Is control necessary for drivers? Exploring the influence of human–machine collaboration modes on driving behavior and subjective perception under different hazard visibility scenarios

Abstract

Before full achieving automation, Autonomous Vehicle(AV) must undergo a transitional phase of human–machine collaborative driving. Therefore, designing appropriate Human-Machine Interface (HMI) modes of collaboration is key to ensuring both driving safety and user experience. However, existing research has rarely considered the design of human–machine collaboration modes under different Hazard Visibility scenarios. In this study, we conducted a simulated driving experiment (N = 28) to explore the effects of three HMI-based collaboration modes (HMI1, HMI2, and HMI3) on driving behavior and subjective perception under two hazard visibility scenarios (visible and invisible hazard). The designs of the three collaboration modes were primarily based on varying levels of explainability and control. The results show that in the invisible hazard scenario, drivers exhibited significantly lower situation awareness and preference compared to the visible hazard scenario. The design of HMI in different collaboration modes significantly influences drivers’ situation awareness, cognitive workload, trust, and attention distribution, with the highest satisfaction reported for HMI2 (high explainability, AV-led decision-making). Particularly in the invisible hazard scenario, HMI2 significantly improved drivers’ situation awareness and attention while minimizing cognitive workload. The study also indicates that during autonomous driving, drivers require a certain sense of control, though this does not necessarily mean they need to directly participate in decision-making. Instead, a sense of control can be fostered by augmenting the explainability of the HMI. These findings provide valuable insights for the design of human–machine interfaces in AV to enhance driving safety.