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To practically apply level 2 automated driving in complex traffic conditions, it is necessary to prompt driver behaviors to prevent potential accidents in areas where manual interventions are frequently required. A driving simulator experiment with 20 participants was conducted to evaluate the impact of different human machine interfaces (HMIs) on drivers’ interventions in terms of braking to avoid rear-end collisions during level 2 automated driving when a motorcycle abruptly cut in near intersections. Two types of HMIs were tested: a static HMI that informed drivers about approaching intersections, and a sensor HMI that displayed real-time object recognition results. Each driver participated in five experimental conditions, which varied the presence or absence of the static and sensor HMIs during level 2 automated driving, with manual driving serving as the baseline condition. The maximum deceleration in terms of braking to avoid rear-end collisions was significantly larger when level 2 automated driving was used without any HMI, compared to that of manual driving. However, when the sensor HMI was applied together with the static HMI during level 2 automated driving, a comparable time to collision could be achieved with a significantly smaller deceleration, compared to that without any HMI. Drivers’ eye-gaze behaviors revealed that no significant difference existed in the percentages of gaze to the road center area, indicating that they were not distracted by the HMIs. Finally, drivers’ attention levels to surrounding traffic and feeling of safety were significantly higher when level 2 automated driving was used in combination with the static and sensor HMIs. The results demonstrated that the combination of static and sensor HMIs successfully aided drivers in ensuring driving safety with a significantly smaller deceleration to avoid rear-end collisions during level 2 automated driving. Furthermore, drivers’ attention levels were maintained, and their feeling of safety was improved when both HMIs were used in combination.

Driver behaviors assisted by different human machine interfaces to avoid rear-end collisions during level 2 automated driving