The Role of Conversational Agents for Long-haul Truck Drivers: An Exploratory On-road Study

Abstract

While conversational AI agents (CAs) have the potential to support drivers through hands-free and eyes-free interaction, their role in long-haul trucking remains unexplored. This paper investigates how long-haul truck drivers perceive CAs and identifies design considerations for their successful deployment. We conducted ride-along observations and semi-structured interviews with five long-haul truck drivers during regular driving operations. The results show that drivers today regulate verbal communication according to driving demands and expect communication partners to adapt to changes in workload and attention. Participants were most receptive to CAs supporting driving-related tasks, including traffic information, rerouting and route planning. Trust, perceived complexity, and discomfort with conversational interaction emerged as key barriers to adoption. We conclude that CAs may be best suited to supporting strategic and selected tactical tasks, while being less appropriate for operational tasks. Effective CA design must adapt to context and workload, support interruptions, and provide transparent and trustworthy support.