Nudging human drivers via implicit communication by automated vehicles: Empirical evidence and computational cognitive modeling

IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Arkady Zgonnikov , Niek Beckers , Ashwin George , David Abbink , Catholijn Jonker
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Abstract

Understanding behavior of human drivers in interactions with automated vehicles (AV) can aid the development of future AVs. Existing investigations of such behavior have predominantly focused on situations in which an AV a priori needs to take action because the human has the right of way. However, future AVs might need to proactively manage interactions even if they have the right of way over humans, e.g., a human driver taking a left turn in front of the approaching AV. Yet it remains unclear how AVs could behave in such interactions and how humans would react to them. To address this issue, here we investigated behavior of human drivers (N = 19) when interacting with an oncoming AV during unprotected left turns in a driving simulator experiment. We measured the outcomes (Go or Stay) and timing of participants’ decisions when interacting with an AV which performed subtle longitudinal nudging maneuvers, e.g. briefly decelerating and then accelerating back to its original speed. We found that participants’ behavior was sensitive to deceleration nudges but not acceleration nudges. We compared the obtained data to predictions of several variants of a drift-diffusion model of human decision making. The most parsimonious model that captured the data hypothesized noisy integration of dynamic information on time-to-arrival and distance to a fixed decision boundary, with an initial accumulation bias towards the Go decision. Our model not only accounts for the observed behavior but can also flexibly generate predictions of human responses to arbitrary longitudinal AV maneuvers, and can be used for both informing future studies of human behavior and incorporating insights from such studies into computational frameworks for AV interaction planning.

通过自动驾驶车辆的隐性通信对人类驾驶员进行提示:经验证据和计算认知模型
了解人类驾驶员与自动驾驶汽车(AV)交互时的行为有助于未来自动驾驶汽车的开发。对此类行为的现有研究主要集中在自动驾驶汽车因人类拥有路权而需要采取行动的情况。然而,未来的自动驾驶汽车可能需要主动管理交互行为,即使它们拥有优先于人类的路权,例如,人类驾驶员在驶近的自动驾驶汽车前左转。然而,目前仍不清楚自动驾驶汽车在此类交互中的行为方式,也不清楚人类会如何应对。为了解决这个问题,我们在驾驶模拟器实验中调查了人类驾驶员(19 人)在无保护左转时与迎面而来的自动驾驶汽车互动的行为。我们测量了参与者在与自动驾驶汽车互动时的结果("走 "或 "留")和决策时机。自动驾驶汽车会进行微妙的纵向推移动作,例如短暂减速,然后加速回到原来的速度。我们发现,参与者的行为对减速暗示敏感,而对加速暗示不敏感。我们将获得的数据与人类决策漂移-扩散模型的几个变体的预测进行了比较。能捕捉到数据的最简洁的模型假定,到达时间和距离固定决策边界的动态信息的整合是嘈杂的,最初的积累偏向于围棋决策。我们的模型不仅能解释观察到的行为,还能灵活预测人类对任意纵向视听操纵的反应,可用于为未来的人类行为研究提供信息,并将这些研究的见解纳入视听交互规划的计算框架。
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来源期刊
International Journal of Human-Computer Studies
International Journal of Human-Computer Studies 工程技术-计算机:控制论
CiteScore
11.50
自引率
5.60%
发文量
108
审稿时长
3 months
期刊介绍: The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities. Research areas relevant to the journal include, but are not limited to: • Innovative interaction techniques • Multimodal interaction • Speech interaction • Graphic interaction • Natural language interaction • Interaction in mobile and embedded systems • Interface design and evaluation methodologies • Design and evaluation of innovative interactive systems • User interface prototyping and management systems • Ubiquitous computing • Wearable computers • Pervasive computing • Affective computing • Empirical studies of user behaviour • Empirical studies of programming and software engineering • Computer supported cooperative work • Computer mediated communication • Virtual reality • Mixed and augmented Reality • Intelligent user interfaces • Presence ...
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