The emerging use of automated driving systems introduces novel situations that may affect the safety of vulnerable road users such as cyclists. In this paper, we explain and conceptualise the phenomenon of phantom braking – sudden and unexpected deceleration – in automated vehicles. We apply signal detection theory to interpret phantom braking as a by-product of automated decision-making, with the vehicle favouring the avoidance of accidents at the cost of potentially causing rear-end accidents. To illustrate phantom braking and its effects on cyclists, we used a newly developed cycling simulator. An exploratory measurement conducted with a single cyclist participant revealed a possible complacency effect of the cyclist, with the cyclist’s decision-making mirroring the automated vehicle’s decision-making. The findings provide a testament to using cycling simulators for further exploration of the effects of phantom braking on cyclists.

Marie Skłodowska-Curie Actions; Innovative Training Networks (ITN); SHAPE-IT; Grant number 860410

DOI: 10.54941/ahfe1005212@en

Efficient crowd management is essential for optimizing the performance of pedestrian infrastructures, either in terms of crowd flow or pedestrian levels of safety and comfort. This study investigates the impact of one type of crowd management measure, namely lighting, on pedestrian behavior. Using Virtual Reality experiments, the impact of lighting, both the brightness level and the light color, on pedestrian route choice is studied. A virtual maze was designed, featuring 10 T-intersections, where the light conditions are varied at each T-intersection to study its impact on pedestrian route choice. Our study shows that pedestrian route choice is strongly influenced by the light color in a virtual environment. Pedestrians prefer to follow paths with green-colored lights and avoid paths with red-colored lights, irrespective of the light color on the other path. Moreover, pedestrians slightly prefer to use the path with a higher brightness level. Lastly, the results indicate that pedestrians do have a slight right-handed tendency on average, however, this effect cancels out almost completely when other guidance information is present in the scenario. Altogether, the findings suggest that lighting can impact pedestrian route choice behavior.
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Although numerous studies used Virtual Reality (VR) to study pedestrian behavior, there is an ongoing debate about the validity of using VR for studying pedestrian behavior. This study aims to contribute toward the validation of immersive VR systems for pedestrian wayfinding behavior studies by conducting a direct comparison of a field experiment and a matched virtual experiment. Both experiments feature three identical wayfinding assignments across multiple floors in a building. To evaluate the ecological validity of VR, three metrics of three different levels of wayfinding behavior are adopted, namely travel time (level: wayfinding performance), wayfinding strategy (level: decision-making), and angular speed of the head (level: observational behavior). Our findings show that VR can be used to study pedestrian wayfinding strategy in buildings with a single floor. However, there are significant differences in pedestrian wayfinding strategy between the field experiment and the VR experiment. Additionally, we found significant differences in the angular speed of the head between the two experiments. It suggests that researchers should take caution when using VR as a research tool to study the wayfinding strategy and the observational behavior of pedestrians in multi-story buildings.@en

This short communication presents the findings of the work conducted by the human behaviour in fire permanent working group of the International Association for Fire Safety Science. Its aim is to identify determinants of research gaps in the field of human behaviour in fire. Two workshops were conducted in 2023 in which research gaps were identified and discussed by twenty experts. The workshops led experts through a series of questions to determine the reasons (or determinants) for these gaps in human behaviour in building fires and wildfires. Through the questions, the primary identified determinants were (1) researchers’ literacy in the variety of methods adopted in the field, (2) difficulties associated with recruitment of study participants, (3) multi-disciplinary barriers across different research sub-domains, and (4) issues in obtaining funding for addressing fundamental human behaviour in fire research questions. Two key issues emerged from an open discussion during the workshops, namely the difficulties in attracting and training new people in the field (given the limited educational offers around the world on the topic) and the need for more regular opportunities for the community to meet.@en

Understanding pedestrian wayfinding behavior is crucial for traffic management and building design. The use of virtual reality technology presents an efficient approach for investigating pedestrian wayfinding behavior in large public spaces, offering numerous advantages for data collection. However, the impact of different scenario dimensions on pedestrian wayfinding behavior in large public spaces remains unclear. Additionally, the selection of virtual experiment scenario dimensions currently relies primarily on researchers’ experience and practical conditions, lacking sufficient evidence to support their rational. Another challenge is the limited focus on spatial knowledge’s effect on wayfinding behavior, with insufficient analysis of the utility of pedestrian visual information and a lack of precise methods to quantify visual field information accurately. This study addresses these gaps by incorporating spatial knowledge at multiple scales and pedestrian visual field information as influencing factors in the analysis of wayfinding behavior. Furthermore, it distinguishes between three-dimensional and two-dimensional scenarios to compare the impact of dimensional differences on pedestrian wayfinding behavior. By analyzing behavior data from non-immersive wayfinding experiments, this research employs statistical analysis methods and a deep learning framework to derive results regarding the factors influencing wayfinding behavior. The findings demonstrate that considering both spatial and visual field information effectively enhances the predictive ability of the wayfinding model. Additionally, dimensional differences significantly influence the pedestrian wayfinding process. These results offer empirical evidence to guide researchers in selecting experimental scenarios of pedestrian behavior and provide insights for public space layout, signage design, and improving pedestrian efficiency.@en

A shared space area is a low-speed urban area in which pedestrians, cyclists, and vehicles share the road, often relying on informal interaction rules and greatly expanding freedom of movement for pedestrians and cyclists. While shared space has the potential to improve pedestrian priority in urban areas, it presents unique challenges for pedestrian-AV interaction due to the absence of a clear right of way. The current study applied Virtual Reality (VR) experiments to investigate pedestrian-AV interaction in a shared space, with a particular focus on the impact of external human-machine interfaces (eHMIs) on pedestrian crossing behavior. Fifty-three participants took part in the VR experiment and three eHMI conditions were investigated: no eHMI, eHMI with a pedestrian sign on the windshield, and eHMI with a projected zebra crossing on the road. Data collected via VR and questionnaires were used for objective and subjective measures to understand pedestrian-AV interaction. The study revealed that the presence of eHMI had an impact on participants' gazing behavior but not on their crossing decisions. Additionally, participants had a positive user experience with the current VR setting and expressed a high level of trust and perceived safety during their interaction with the AV. These findings highlight the potential of utilizing VR to explore and understand pedestrian-AV interactions. @en

This study utilized Virtual Reality (VR) experiments to investigate pedestrian-autonomous vehicle interaction in shared spaces. In the VR experiment, pedestrians attempt to cross the road under different conditions, including the presence of another pedestrian, different external Human-Machin-Interfaces, AV driving styles, and road conditions. We employed an innovative VR setup that enabled two pedestrians to interact in real time with physical movements within an immersive VR environment. Overall, we found that the presence of multiple pedestrians significantly influenced pedestrian movement dynamics during road crossing. Additionally, the relative standing position had a significant impact on the distant pedestrians regarding time before crossing and vehicle-gazing behavior. While previous studies predominantly focused on pedestrian-AV interaction with a single pedestrian, this study takes an important step forward in terms of theory, methods, and relevance by considering interactions between multiple pedestrians and AVs. The findings establish a basis for further exploration of pedestrian-AV interaction in shared space.@en

Virtual Reality (VR) provides the possibility to study pedestrian wayfinding behaviour in multi-level buildings. Although VR has been applied increasingly to study pedestrian behaviour, it has remained unclear how different VR technology would affect behavioural outcomes in a multi-level building. The study compares the adoption of different VR technologies for pedestrian wayfinding studies, via investigating the difference in pedestrian wayfinding behaviour and user experience. Wayfinding experiments with two groups of participants were conducted using either HMD VR or Desktop VR. Pedestrian movement trajectory data were collected via the VR system and user experience data were recorded via a questionnaire. These data allow for direct comparison and detailed analysis of pedestrian behaviour and user experience between the adoption of two VR technologies. The results showed that technological differences have a significant impact on wayfinding task performance and head rotation change. However, the route choice, exit choice and user experience were overall similar between the two groups. These results provide empirical evidence supporting researchers to choose between immersive and non-immersive VR when study pedestrian wayfinding behaviour.
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This dissertation is focused on using Virtual Reality to study pedestrian wayfinding behaviour in buildings during both normal and emergency situations, from simple scenarios to complex scenarios. In particular, various empirical datasets featuring pedestrian wayfinding and evacuation behaviour were collected using different VR technologies to understand the usage of VR to investigate pedestrian behaviour and thereby generate new insights into pedestrian wayfinding behaviour in buildings. This thesis shows that different VR technologies (i.e., Mobile VR, HMD VR, Desktop VR) can collect valid behavioural data and study pedestrian wayfinding behaviour in various contexts.@en

Although understanding wayfinding behaviour in complex buildings is important to ensure pedestrian safety, the state of the art predominantly investigated pedestrian movement in simplified environments. This paper presents a Virtual Reality tool – WayR, that is designed to investigate pedestrian wayfinding behaviour in a multi-story building under both normal and emergency situations. WayR supports free navigation and collects pedestrian walking trajectories, head movements and gaze points automatically. To evaluate WayR, a VR experiment consists of four wayfinding assignments were conducted. The validity and usability of WayR are evaluated using objective measures (i.e., route choice, evacuation exit choice, wayfinding performance, and observation behaviour) and subjective measures (i.e., realism, feeling of presence, system usability, and simulation sickness). Analysis of the objective measures indicates that participants’ wayfinding behaviour in VR matches with findings in the literature. Moreover, we found that overall participants behaved significantly different across wayfinding assignments with increasing complexity. Furthermore, the results of subjective measures indicate a high degree of realism, immersion, usability, and low level of sickness of WayR. Overall, the results demonstrated the face validity, content validity, construct validity and usability of WayR as a research tool to study wayfinding behaviour in a complex multi-story building.@en

Exit choice is vital to pedestrians’ survival during evacuations. This paper presents the results of a VR experiment and a field experiment to study pedestrian exit choice behaviour during evacuations. Primarily, we compared pedestrian exit choice behaviour with a VR experiment and a field experiment to determine the ecological validity of a particular VR simulator (smartphone-based HMD and 360° video) as a research tool to study pedestrian exit choice behaviour. The results showed that the pedestrians’ exit choice behaviour during the evacuation is similar in the field experiment and the VR experiment. Furthermore, we investigated whether and to what extent different types of information (i.e., exit signs, directional signs, presence of people) influence pedestrian exit choice during evacuations. The analysis focused on the commonalities and differences in the pedestrians’ exit choice behaviour between the scenario without additional information and three scenarios with different types of information. The comparison between scenarios with different types of information illustrated that the presence of other pedestrians and directional signs have a significant influence on the participants’ exit choice. Moreover, the results indicated that this VR simulator is applicable to study pedestrian exit choice behaviour during evacuations.@en

Collecting pedestrian behaviour data is vital to understand pedestrian behaviour. This systematic review of 145 studies aims to determine the capability of contemporary data collection methods in collecting different pedestrian behavioural data, identify research gaps and discuss the possibilities of using new technologies to study pedestrian behaviour. The review finds that there is an imbalance in the number of studies that feature various aspects of pedestrian behaviour, most importantly (1) pedestrian behaviour in large complex scenarios, and (2) pedestrian behaviour during new types of high-risk situations. Additionally, three issues are identified regarding current pedestrian behaviour studies, namely (3) little comprehensive data sets featuring multi-dimensional behaviour data simultaneously, (4) generalizability of most collected data sets is limited, and (5) costs of pedestrian behaviour experiments are relatively high. A set of new technologies offers opportunities to overcome some of these limitations. This review identifies three types of technologies that can become a valuable addition to pedestrian behaviour research methods, namely (1) applying VR experiments to study pedestrian behaviour in the environments that are difficult or cannot be mimicked in real-life, repeat experiments to determine the impact of factors on pedestrian behaviour and collect more accurate behavioural data to understand the decision-making process of pedestrian behaviour deeply, (2) applying large-scale crowd monitoring to study pedestrian movements in large complex environments and incident situations, and (3) utilising the Internet of Things to track pedestrian movements at various locations that are difficult to investigate at the moment.

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Virtual Reality (VR) is a valuable tool for studying pedestrian behaviour in complex and realistic scenarios. However, it has remained unknown how different VR technology would influence pedestrian behaviour. This paper presents VR experiments that were conducted with 70 participants using a desktop VR or a HMD VR to perform four different wayfinding tasks in a multi-story building. Quantitative analysis of pedestrian behaviour data and user experience data were performed in order to investigate the impact of the technological differences between the two VR techniques. It was found that participants had better wayfinding task performance in the desktop group. However, the route and exit choice and user experience were overall similar between the two groups. The findings suggest that one could adopt more ‘simple’ VR technologies for studies featuring ‘simple’ wayfinding tasks.@en

This paper presents a Virtual Reality (VR) experiment to study pedestrian exit choice behavior during evacuations. It investigates whether and to what extent different types of guidance information (i.e. exit signs and directional signs) influence pedestrian exit choice during an evacuation (drill). The analysis focuses on the commonalities and differences in the pedestrians’ exit choice behavior between the scenario without any additional guidance information and two scenarios with different types of guidance information. The findings suggest that guidance information of exit signs and direction signs have significant influences on the number of recognized exits. Meanwhile, guidance information might have a relevant effect on final exit choice of participants.

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This paper presents a new VR research tool to systemically study pedestrian movement and choice behavior. This new VR tool, called CivilEvac, features a complex multi-level building that is an exact copy of an existing building. CivilEvac allows participants to freely navigate through the building, records their movements and vision fields at 10 fps, which assist the analysis of pedestrian movement and choice behavior. By showcasing CivilEvac, this paper contributes an example of using VR experiments specifically developed to study pedestrian movement and choice behavior. Thereby adding to the discussion surrounding the usage of VR technologies for studying pedestrian behavior.

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Understanding pedestrian exit choice behavior during emergency situations is important for improving evacuation efficiency. Virtual Reality is a promising technique that can be used to study pedestrian evacuation behavior. However, studies comparing evacuation behavior in real and virtual environments are still scarce. This paper explores Virtual Reality as a novel technique to study pedestrian exit choice behavior during evacuations. Two experimental methods were compared, namely a field experiment in a real building environment and a Virtual Reality experiment that covers the same situation. The comparison focuses on the commonalities and differences in the pedestrians’ exit choice behavior between the field experiment and the VR experiment. The results show that the pedestrians’ exit choice behavior during the evacuation are overall similar in the field experiment and the VR experiment. The promising results show the use of VR can be considered as a research tool for research on exit choice behavior during evacuations.@en

Social groups with heterogeneous characteristics are very common and have obvious effects on pedestrian movements. However, a limited number of models investigated the relationship of social groups with heterogeneous characteristics on the people movements. Based on several controlled experiments which took the social-groups with heterogeneous characteristics in terms of family-group and friend-group as the research objectives, the heterogeneous groups are characterized by different group size, velocity, interpersonal distance, step frequency, and walking pattern. The results showed that heterogeneous groups do have effects on pedestrian movements and the effect degrees vary with the heterogeneous attributes of groups. This paper filled the gap by developing an improved social force model which take in account the movement characteristics of groups and its influence on the pedestrians.@en

Existing literature suggested that pedestrian flow is largely effected by the nature of pedestrian group, which is a common phenomenon in crowds. However, the influence of social groups with heterogeneity on the crowd movement has not yet been fully elucidated. In order to recognize the movement characteristics of groups with heterogeneity and its influence on the pedestrian crowd, this paper takes the social-groups with heterogeneity as the research object, particularly for two types of groups, namely, Friend-group and Family-group. The groups of heterogeneity were analysed by observing group size, velocity, interpersonal distance, step frequency and walking pattern. The results shown that groups do have effects on pedestrian movement and the degree of influence depends on the heterogeneity of groups. Based on these observation, this paper developed a conceptual model on the basis of the existing social force model which obtaining the qualitative relationship between the parameter of model and groups’ heterogeneity.@en