To Drive or to Be Driven? The Impact of Autopilot, Navigation System, and Printed Maps on Driver’s Cognitive Workload and Spatial Knowledge

Abstract

The technical advances in navigation systems should enhance the driving experience, supporting drivers’ spatial decision making and learning in less familiar or unfamiliar environments. Furthermore, autonomous driving systems are expected to take over navigation and driving in the near future. Yet, previous studies pointed at a still unresolved gap between environmental exploration using topographical maps and technical navigation means. Less is known about the impact of the autonomous system on the driver’s spatial learning. The present study investigates the development of spatial knowledge and cognitive workload by comparing printed maps, navigation systems, and autopilot in an unfamiliar virtual environment. Learning of a new route with printed maps was associated with a higher cognitive demand compared to the navigation system and autopilot. In contrast, driving a route by memory resulted in an increased level of cognitive workload if the route had been previously learned with the navigation system or autopilot. Way-finding performance was found to be less prone to errors when learning a route from a printed map. The exploration of the environment with the autopilot was not found to provide any compelling advantages for landmark knowledge. Our findings suggest long-term disadvantages of self-driving vehicles for spatial memory representations.

GPS navigation assistance improves driving mobility in older drivers

“…On a theoretical level, whilst several theories have postulated as to why eNA technology reduces survey knowledge acquired from the environment, including reduced cognitive load, divided attention, and reduced time to process environmental features due to increased velocity (30,31), the present study provides a potential explanation that survey knowledge is reduced due to spatial learning strategy, as we show that drivers who use eNA for everyday journeys to new locations were less likely to use landmark-dependent navigation strategies.…”

“…Previous experimental studies, conducted amongst younger populations, have found that driving whilst using eNA is associated with impairments to route learning (29,30). Therefore, whilst greater eNA usage may not impair objective cognitive facets overall, they may impair learning of spatial environments to which they are applied.…”

Driving Activity Recognition Using UWB Radar and Deep Neural Networks

“…Under the increasing level of automation available in production vehicles, continuous driver monitoring becomes a crucial safety factor [ 1 ]. To ensure drivers remain undistracted in the driving loop [ 2 ] and to prevent a negative impact of the autonomous system on the ability of drivers to take over [ 3 , 4 , 5 ], multiple methods from various research fields including human–machine interaction, psychology, computer science, and ergonomics have been investigated. Thus, in-cabin driver monitoring cameras [ 6 , 7 ] and eye-tracking systems were tested [ 3 , 8 , 9 , 10 , 11 , 12 ] and partly integrated into production vehicles.…”