ABSTRACT
Autonomous vehicles (AVs) are expected to play a key role in the future of urban transportation systems, as they will offer additional safety, increased productivity, greater accessibility, and better road efficiency, which have a positive impact on the environment. Section 1.1 defines an AV as one using a combination of sensors, cameras, radar, and artificial intelligence (AI) to travel between destinations without a human operator. To qualify as fully autonomous, a vehicle must be able to navigate without human intervention to a predetermined destination over roads that have not been adapted for its use. Beyond connectivity-enabled functions, an AV will understand its environment and passengers. It will also “learn” to react and adapt to different situations during the entire driving process.
The technologies developed for AVs, i.e., sensing technologies, data science, and machine learning, can be used to take the predictive maintenance of industrial assets to a new level. Sections 1.2–1.4 provide a conceptual framework for the use of autonomous inspection and maintenance practices. Autonomous robots, for instance, unmanned aerial vehicles, pipe inspection gauges, and remotely operated vehicles, are already used in various industrial settings for inspection and maintenance. Autonomous robots can be programmed for repetitive and specific tasks; this is useful for the inspection and maintenance of linear assets.
