開始時刻
前のセッションの直後
163. Autonomous Vehicles
発表数
5
時間
3分
発表担当
目次
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Exploring the Impact of Interconnected External Interfaces in Autonomous Vehicles on Pedestrian Safety and Experience
説明
Policymakers advocate for the use of external Human-Machine Interfaces (eHMIs) to allow autonomous vehicles (AVs) to communicate their intentions or status. Nonetheless, scalability concerns in complex traffic scenarios arise, such as potentially increasing pedestrian cognitive load or conveying contradictory signals. Building upon precursory works, our study explores 'interconnected eHMIs,' where multiple AV interfaces are interconnected to provide pedestrians with clear and unified information. In a virtual reality study (N=32), we assessed the effectiveness of this concept in improving pedestrian safety and their crossing experience. We compared these results against two conditions: no eHMIs and unconnected eHMIs. Results indicated interconnected eHMIs enhanced safety feelings and encouraged cautious crossings. However, certain design elements, such as the use of the colour red, led to confusion and discomfort. Prior knowledge slightly influenced perceptions of interconnected eHMIs, underscoring the need for refined user education. We conclude with practical implications and future eHMI design research directions.
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"It Must Be Gesturing Towards Me": Gesture-Based Interaction between Autonomous Vehicles and Pedestrians
説明
Interacting with pedestrians understandably and efficiently is one of the toughest challenges faced by autonomous vehicles (AVs) due to the limitations of current algorithms and external human-machine interfaces (eHMIs). In this paper, we design eHMIs based on gestures inspired by the most popular method of interaction between pedestrians and human drivers. Eight common gestures were selected to convey AVs' yielding or non-yielding intentions at uncontrolled crosswalks from previous literature. Through a VR experiment (N1 = 31) and a following online survey (N2 = 394), we discovered significant differences in the usability of gesture-based eHMIs compared to current eHMIs. Good gesture-based eHMIs increase the efficiency of pedestrian-AV interaction while ensuring safety. Poor gestures, however, cause misinterpretation. The underlying reasons were explored: ambiguity regarding the recipient of the signal and whether the gestures are precise, polite, and familiar to pedestrians. Based on this empirical evidence, we discuss potential opportunities and provide valuable insights into developing comprehensible gesture-based eHMIs in the future to support better interaction between AVs and other road users.
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Multi-Modal eHMIs: The Relative Impact of Light and Sound in AV-Pedestrian Interaction
説明
External Human-Machine Interfaces (eHMIs) have been evaluated to facilitate interactions between Automated Vehicles (AVs) and pedestrians. Most eHMIs are, however, visual/ light-based solutions, and multi-modal eHMIs have received little attention to date. We ran an experimental video study (N = 29) to systematically understand the effect on pedestrian's willingness to cross the road and user preferences of a light-based eHMI (light bar on the bumper) and two sound-based eHMIs (bell sound and droning sound), and combinations thereof. We found no objective change in pedestrians' willingness to cross the road based on the nature of eHMI, although people expressed different subjective preferences for the different ways an eHMI may communicate, and sometimes even strong dislike for multi-modal eHMIs. This shows that the modality of the evaluated eHMI concepts had relatively little impact on their effectiveness. Consequently, this lays an important groundwork for accessibility considerations of future eHMIs, and points towards the insight that provisions can be made for taking user preferences into account without compromising effectiveness.
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Light it Up: Evaluating Versatile Autonomous Vehicle-Cyclist External Human-Machine Interfaces
説明
The social cues drivers exchange with cyclists to negotiate space-sharing will disappear as autonomous vehicles (AVs) join our roads, leading to safety concerns. External Human-Machine Interfaces (eHMIs) on vehicles can replace driver social signals, but how these should be designed to communicate with cyclists is unknown. We evaluated three eHMIs across multiple traffic scenarios in two stages. First, we compared eHMI versatility, acceptability and usability in a VR cycling simulator. Cyclists preferred colour-coded signals communicating AV intent, easily seen through quick glances. Second, we refined the interfaces based on our findings and compared them outdoors. Participants cycled around a moving car with real eHMIs. They preferred eHMIs using large surfaces on the vehicle and animations reinforcing colour changes. We conclude with novel design guidelines for versatile eHMIs based on first-hand interaction feedback. Our findings establish the factors that enable AVs to operate safely around cyclists across different traffic scenarios.
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One Size Does Not Fit All: Designing and Evaluating Criticality-Adaptive Displays in Highly Automated Vehicles
説明
To promote drivers' overall experiences in highly automated vehicles, we designed three objective criticality-adaptive displays:IO display highlighting Influential Objects, CO display highlighting Critical Objects, and ICO display highlighting Influential and Critical Objects differently. We conducted an online video-based survey study with 295 participants to evaluate them in varying traffic conditions. Results showed that low-trust propensity participants found ICO display more useful while high-trust propensity participants found CO displays more useful. When interacting with vulnerable road users (VRUs), participants had higher situational awareness (SA) but worse non-driving related task (NDRT) performance. Aging and CO displays also led to slower NDRT reactions. Nonetheless, older participants found displays more useful. We recommend providing different criticality-adaptive displays based on drivers' trust propensity, age, and NDRT choice to enhance driving and NDRT performance and suggest carefully treating objects of different categories in traffic.
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