tends to be associated with low workload. Under low workload conditions, the operators' ability to detect targets improves, but their ability to detect automation induced errors does not. Suggestions for improving the usefulness of automated detection and tracking systems are offered.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2009
- Accession Number
- ADA599406
Entities
People
- Kirsten Stanger
- Melissa Lauz
- Sharon Mcfadden
Organizations
- Defence Research and Development Canada