Effects of Environmental Perception and Planned Maneuver Visualization on Takeover Performance in Silent Failure Scenarios

Human-automation interaction plays a vital role for the safety in partially and conditionally automated vehicles. While previous research mostly focused on the design of3takeover requests (TORs), the silent ADS failure scenarios without TORs are more common and even more safety critical. Improving the interpretability of the ADS may support drivers in these scenarios. However, little is known about the effectiveness of different types of ADS interpretability information on drivers’ performance in handling silent ADS failures. In this study, a driving simulator experiment with 48 participants were conducted to explore the impact of environmental perception (EP) and planned maneuver (PM) explanations on driver takeover performance when facing silent automation failures. Drivers encountered two types of hazards (invisible hazards, which were not visible but can be predicted based on the environment or11traffic setup and visible hazards that were directly visible) in two lighting condition (i.e., nighttime and daytime). The findings revealed that neither EP nor PM explanations increased the chance of successful takeovers, but both EP and PM, as well as their combinations, facilitated earlier takeover actions, which might be attributed to drivers’ earlier detection of hazards with the support of these types of explanations. The nighttime conditions impose challenges for drivers to respond to silent failures, especially when there were invisible hazards. Finally, the EP explanation can eliminate the negative effect of salient failures on drivers’ trust in ADS. The results from our study can provide insights for human-machine interface designs in vehicles with ADS to facilitate safer driving-task transitions.

Recommended citation: S. Yan, H. Liu, J. Zhang, J. Wang, J. Ma and D. He, "Effects of Environmental Perception and Planned Maneuver Visualization on Takeover Performance in Silent Failure Scenarios," International Journal of Human - Computer Studies, vol. 0, no. 0, pp. 1-34, 2026.