Impact of Automation on Drivers’ Performance in Agricultural Semi-Autonomous Vehicles

Drivers inadequate mental workload has been reported as one of the nega- tive effects of driving assistant systems and in-vehicle automation. The increasing trend of automation in agricultural vehicles raises some concerns about drivers mental work- load in such vehicles. Thus, a human factors perspective is needed to identify the conse- quences of such automated systems. In this simulator study, the effects of vehicle steering task automation (VSTA) and implement control and monitoring task automation (ICMTA) were investigated using a tractor-air seeder system as a case study. Two performance parameters (reaction time and accuracy of actions) were measured to assess drivers perceived mental workload. Experiments were conducted using the tractor driving simu- lator (TDS) located in the Agricultural Ergonomics Laboratory at the University of Manitoba. Study participants were university students with tractor driving experience. According to the results, reaction time and number of errors made by drivers both de- creased as the automation level increased. Correlations were found among performance parameters and subjective mental workload reported by the drivers.