Abstract
This study conducted a driving simulation experiment to compare four automated driving systems (ADS) designs during lane change demanding traffic situations on highways while accounting for the drivers’ gender, age, experience, and practice. A lane-change maneuver was required when the automated vehicle approaches traffic congestion on the left-hand lane. ADS-1 can only reduce the speed to synchronize with the congestion. ADS-2 reduces the speed and issues an optional request to intervene, advising the driver to change lanes manually. ADS-3 offers to overtake the congestion autonomously if the driver approves it. ADS-4 overtakes the congestion autonomously without the driver’s approval. Results of drivers’ reaction, acceptance, and trust indicated that differences between ADS designs increase when considering the combined effect of drivers’ demographic factors more than the individual effect of each factor. However, the more ADS seems to have driver-like capacities, the more impact of demographic factors is expected. While preliminary, these findings may help us understand how ADS users’ behavior can differ based on the interaction between human demographic factors and system design.
Highlights
In the aviation domain, automation is complex, and the pilots, usually a pilot and a copilot, must monitor a high number of p arameters[14]
This paper investigates the impact of human demographic factors on driver decision-making and control when exposed to different ADS designs and traffic conditions
ADS-1 did not support drivers’ decisions or actions when encountering traffic congestion, approximately 85% of the participants took over the vehicle control and manually changed lanes
Summary
Automation is complex, and the pilots, usually a pilot and a copilot, must monitor a high number of p arameters[14]. The human–machine interface (HMI) in automotive automation could be less complex, but the driving environment is faster-paced and more complex than aviation, and drivers are less qualified than p ilots[15] In both aviation and automotive domains, the performance of the operation and tactical tasks and strategic decisions is highly dependent on humans’ ability to learn from heuristics and experience. Investigators have examined the effects of training and practice on driver takeover during automated driving[24,25,26,27,28] These studies established that prior familiarization and practice of automated driving affect drivers’ performance, acceptance, and trust compared to drivers presented with automated driving for the first time. We anticipated that the combined effect of driver gender, age, experience, and practice would be more than the individual impact of each factor
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