Who goes first? A distributed simulator study of vehicle–pedestrian interaction

Kalantari, Amir Hossein; Yang, Yue; Pedro, Jorge Garcia de; Lee, Yee Mun; Horrobin, Anthony; Solernou, Albert; Holmes, Chris; Merat, Natasha; Markkula, Gustav

doi:10.1016/j.aap.2023.107050

Cited by 19 publications

(34 citation statements)

References 54 publications

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“…Regarding the space gap, we found it has a significant impact on crossing initiation time, time before crossing, time to cross, total crossing distance, and crossing speed. In line with other studies, we found the increased space gap led to less time to initiate the crossing decision, indicating pedestrians prefer to cross when there are larger spatial traffic gaps [5,14,30]. Moreover, we found participants took longer time and longer distances to cross the road when the distance from the vehicle was larger.…”

Section: Discussionsupporting

confidence: 91%

“…In addition to investigating the impact of eHMIs on the efficient communication between pedestrians and AVs, several studies focused on implicit communication, specifically analyzing the state of vehicles. For instance, studies showed pedestrian crossing behavior can be influenced by a vehicle's kinematics information, such as vehicle speed [9] and time gap [5,13,14,30]. While some studies argue that implicit communication cues are more effective and efficient, a few studies showed that pedestrians rely on more vehicle kinematics to make crossing decisions [6,28,31].…”

Section: Introductionmentioning

confidence: 99%

“…The interaction between pedestrians and AVs has been investigated in diverse road-crossing situations. The majority of studies explored the interaction in unsignalized traffic situations, mostly featuring one-lane road [2,3,5] and two-lane road [30,32]. Compared to more traditional unsignalized traffic situations, a few studies investigated pedestrian-AV interaction in unmarked crossings, junctions, and intersections [5].…”

Section: Introductionmentioning

confidence: 99%

“…However, when there are more pedestrians involved in the above-mentioned studies, they are pre-programmed computer agents, or the type of interaction is limited (e.g., clicking a button to indicate the cross-decision). Hence, it's uncertain whether pedestrian roadcrossing behavior would be the same if they were engaging with real humans in the traffic scenario [30]. Only [37] and [38] investigated paired participants crossing the road in a physical space together where the virtual environment was projected on large-screen displays.…”

Section: Introductionmentioning

confidence: 99%

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Does another pedestrian matter? A Virtual Reality study on the interaction between multiple pedestrians and autonomous vehicles in shared space

Feng,

Xu,

Farah

et al. 2023

Preprint

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Shared space has become a popular urban planning approach that reduces the segregation between pedestrians and vehicles, aiming to increase quality and accessibility of different road users. This study utilized both quantitative and qualitative data collected via a Virtual Reality (VR) experiment to investigate pedestrian road-crossing behavior in front of AV in a shared space. In the VR experiment, pedestrians attempt to cross the road in a shared space under different conditions, including the presence of another pedestrian, different external Human Machine Interface (eHMI) signs, different AV driving styles, and different road conditions. To achieve this, we employed an innovative VR setup that enabled two pedestrians to interact in real-time with physical movements within an immersive VR environment. By analyzing the collected data, we evaluate pedestrian road-crossing behavior using six key behavioral metrics (e.g., crossing initiation time, time before crossing, time to cross, gazing time, crossing speed, and crossing distance) and assess the user experience with the VR setup using questionnaire responses. Overall, we found that the presence of multiple pedestrians had significant impact on pedestrian movement dynamics during road crossing. Moreover, we found that the relative standing position had a significant impact on the distant pedestrians in terms of their time before crossing and vehicle-gazing behavior. While previous studies have predominantly focused on the interaction of an AV with a single pedestrian, this study takes an important step forward in terms of theory, methods, and relevance by considering the interaction between multiple pedestrians and AVs. The findings from the study establish a basis for further exploration of pedestrian-AV interaction in shared space.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Does another pedestrian matter? A Virtual Reality study on the interaction between multiple pedestrians and autonomous vehicles in shared space

Feng,

Xu,

Farah

et al. 2023

Preprint

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“…A distributed simulator study was conducted to investigate road user interactions in a safe and controlled environment, providing a large dataset of vehicle-pedestrian interactive behaviors to test and validate the computational models of this study. The full details of the study can be found in [67]. Here, we provide a summary of the study.…”

Section: A Empirical Studymentioning

confidence: 99%

Driver-Pedestrian Interactions at Unsignalized Crossings Are Not in Line With the Nash Equilibrium

Kalantari,

Yang,

Lee

et al. 2023

IEEE Access

Self Cite

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Recent developments in vehicle automation require simulations of human-robot interactions in the road traffic context, which can be achieved by computational models of human behavior such as game theory. Game theory provides a good insight into road user behavior by considering agents' interdependencies. However, it is still unclear whether conventional game theory is suitable for modeling vehicle-pedestrian interactions at unsignalized locations or if more complex models like behavioral game theory are needed. Hence, we compared four game-theoretic models based on two different payoff formulations and two solving algorithms, to answer this question. Unlike the most previous studies that employed naturalistic datasets to test and validate such models, this study utilized a distributed simulation dataset to test and compare the models. The study was conducted by connecting a CAVE-based pedestrian simulator to a motion-based driving simulator to replicate the traffic scenarios for 32 pedestrian-driver pairs. The findings demonstrated that there is a high variability between participant pairs' behaviors. Our proposed behavioral game-theoretic model outperformed other models in predicting the interaction outcome. This translates to a decrease by 70% and 67% in the root mean squared error (RMSE) when compared to the baseline model, for marked and unmarked crossings, respectively. The model can also predict which interaction will take the longest time to resolve. According to our results, road users cannot be expected to behave in line with the Nash equilibrium of conventional game theory that underscores the complexity of human behavior with implications for the testing and development of automated vehicles.

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Graph Neural Networks in ADAS: Architectures, Datasets and Common Approaches

Youssef,

Zemmouri

2024

Lecture Notes in Information Systems and Organisation

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Who goes first? A distributed simulator study of vehicle–pedestrian interaction

Cited by 19 publications

References 54 publications

Does another pedestrian matter? A Virtual Reality study on the interaction between multiple pedestrians and autonomous vehicles in shared space

Does another pedestrian matter? A Virtual Reality study on the interaction between multiple pedestrians and autonomous vehicles in shared space

Driver-Pedestrian Interactions at Unsignalized Crossings Are Not in Line With the Nash Equilibrium

Graph Neural Networks in ADAS: Architectures, Datasets and Common Approaches

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