Safety perception and pedestrian dynamics: Experimental results towards affective agents modeling

<p>The dissertation explores the influence of emerging technologies on the dynamics of urban areas from a pedestrian-oriented perspective. To evaluate this influence, novel data sources and modern data-driven approaches replace traditional data collection methods and modelling techniques. Part of the dissertation establishes new tools and techniques to predict and explain pedestrian behaviour that concerns the future dynamics in urban areas. Specifically, this dissertation considers: (i) what are the novel data sources that can capture detailed information on pedestrian behaviour and how can they be used efficiently? (ii) how to extract valuable information from these new high- dimensional data sources? (iii) how to utilize the data and tools to predict pedestrian behaviour in the future urban environment? and (iv) how to interpret and explain pedestrian behaviour in the context of smart cities?</p> <p>This thesis is based on four articles introduced in Chapters 3 to 6. Chapter 3 introduces a semi-supervised residual network for transportation mode detection using passively collected labelled and unlabelled Wi-Fi signal data. Chapter 4 provides a survival analysis to model the wait time behaviour of a crossing pedestrian and analyze the effect of smartphone distraction on pedestrian behaviour. Virtual reality is used in this chapter as a means of data collection in a controlled environment. Chapter 5 highlights pedestrian crossing behaviour in the presence of automated vehicles. A large virtual reality data collection campaign is conducted to understand pedestrian behaviour in futuristic scenarios. Data-driven survival analysis is developed to analyze pedestrian wait time before mid-block unsignalized crossings. By using a post-hoc model interpretation, the contributing factors to pedestrian wait time are assessed. In Chapter 6, a neural network architecture is developed to incorporate sequential time-series data and contextual information to predict pedestrian trajectory. The proposed framework is applied to the virtual reality dataset.</p> <p>Methodological and data collection frameworks explored in this dissertation provide solutions for detecting, modelling and predicting pedestrian behaviour in a futuristic context. This dissertation con- tributes to the field of transportation by proposing alternative data collection methods, developing novel data-driven methodologies and analyzing pedestrian behaviour in the context of automated vehicles.</p>

Modified social force model considering emotional contagion for crowd evacuation simulation

Multi-grid simulation of counter flow pedestrian dynamics with emotion propagation

Cellular Automata have successfully been successfully applied to the modeling and simulation of pedestrian and crowd dynamics. In particular, the investigated scenarios have often been focused on the evaluation of medium–high population density situations, in which the motivation of pedestrians to reach a certain location overcomes their tendency to naturally respect proxemic distances. The global COVID-19 outbreak, though, has shown that sometimes it is crucial to contemplate how proxemic tendencies are emphasized and amplified by the affective state of the individuals involved in the scenario, representing an important factor to take into consideration when investigating the behaviour of a crowd. In this paper we present a research effort aimed at integrating results of quantitative analyses regarding the effects of affective states on the perception of distances maintained by different types of pedestrians with the modeling of pedestrian movement choices in a cellular automata framework.

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.

Background: Previous field studies evaluated the effects of visit to different outdoor urban environments on short-term psychological, cognitive and physiological responses. Less is known on the effect of going outside from the indoor home environment to these urban environments. Aim: To evaluate whether visits to different urban and ethnic environments, in comparison to home indoor environment, leads to short-term responses and whether these are independent of ethnicity. Methods: The participants, 20-35 year-old healthy women (N=72, 48 Arab and 24 Jewish), started the experiment at their home and visited six different outdoor urban environments in predominantly ethnic Arab or Jewish cities, in Israel. First they visited intra-ethnic city and afterward inter-ethnic city environments. In each city they visited an urban park, a residential neighborhood and the city center. In each environment (including home) the following measures were evaluated: mood (measured as positive and negative emotions, cheerfulness, relaxed, natural and discomfort feelings), working memory (measured with backwards digit-span task) and autonomic nervous system (assessed using heart rate variability (HRV)). Several potential mediators were measured: carbon monoxide (CO), heat, noise, social aspects, and the self-perceived restoration scale. Results: Going outside from home, to both intra and inter-ethnic parks, was associated with beneficial psychological, physiological, and cognitive responses, and the strongest effects were found for the intra-ethnic park. The results for the other urban environments were different between Jewish and Arab women. The self-perceived restoration, the social aspects and reduced CO, heat and noise exposures during the visits did not explain the observed changes between the outdoor environments and home. Conclusions: Visits to urban parks compared to the home demonstrated short-term beneficial changes in the outcomes that could not be attributed to the investigated mediators. Women should be encouraged to go outdoors and specifically visit parks to improve their psycho-physiological health.

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.

this multidisciplinary project involves concepts from architectural design, statistical learning, machine vision, and human ecology.the focus is on analysing how pedestrians' dynamic behaviour in space is influenced by the environmental design of different architectural scenarios.this paper presents a multi-agent pedestrian simulation and analysis system that supports agent-to-agent interactions, different spatial desires, and interpersonal distance.the system simulates and analyses pedestrian spatial behaviour with combined focus on movement trajectories, walking speed, and the visual gaze vector.the analysis component relies on learning a statistical model characterising normal/abnormal behaviour, based on sample observations of regular pedestrian movements without/with the impacts of significant visual attractions in the environment.using the example of wheeler place in Newcastle (Australia) our pilot experiments demonstrate how pedestrian behaviour characteristics can depend on selected features in the visual environment.the presented system will allow architects and urban designers to obtain better assessment of planned urban spaces and streetscape characteristics and their impacts on pedestrian behaviour.

A range of processes are required for recognizing others' affective states. It is particularly important that we process the perceptual cues providing information about these states. These experiments tested the hypothesis that difficulties with affective state identification in older adults (OAs) arise, at least partly, from deficits in perceptual processing. To this end we presented "point light display" whole body stimuli to healthy OAs and comparison younger adults (YAs) in 3 signal detection experiments. We examined the ability of OAs to recognize visual bodily information-posture and kinematics-and whether impaired recognition of affective states can be explained by deficits in processing these cues. OAs exhibited reduced sensitivity to postural cues (Experiment 1) but not to kinematic cues (Experiment 2) in affectively neutral stimuli. Importantly, they also exhibited reduced sensitivity only to affective states conveyed predominantly through posture (Experiment 3) -that is, the cue they were impaired in perceiving. These findings highlight how affective state identification difficulties in OAs may arise from problems in perceptual processing and demonstrate more widely how it is essential to consider the contribution of perceptual processes to emotion recognition. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Pedestrian choice behavior analysis and simulation of ticket gate machine in rail transit station

This thesis assesses the use of a group of small, low-altitude, low-power (in terms of communication equipment), ?xed-wing unmanned aerial vehicles (UAVs) as a mobile communication relay nodes to facilitate reliable communication between ground nodes in urban environments. This work focuses on enhancing existing models for optimal trajectory planning and enabling UAV relay implementation in realistic urban scenarios. The performance of the proposed UAV relay algorithms was demonstrated and proved through an indoor simulated urban environment, the ?rst experiment of its kind.The objective of enabling UAV relay deployment in realistic urban environments is addressed through relaxing the constraints on the assumptions of communication prediction models assumptions, reducing knowledge requirements and improving prediction efficiency. This thesis explores assumptions for urban environment knowledge at three different levels: (i) full knowledge about the urban environment, (ii) partially known urban environments, and (iii) no knowledge about the urban environment. The work starts with exploring models that assume the city size, layout and its effects on wireless communication strength are known, representing full knowledge about the urban environment. [Continues.]

研究指出自然環境對人的健康、學習及工作上具有正面的幫助，因此本研究欲了解不同環境中的生心理反應與創造思考的關係。以二個自然景觀點及二個街道景觀點進行現地實驗，實驗步驟依次為感受現地環境並完成環境恢復力知覺量表，戴上生理感測儀器感受環境並進行創造思考作業，最後為感受環境的生理放鬆後測。研究結果顯示，自然環境相較於都市環境在創造思考力的原創性及變通性面項、注意力恢復力及生理放鬆效益上有較佳的表現。Environment affects physical and psychological reactions has been approved by many studies. The benefits of natural landscapes on human health, learning and working are emphasized by landscape researchers and designer. Creative thinking is an important mental process by value of ''looking for the possibilities of things'' (White, 1990). Does natured landscape environment affect creativity? In order to understand the relationship between psychological benefits and creative thinking in different environments, this study conducted experiments in four sites including two natural and two urban environments. The participants experienced one of the experimental environments and completed the perceived restorative scale firstly. Second, they wore the biofeedback sensor, then experienced the environment and took creative tasks. Last, they experienced the environment and post-test their physiological response. Total experiment took about 25 minutes to complete. The results indicated that the natural environment was significantly more restorative than urban environment on both psychological and physiological aspects. Moreover, people performed better on originality and flexibility of the creative task in natural environment compared to urban environment. To sum up, this study shown that natural environment is more restorative and facilitated creative then urban environment.

Pedestrian dynamics is concerned with understanding the movement patterns that arise in places where more than one person walks. Relating theoretical models to data is a crucial goal of research in this field. Statistical model fitting and model selection are a suitable approach to this problem and here we review the concepts and literature related to this methodology in the context of pedestrian dynamics. The central tenet of statistical modelling is to describe the relationship between different variables by using probability distributions. Rather than providing a critique of existing methodology or a "how to" guide for such an established research technique, our review aims to highlight broad concepts, different uses, best practices, challenges and opportunities with a focussed view on theoretical models for pedestrian behaviour. This contribution is aimed at researchers in pedestrian dynamics who want to carefully analyse data, relate a theoretical model to data, or compare the relative quality of several theoretical models. The survey of the literature we present provides many methodological starting points and we suggest that the particular challenges to statistical modelling in pedestrian dynamics make this an inherently interesting field of research.

The expansion, densification and proliferation of urban areas around the world is currently occurring at a rate that is unprecedented in human history. It is predicted that global urban land cover will triple between 2000 and 2030, with some regions (including biodiversity hotspots) experiencing a ninefold increase in urban land cover over the same time period (Seto, G€ uneralp & Hutyra 2012). Accompanying the expansion of urban landscapes, it is anticipated that the human population living in cities and towns globally will increase from 3 5 to 5 billion people within the next 20 years (Fragkias et al. 2013). Thus, the demands of an expanding and urbanizing human population are one of the pressing ecological problems our world is facing (Sanderson et al. 2002), alongside, and in combination with, global climate change and changes to biodiversity at local and global scales (Pimm et al. 2014). Yet, urban environments also present a unique opportunity to expand our fundamental knowledge related to ecology and evolution due to the presence of intense and often novel selection pressures. In the inaugural issue of this journal, Calow (1987) defined functional ecology as the sum of three interactive processes: (i) those occurring between organisms and their environment, (ii) biotic interactions between organisms and (iii) adaptive processes driven by natural selection. The same three processes were highlighted 1 year earlier by Jared Diamond in Nature, when he called for biologists to pay more attention to the potential of using the unprecedented environmental conditions that exist within towns and cities to develop and test evolutionary and ecological theory (Diamond 1986). There is thus a natural synergy between functional ecology and urban ecology, as exemplified by some of the classic papers that have appeared in this journal, such as Rydell (1992) who demonstrated that the form of echolocation system determined the impact of light pollution on bat foraging behaviour. The potential of combining functional ecological research with urban ecology is, however, a long way from being fully realized. This is in part explained by the youth of urban ecology as a discipline. Scientific enquiry into the ecological consequences of urban environments has been underway for over half a century, although most of the momentum emerged after the mid 1990s (McDonnell 2011; Wu 2014). Thus, the focus of much urban research to date has involved describing patterns along environmental gradients (Gagn e 2013; McDonnell & Hahs 2013) rather than investigating the mechanistic processes that lie at the heart of functional ecology. To be effective in addressing the global challenges of urbanization, a much better understanding of how the urban environment affects the ecology and evolution of organisms needs to be developed (Grimm et al. 2008; Marzluff 2012; Gil & Brumm 2014; McDonnell & Hahs 2015). The purpose of this special feature is to draw attention to the plethora of opportunities that await researchers investigating the ecology and evolution of organisms in urban environments. The combination of environmental stressors and conditions within urban areas provides a novel opportunity to test and expand our theories related to ecology and evolution of organisms, and some intriguing insights are already beginning to emerge. For example, the detailed understanding of the molecular, genetic and developmental mechanisms of beak evolution that has arisen from studying Galapagos finches has been significantly advanced by studying beak evolution in the house finch Carpodacus mexicanus in response to novel urban food sources and its consequences for acoustic communication (Badyaev 2010, 2014). Thus, urban ecology has the potential to extend our understanding of extremely well-studied ecological and evolutionary problems.

Athletes' affective states can vary dramatically before, during, and after competition. Further, intense affect is associated with physiological responses that may amplify biological reactions manifested from the execution of physical tasks underlying performance. Fluctuations in perceptual cues (eg, perceived exertion) and physiological responses (eg, blood lactate, heart rate) can influence performance and vary dramatically in relation to competition. However, the pattern of these fluctuations and potential associations between perceptual cues and biological responses may also diverge during task execution with differential implications for performance. Data collected from highly trained athletes (N=25; Mage =25.4) during a competition (ie, maximum total distance) comprised of three 7-minute cycling time trials and were analyzed with longitudinal multilevel modeling. Results showed that affective states were negatively associated with perceived exertion at the within-person level and negatively associated with heart rate at the between-person level within each trial. Blood lactate and heart rate were positively associated at the between-person level, whereas heart rate was positively associated with perceived exertion at the within-person level. The anticipation of more pleasurable affective states predicted less decline in affective states, but not physiological responses, during each trial. Anticipated affective states prior to each trial were also associated with affective states upon its completion. These findings suggest associations among perceptual cues and physiological responses may differ depending on the level of analysis (between- vs. within-person level associations), and anticipated affective states prior to performance may influence affective states during and after task execution.