Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.
Human-Centered Mobility Research Center, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan.
Traffic Inj Prev. 2023;24(6):475-481. doi: 10.1080/15389588.2023.2222326. Epub 2023 Jun 20.
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.
为了在复杂交通情况下实际应用 2 级自动驾驶，有必要提示驾驶员行为，以防止在需要频繁手动干预的区域发生潜在事故。
通过 20 名参与者进行驾驶模拟器实验，评估在 2 级自动驾驶过程中，当摩托车在接近交叉口时突然切入时，不同人机界面（HMI）对驾驶员干预（避免追尾碰撞时制动）的影响。测试了两种类型的 HMI：一种静态 HMI，用于通知驾驶员即将接近交叉口；一种传感器 HMI，用于显示实时对象识别结果。每位驾驶员参与了五个实验条件，其中包括在 2 级自动驾驶期间是否存在静态和传感器 HMI，手动驾驶作为基线条件。
与手动驾驶相比，在没有任何 HMI 的情况下使用 2 级自动驾驶时，避免追尾碰撞的最大制动减速度显著更大。然而，当在 2 级自动驾驶期间同时应用传感器 HMI 和静态 HMI 时，与没有任何 HMI 相比，可以实现可比的碰撞时间，且减速度显著更小。驾驶员的眼动行为表明，注视道路中心区域的百分比没有显著差异，这表明他们没有被 HMI 分散注意力。最后，当结合使用静态和传感器 HMI 进行 2 级自动驾驶时，驾驶员对周围交通的注意力水平和安全感显著提高。
结果表明，静态和传感器 HMI 的组合成功地帮助驾驶员在 2 级自动驾驶过程中确保驾驶安全，避免追尾碰撞时的制动减速度显著更小。此外，当同时使用两个 HMI 时，驾驶员的注意力水平得以维持，并且他们的安全感得到提高。
