Delhi,17 september 2025: Motorists using automated driving systems overestimate their situation awareness and readiness to respond but are slower to recognise hazards compared with active โhands onโ driving, a new study from Macquarie University shows. The findings, published in the journal Applied Ergonomics, raise significant concerns about driver performance and road safety as increasingly advanced automation systems are integrated into new vehicles, the authors warn.
Researchers from Macquarieโs Performance and Expertise Research Centre studied participants who used a sophisticated simulator to โdriveโ about six kilometres in automated and non-automated driving modes, asking them to rate their situation awareness and measuring their responses to hazards. Surprisingly, drivers under automated driving conditions self-reported higher levels of situation awareness than those actively driving in non-automated mode. However, they also demonstrated significantly poorer hazard recognition compared to those participants in non-automated driving conditions, taking a longer driving distance to react to both anticipated hazards (such as another vehicle with its turning indicators on) and surprise hazards (such as a pedestrian emerging suddenly from behind a sign). Globally, there are approximately 54 million automated cars, which is expected to grow to 80 million units worldwide, and in India, there are 1.2 million units, and the number is expected to grow to 4.5 million by the year 2030.
Shedding a little light on the psyche of the drives, Mr. George Nasser, the researcher, said, โThis paradox is an example of what we call the โout-of-the-loopโ phenomenon. When theyโre relieved of responsibility for control, and as their trust in the vehicle increases, drivers tend to pay less attention to monitoring what the automated systems are doing. Under these conditions, the driverโs situation awareness declines and so does their ability to get back โin the loopโ and take control should they need to in the event of a hazard or malfunction.โ
The disconnect researchers found between driversโ perceptions and their actual driving performance suggests they develop inaccurate understandings or โmental modelsโ of the automated driving system and what it does. As an example of a worst-case scenario, Mr. Nasser cites a fatal 2016 crash in the US involving a Tesla electric vehicle in which the driver had his hands on the steering wheel for only 25 seconds while the vehicleโs โautopilotโ system was active for 37 minutes. An incomplete understanding of the systemโs limitations led to the driver not intervening when the automated system failed to detect and respond to a truck crossing the vehicleโs path.
Speaking on the subject, Mr. Nasser said, โThe driverโs mental model โ in other words, how fully and accurately the driver understands the automation system and the information it feeds back to them โ determines their ability to take control. What complicates this area is that our mental models of driving are constantly changing as we encounter more automated systems built into new cars.โ
Mr. Nasser further added, โWhat the review highlights is a need to keep drivers โon the loopโ โ monitoring without direct control but remaining vigilant and ready to intervene, if necessary. Evidence suggests interfaces and visual displays that provide the driver with continuous, easy-to-interpret feedback about system status and limitations are the best way to support accurate mental models and optimise take-over performance.โ
โAutomation in vehicles is here to stay, and the challenge now is ensuring it works with drivers, not against them. If we design systems that keep drivers engaged, we can enjoy the safety benefits of automation without compromising lives on the road,โ concludes Mr. Nasser.






