Pedestrian Dynamics in Smart Cities: Ubiquitous Sensing, Interactions, and Models

Modified social force model considering emotional contagion for crowd evacuation simulation

In this study, we investigate whether data collected on route knowledge is influenced by the method of data collection. The results of stereoscopic panoramic interactive navigation re-enactment sessions and conventional paper and pencil maps are compared against observational tracing data of pedestrian route choice behavior in the city center of Eindhoven, The Netherlands. The findings of the study suggest that the data collected through maps better describe empirical observations of pedestrian route choice behavior that the data collected through stereoscopic panoramic interactive navigation sessions.

The modeling of a new generation of agent-based simulation systems supporting pedestrian and crowd management taking into account affective states represents a new research frontier. Pedestrian behaviour involves human perception processes, based on subjective and psychological aspects. Following the concept of pedestrian environmental awareness, each walker adapts his/her crossing behaviour according to environmental conditions and his/her perception of safety. Different pedestrian behaviours can be related to subjective mobility and readiness to respond, and these factors are strongly dependent on the subjective interaction with the environment. Having additional inputs about pedestrian behaviour related to their perception processes could be useful in order to develop a more representative pedestrian dynamic model. In particular, the subjective perception of the safeness of crossing should be taken into consideration. In order to focus on the pedestrians’ perception of safe road crossing and walking, an experiment in an uncontrolled urban scenario has been carried out. Besides more conventional self-assessment questionnaires, physiological responses have been considered to evaluate the affective state of pedestrians during the interaction with the urban environment. Results from the analysis of the collected data show that physiological responses are reliable indicators of safety perception while road crossing and interacting with real urban environment, suggesting the design of agent-based models for pedestrian dynamics simulations taking in account the representation of affective states.

This study aims to provide information on the behavior of pedestrians using the crossing facilities along the Malioboro in Yogyakarta and to describe the perception of pedestrians on the crossing condition of the facilities available. This study used survey method. the type of research design used in this research is descriptive qualitative research is to depict or describe the naturally occurring condition. While data collection is done through a literature study, observation, and interviews. The population of this research is all pedestrian with the number of respondents as many as 20 people and sample collection techniques are Snowball Sampling. There are three aspects of the indicator analysis study, namely: security and safety, comfort, and ease of access. The results of this study are descriptions of the various behaviors of pedestrians in using the facilities crossings in terms of security and safety aspects, comfort, and ease of access as well as describe the condition of the facilities crossings available, so it can be used as an input policy development and design facilities crossings better. Keywords: Crossing Facilities, Security and Safety, Walking Behavior

In recent years, Sri Lanka’s construction industry has seen a troubling increase in both fatal and non-fatal accidents, largely attributed to insufficient safety knowledge among workers and deficiencies in the health and safety system. To mitigate these accidents, effective occupational health and safety training is imperative. However, the efficacy of traditional safety training methods has been questioned due to their limited impact on workers’ ability to identify and assess risks critically. The lack of experiential training is the primary cause of accidents that could have been easily avoided at construction sites in Sri Lanka. Addressing this gap, there is growing interest in utilising Virtual Reality (VR) as a powerful tool for experiential safety training in the construction sector. VR offer a realistic and safe environment where workers can engage with various scenarios and procedures, enhancing their understanding and awareness of safety protocols. This research explores the effectiveness of VR tools in enhancing safety knowledge and awareness among construction workers through a simulation safety training platform, using VR and PowerPoint methods for data collection. An experiment was conducted with VR and PowerPoint safety training methods as a data collection method. A questionnaire survey was conducted to compare conventional training methods with the VR solution. The results indicate that workers trained in VR environments had better retention of critical information, highlighting the efficiency of VR in providing a safe yet realistic training experience. This research emphasises the potential advantages of the suggested VR safety training methods in improving construction safety knowledge and awareness of construction workers.

The interest toward promoting walking culture has been increased dramatically especially in many cities across the nation. This is also included universities worldwide that have started seeking ways to increase pedestrian activities. Hence, campus planners must address the mobility and accessibility needs of pedestrian in their communities to ensure safety, functionality and conducive living and learning environment. This study was conducted to evaluate the pedestrian perception and behaviour towards the unsignalized zebra crossing in campus environment. To achieve the objective of this study, the unsignalized zebra crossing in UMP Gambang campus was selected as study location. This study was conducted using a quantitative study by means of questionnaires distribution and pedestrian movement data collection. Then Average Index Method was performed to indicate the pedestrian perception towards the crossing facility performances. The result shows that the zebra crossing was efficient and safe from the respondent’s perspective. Other than that, gender and platoon significantly influenced the crossing speeds. The outcomes from this study were hoped to bring some understanding to the university on the pedestrian’s behaviour for future planning and pedestrian safety.

Understanding pedestrian movement behavior on stairways is essential for optimizing staircase design, pedestrian flow management, and safety planning, particularly in high-density environments such as schools. While previous studies have examined pedestrian walking behavior on stairs, limited research has focused on how high school students’ characteristics influence their movement during stair descent. This study investigates the stair descent behavior of high school students under normal conditions in a natural school setting, focusing on the influence of pedestrian density, spatial position, and group walking behavior on movement speed. A field study was conducted, in which students’ movement characteristics were analyzed using video recordings to capture real-world pedestrian dynamics. The results reveal significant variations in walking behavior across different stair sections and density conditions, as well as the impact of group behavior on stair descent. Specifically, higher pedestrian density significantly reduces walking speed, highlighting the restrictive effects of congestion. Additionally, spatial positioning plays a critical role, as students walking on the outer side of the stairs exhibit higher speeds, while those on the inner side experience increased congestion and slower movement. The spatiotemporal distribution of descent speed illustrates the propagation of traffic waves upward, demonstrating the influence of density on pedestrian flow stability. Furthermore, group walking behavior is found to be a key factor in movement efficiency, with larger groups exhibiting slower speeds due to greater coordination and interaction demands. These findings provide valuable insights into pedestrian dynamics on stairways, with important implications for the design and management of school staircases and other public infrastructure.

ESRA19-0696 Non-pharmacological methods for comfort and pain management (virtual reality, musicotherapy, hypnosis,……)

Objectives Currently, pedestrians’ road-crossing decisions depend on the traffic at the crossing point, crossing opportunities, and circumstantial elements. Longer wait times on the curb and time pressure raise the number of traffic violations among pedestrians. The era of fully autonomous vehicles (FAVs) promises new interactions. External Human-Machine Interfaces (eHMIs) aim to increase the understanding of FAVs’ intentions and will influence pedestrians’ intent to cross. Yet, how pedestrian behaviors will change in the FAV era remains unclear. Further, there are no good metrics for evaluating the intricate interaction of crossing-related factors. Methods In a laboratory study, sixty participants observed crossing scenarios of a typical one-lane road with 10–12 FAVs driving along, two possible eHMI messages (“Cross!”/“Stop!”), and varying crossing opportunities (safe, risky, and unsafe). Participants had to indicate when they intended to cross the road using a designated button. Half of the participants were induced to feel time pressure. We developed index scores to convey the complexity of such crossing situations from the perspective of a pedestrian and used them to analyze the experimental data. Results In total, 48% of participants’ indications were to cross in safe crossing opportunities, 34% risky, and 18% unsafe; 69% were made when the eHMI proposition was “Cross!” and 31% for “Stop!”. High, significant, and negative correlations were found for compatible responses, e.g., with a safe crossing gap and an eHMI sign to “Cross!”. The opposite was true for incompatibility, e.g., a safe crossing gap and an eHMI sign to “Stop!” or an unsafe crossing gap and an eHMI sign to “Cross!”. The time pressure group’s median times to cross were shorter, making riskier decisions. Conclusion Our findings reflect a tendency to comply with the eHMI. In more complex scenarios where the crossing opportunity was uncertain or waiting times were longer, we observed that pedestrians were more inclined to follow the eHMI’s guidance to cross. These findings suggest that pedestrians may be more likely to follow the eHMI’s suggestion to cross than their self-skill, especially under time pressure. Our indices and metrics reflect the intricate interaction aspects of pedestrian behavior with eHMIs.

Accurately simulating occupant behavior is essential to improve our understanding about the future energy performance of the buildings. To date, most of the information related to the occupancy behaviors has been gathered through field observations and/or performing experiments within the lab environments. Even though these common data collection methods are effective and reliable for the existing buildings, using such data to project occupant behaviors in other contexts is likely to lead to uncertainties. The most significant theoretical achievement of this dissertation was to provide the future building occupants with thermal experience of non-physically existent environments. In this dissertation occupant behavior data was generated in an innovative experimental platform, the state-of-the-art, multi-sensory IVE within a climate chamber. This novel data collection approach allows designers to incorporate human sensation in design process and provides the possibility of examining the occupants’ thermoceptions and thermally-driven behavioral intentions in pre-occupancy stages of buildings’ life cycle. In specific, this dissertation focused on exploring the effectiveness of this new testbed in producing psychological and physiological responses that are comparable to their in-situ counterparts. Through the observations from the pilot studies, a well-grounded basis for developing a theoretical framework for the dissertation was formed, and results from the empirical evaluations and hypothesis testing of the proposed theoretical framework of the dissertation provided evidence for the ecological validity of the IVE as a scientific research tool. It was revealed that changing the indoor temperature between 65 ºF to 85 ºF has the same impact on participants’ perception of the thermal environment and physiological responses in both IVE and in-situ settings. However, some of the physiological responses at the beginning of the IVE sessions were significantly different from the in-situ sessions that could imply the availability of stress or worry. Also, the analyses of the collected sample of the dissertation showed that the variables age, computer skills and experience with virtual reality, as well as immersive tendency (entertainment) were positively, and the variable cybersickness (nausea) was negatively correlated with the consistency of thermally-driven behavioral intentions across the IVE and in-situ settings. The dissertation improved the IVE-based data collection using modeling techniques which are sensitive to the contextual factors such as the spatial, temporal and outside weather conditions. Another considerable finding of this dissertation was that the thermally-driven behavioral intentions in the IVE showed significant independence from the two periods of data collection (colder vs. warmer outside), which opposes the findings

Staircases play an essential role in crowd dynamics, allowing pedestrians to flow across large multi-level public facilities such as transportation hubs, shopping malls, and office buildings. Achieving a robust quantitative understanding of pedestrian behavior in these facilities is a key societal necessity. What makes this an outstanding scientific challenge is the extreme randomness intrinsic to pedestrian behavior. Any quantitative understanding necessarily needs to be probabilistic, including average dynamics and fluctuations. To this purpose, large-scale, real-life trajectory datasets are paramount.In this work, we analyze the data from an unprecedentedly high statistics year-long pedestrian tracking campaign, in which we anonymously collected millions of trajectories of pedestrians ascending and descending stairs within Eindhoven Central train station (The Netherlands). This has been possible thanks to a state-of-the-art, faster than real-time, computer vision approach hinged on 3D depth imaging, sensor fusion, and YOLOv7-based depth localization. We consider both free-stream conditions, i.e. pedestrians walking in undisturbed, and trafficked conditions, unidirectional/bidirectional flows. We report on Eulerian fields (density, velocity and acceleration), showing how the walking dynamics changes when transitioning from stairs to landing. We then investigate the (mutual) positions of pedestrian as density changes, considering the crowd as a “compressible” physical medium. In particular, we show how pedestrians willingly opt to occupy fewer space than available, accepting a certain degree of compressibility. This is a non-trivial physical feature of pedestrian dynamics and we introduce a novel way to quantify this effect. As density increases, pedestrians strive to keep a minimum distance d≈0.6m (two treads of the staircase) from the person in front of them. Finally, we establish first-of-kind fully resolved probabilistic fundamental diagrams, where we model the pedestrian walking velocity as a mixture of a slow and fast-paced component (both in non-negligible percentages and with density-dependent characteristic fluctuations). Notably, averages and modes of velocity distribution turn out to be substantially different. Our results, of which we include probabilistic parametrizations based on few variables, are key towards improved facility design and realistic simulation of pedestrians on staircases.

On the use of virtual immersive reality for discrete choice experiments to modelling pedestrian behaviour

A potentially powerful method of social-scientific data collection and investigation has been created by an unexpected institution: the law. Article 15 of the EU’s 2018 General Data Protection Regulation (GDPR) mandates that individuals have electronic access to a copy of their personal data, and all major digital platforms now comply with this law by providing users with “data download packages” (DDPs). Through voluntary donation of DDPs, all data collected by public and private entities during the course of citizens’ digital life can be obtained and analyzed to answer social-scientific questions – with consent. Thus, consented DDPs open the way for vast new research opportunities. However, while this entirely new method of data collection will undoubtedly gain popularity in the coming years, it also comes with its own questions of representativeness and measurement quality, which are often evaluated systematically by means of an error framework. Therefore, in this paper we provide a blueprint for digital trace data collection using DDPs, and devise a “total error framework” for such projects. Our error framework for digital trace data collection through data donation is intended to facilitate high quality social-scientific investigations using DDPs while critically reflecting its unique methodological challenges and sources of error. In addition, we provide a quality control checklist to guide researchers in leveraging the vast opportunities afforded by this new mode of investigation.

Interacting with pedestrians is challenging for Autonomous vehicles (AVs). This study evaluates how AV operations /associated signaling and roadway infrastructure affect pedestrian behavior in virtual reality. AVs were designed with different operations and signal indications, including negotiating with no signal, negotiating with a yellow signal, and yellow/blue negotiating/no-yield indications. Results show that AV signal significantly impacts pedestrians' accepted gap, walking time, and waiting time. Pedestrians chose the largest open gap between cars with AV showing no signal, and had the slowest crossing speed with AV showing a yellow signal indication. Roadway infrastructure affects pedestrian walking time and waiting time.

Pedestrian behavior interacting with autonomous vehicles during unmarked midblock multilane crossings: Role of infrastructure design, AV operations and signaling