Pedestrian interactions with automated vehicles: Does the presence of a zebra crossing affect how eHMIs and movement patterns are interpreted?

Madigan, Ruth; Mun Lee, Yee; Lyu, Wei; Carlowitz, Stefanie; Garcia de Pedro, Jorge; Merat, Natasha

doi:10.1016/j.trf.2023.09.003

Cited by 11 publications

(2 citation statements)

References 27 publications

(35 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study used the head-tracking data collected as part of a virtual reality experiment developed for the EC project interACT (Grant Agreement No. 723395) to investigate the impact of road infrastructure and eHMIs on pedestrian crossing decisions at a residential crossing (see Madigan et al, 2023).…”

Section: Participantsmentioning

confidence: 99%

Interpreting pedestrians' head movements when encountering automated vehicles at a virtual crossroad

Yang,

Lee,

Madigan

et al. 2023

Preprint

View full text Add to dashboard Cite

In the future, Automated Vehicles (AVs) may be able to use pedestrians’ head movement patterns to understand their crossing intentions. This ability of the AV to predict pedestrian crossing intention will improve road safety in mixed traffic situations and may also enhance traffic flow, allowing the vehicle to gradually reduce its speed in advance of a yield, eliminating the need for a complete and erratic halt. To date, most of the work conducted on studying pedestrian head movements has been based on observation studies. To further our understanding in this area, this study examined pedestrians' head movements when interacting with AVs during a range of road crossing scenarios, developed in a VR environment. Thirty-eight participants took part in this CAVE-based pedestrian simulator study. Head movements were recorded using stereoscopic motion-tracking glasses, as pedestrians crossed the road in response to an AV which approached from the right (UK-based road). To understand how the surrounding infrastructure affected crossing behaviour, a zebra crossing was included in half of the trials. The effect of different approaching speeds of the AV, and the presence of an external Human-Machine Interface (eHMI), on head movements and crossing behaviour was also studied. Results showed that the absolute head-turning rate (change in pedestrians' head-turning angle per frame) increased significantly at around 1 s before a crossing initiation, reaching a peak at the crossing initiation, where pedestrians presented a “last-second check” before the crossing decision. Another increase in head-turning behaviour to the right was seen at the end of the crossing (~ 1.5 s after crossing initiation), to check the proximity of the approaching vehicle. A higher frequency of head turns was also seen for AV-yielding scenarios. Finally, the least number of head turns was seen for the yielding conditions which included an eHMI, in the presence of the zebra crossing. These results show the value of infrastructural and vehicle-based cues in assisting pedestrians’ crossing decisions and provide an insight into how head-turning behaviour can be used by AVs to better predict pedestrians’ crossing intentions in busy mixed traffic scenarios.

show abstract

Section: Participantsmentioning

confidence: 99%

Interpreting pedestrians' head movements when encountering automated vehicles at a virtual crossroad

Yang,

Lee,

Madigan

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…A growing body of research suggests that this heavily relies on implicit communication [8], [9] which consists of time-based (e.g., time-to-arrival [TTA]) [10], [11] and movement-based (e.g., vehicle speed) [12], [13] factors. Other situational factors such as crossing location type (e.g., presence of zebra) [14], [15] and vehicle distance at interaction onset [16] have also been found to play an important mediating role [17]. For instance, pedestrians have been found to cross less often at an unmarked crossing compared to a zebra crossing for the same TTA [14].…”

mentioning

confidence: 99%

Testing the validity of multi participant distributed simulation for understanding and modeling road user interaction

Kalantari,

Lin,

Mohammadi

et al. 2023

Preprint

View full text Add to dashboard Cite

Understanding driver-pedestrian interactions at unsignalized locations has gained additional importance due to the advancements that have happened recently in vehicle automation. To investigate these interactions, we previously developed a novel experimental study paradigm and a set of computational models, including four game-theoretic models (i.e., two conventional and two behavioral game-theoretic models) and a logit model. The aim of this study is to validate both the lab study and the models with naturalistic data to understand to what extent the results that come out of the lab are comparable to real traffic data. In the experimental study, several pairs of one driver and one pedestrian interacted with each other under different kinematic conditions and at zebra crossings in a virtual environment. The naturalistic data collection was conducted at two marked crossings (normal versus zebra staggered crossing) using state-of-the-art sensors capturing road user type, trajectory, and speed over time. Overall, the results indicated there is a fine relative validity of the experimental study where road users showed similar patterns of non-verbal communication in both studies. Similar to the lab data, crossing type played a role in interaction outcomes and metrics such as pedestrian crossing speed and vehicle delay. Pedestrians crossed more often and walked faster at staggered zebra compared to normal zebra in real traffic. In both studies, vehicle delay was affected by kinematics and location. However, vehicle delay was longer in the lab compared to real traffic. Also, unlike the lab study, pedestrian approach speed was measured and found to be the predictor of their crossing speed and the delay of the drivers. Additionally, all the computational models performed close to each other and well as opposed to the lab study. The behavioral game-theoretic models performed slightly better than the others in terms of prediction accuracy; this replicated our previous findings about road user behavior complexity which is a pivotal point for the virtual testing of automated vehicles.

show abstract

Implicit communication in cyclist-vehicle interaction: Examining the influence of driving dynamics in interactions with turning (automated) vehicles on cyclists' perceived safety, behavioral intention, and risk anticipation

Harkin,

Mangold,

Harkin

et al. 2024

Journal of Cycling and Micromobility Research

View full text Add to dashboard Cite

Pedestrian interactions with automated vehicles: Does the presence of a zebra crossing affect how eHMIs and movement patterns are interpreted?

Cited by 11 publications

References 27 publications

Interpreting pedestrians' head movements when encountering automated vehicles at a virtual crossroad

Interpreting pedestrians' head movements when encountering automated vehicles at a virtual crossroad

Testing the validity of multi participant distributed simulation for understanding and modeling road user interaction

Implicit communication in cyclist-vehicle interaction: Examining the influence of driving dynamics in interactions with turning (automated) vehicles on cyclists' perceived safety, behavioral intention, and risk anticipation

Contact Info

Product

Resources

About