Drivers’ Performance in Non-critical Take-Overs From an Automated Driving System—An On-Road Study

Journal article, 2023

Objective: The objective of this semi-controlled study was to investigate drivers’ performance when resuming control from an Automated Driving System (ADS), simulated through the Wizard of Oz method, in real traffic. Background: Research on take-overs has primarily focused on urgent scenarios. This article aims to shift the focus to non-critical take-overs from a system operating in congested traffic situations. Method: Twenty drivers drove a selected route in rush-hour traffic in the San Francisco Bay Area, CA, USA. During the drive, the ADS became available when predetermined availability conditions were fulfilled. When the system was active, the drivers were free to engage in non-driving related activities. Results: The results show that drivers’ transition time goes down with exposure, making it reasonable to assume that some experience is required to regain control with comfort and ease. The novel analysis of after-effects of automated driving on manual driving performance implies that the after-effects were close to negligible. Observational data indicate that, with exposure, a majority of the participants started to engage in non-driving related activities to some extent, but it is unclear how the activities influenced the take-over performance. Conclusion: The results indicate that drivers need repeated exposure to take-overs to be able to fully resume manual control with ease. Application: Take-over signals (e.g., visuals, sounds, and haptics) should be carefully designed to avoid startle effects and the human-machine interface should provide clear guidance on the required take-over actions.