Autonomous Heavy-Duty Mobile Machinery : A Multidisciplinary Collaborative Challenge

• Heavy-duty mobile machines (HDMMs), are a wide range of off-road machinery used in diverse and critical application areas which are currently facing several issues like skilled labor shortage, safety requirements, and harsh work environments in general. Consequently, efforts are underway to increase automation in HDMMs for increased productivity and safety, eventually transitioning to operator-less autonomous HDMMs to address skilled labor shortages. However, HDMM are complex machines requiring continuous physical and cognitive inputs from human operators. Thus, developing autonomous HDMM is a huge challenge, with current research and developments being performed in several independent research domains. Through this study, we use the bounded rationality concept to propose multidisciplinary collaborations for new autonomous HDMMs and apply the transaction cost economics framework to suggest future implications in the HDMM industry. Furthermore, we introduce and provide a conceptual understanding of the autonomous HDMM industry collaborations as a unified approach, while highlighting the practical implications and challenges of the complex nature of such multidisciplinary collaborations. The collaborative challenges and potentials are mapped out between the following topics: mechanical systems, AI methods, software systems, sensors, data and connectivity, simulations and process optimization, business cases, organization theories, and finally, regulatory frameworks.

Subject headings

SAMHÄLLSVETENSKAP  -- Ekonomi och näringsliv (hsv//swe)

SOCIAL SCIENCES  -- Economics and Business (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

automation

augmentation

autonomous

collaboration

mobile machinery

transaction cost economics

Business Studies

Företagsekonomi

Computer Science

Datavetenskap

Publication and Content Type

ref (subject category)

kon (subject category)