Real-time trajectory planning for asphalt compaction operator support

Abstract

Operator Support Systems (OSSs) that support operators during highly time-critical asphalt compaction operations provide them with real-time sensory data. Nonetheless, the conventional asphalt compaction OSSs tend to cognitively overload operators with information that requires much human interpretation on the fly. To address the problem of OSSs' infobesity, the transition to a higher level of system automation that prescribes actions, i.e., prescriptive guidance, can be considered. To this end, this research aims to develop a novel compaction trajectory planning method that can be used to implement the Prescriptive Guidance mode in asphalt compaction OSSs. The proposed method analyzes the compaction and temperature profiles of the asphalt in real-time and suggests a compaction trajectory that ensures compaction efficiency and continuity. The proposed method is developed and compared to other types of asphalt compaction OSSs in two case studies. It is shown that while prescriptive asphalt compaction OSSs have a clear edge over more conventional OSSs in terms of improving compaction efficiency (i.e., more than 50% increase in compaction efficiency), there are still technology adoption and cultural issues that may affect the acceptance of this new technology in practice. The main contribution of this research is that it generates insights into (1) how to develop actionable and prescriptive compaction guidance, and (2) the interplay between the experience level of machine operators and the effectiveness of different support modes of asphalt compaction OSSs.