自动驾驶汽车与行人交互中的沟通界面设计：基于行人过街决策模型的评估

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蒋倩妮, 庄想灵(

), 马国杰

陕西省行为与认知心理学重点实验室暨陕西师范大学心理学院, 西安 710062

收稿日期:2020-12-04出版日期:2021-11-15发布日期:2021-09-23
通讯作者:庄想灵E-mail:zhuangxl@snnu.edu.cn

基金资助:国家自然科学基金项目(31970998)

Evaluation of external HMI in autonomous vehicles based on pedestrian road crossing decision-making model

JIANG Qianni, ZHUANG Xiangling(

), MA Guojie

Shaanxi Key Laboratory of Behavior and Cognitive Neuroscience, School of Psychology, Shaanxi Normal University, Xi’an 710062, China

Received:2020-12-04Online:2021-11-15Published:2021-09-23
Contact:ZHUANG Xiangling E-mail:zhuangxl@snnu.edu.cn

摘要/Abstract

摘要： 自动驾驶汽车要进入人车混行的普通道路, 需确保与过街行人之间的交互安全和效率。为解决这一问题, 高等级自动驾驶汽车往往在车辆外部装置显示设备, 即外部人机界面(eHMIs)以和行人沟通信息。在具体设计上, 已有研究主要采用文字、图形、投影等视觉沟通形式, 传达车辆状态(是否在自动驾驶模式)、意图和对行人的过街建议等沟通信息, 并在真实路段实验、虚拟场景及实验室实验等情境中评估了界面的使用对行人过街意向、速度和准确性等指标的影响。然而, 以行人为中心的外部界面设计需系统地支持行人过街决策前各阶段的信息加工需求。因此, 我们结合行人过街决策过程和情境意识理论, 提出行人与自动驾驶汽车交互中的动态过街决策模型, 从行人认知加工视角评估各种界面的沟通效果。评估的结果启示, eHMIs应促进行人对车辆信息的感知、理解和预测。在感知阶段, 应采用多种类型界面、多呈现载体相结合, 增强信息的可识别性。在理解阶段, 需结合文字说明、合理选择沟通视角、信号标准化和培训提高可理解性。在预测阶段, 应结合车辆内隐运动信息, 帮助行人快速准确获取车辆未来行动意图。更重要的是, 未来研究应关注在多行人、多车辆混行情境下的信息沟通设计及其对行人的影响。理论方面, 未来研究也需要关注外部界面如何通过自下而上的通路影响情境意识和心智模型的形成。

图/表 2

表1当前研究者设计的eHMIs(外部人机交互界面)总结

图1行人与自动驾驶汽车交互中的动态过街决策模型, 基于情境意识模型(Endsley, 1995)和动态过街决策模型(Rodríguez Palmeiro et al., 2018)。为突显自上而下与自下而上两条加工路径如何影响情境意识, 模型仅呈现情境意识形成过程中的认知加工通路。

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