318 research outputs found

    Constraint-based simulation of virtual crowds

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    Central to simulating pedestrian crowds is their motion and behaviour. It is required to understand how pedestrians move to simulate and predict scenarios with crowds of people. Pedestrian behaviours enhance the range of motions people can demonstrate, resulting in greater variety, believability, and accuracy. Models with complex computations and motion have difficulty in being extended with additional behaviours. This is because the structure of these models are not designed in a way that is generally compatible with collision avoidance behaviours. To address this issue, this thesis will research a possible pedestrian model that can simulate collision response with a wide range of additional behaviours. The model will do so by using constraints, a limit on the velocity of a person's movement. The proposed model will use constraints as the core computation. By describing behaviours in terms of constraints, these behaviours can be combined with the proposed model. Pedestrian simulations strike a balance between model complexity and runtime speed. Some models focus entirely on the complexity and accuracy of people, while other models focus on creating believable yet lightweight and performant simulations. Believable crowds look realistic to human observation, but do not match up to numerical analysis under scrutiny. The larger the population, and the more complex the motion of people, the slower the simulation will run. One route for improving performance of software is by using Graphical Processing Units (GPUs). GPUs are devices with theoretical performance that far outperforms equivalent multi-core CPUs. Research literature tends to focus on either the accuracy, or the performance optimisations of pedestrian crowd simulations. This suggests that there is opportunity to create more accurate models that run relatively quickly. Real time is a useful measure of model runtime. A simulation that runs in real time can be interactive and respond live to user input. By increasing the performance of the model, larger and more complex models can be simulated. This in turn increases the range of applications the model can represent. This thesis will develop a performant pedestrian simulation that runs in real time. It will explore how suitable the model is for GPU acceleration, and what performance gains can be obtained by implementing the model on the GPU

    Multi-scale Pedestrian Navigation and Movement in Urban Areas

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    Sustainable transport planning highlights the importance of walking to low-carbon and healthy urban transport systems. Studies have identified multiple ways in which vehicle traffic can negatively impact pedestrians and inhibit walking intentions. However, pedestrian-vehicle interactions are underrepresented in models of pedestrian mobility. This omission limits the ability of transport simulations to support pedestrian-centric street design. Pedestrian navigation decisions take place simultaneously at multiple spatial scales. Yet most models of pedestrian behaviour focus either on local physical interactions or optimisation of routes across a road network. This thesis presents a novel hierarchical pedestrian route choice framework that integrates dynamic, perceptual decisions at the street level with abstract, network based decisions at the neighbourhood level. The framework is based on Construal Level Theory which states that decision makers construe decisions based on their psychological distance from the object of the decision. The route choice framework is implemented in a spatial agent-based simulation in which pedestrian and vehicle agents complete trips in an urban environment. Global sensitivity analysis is used to explore the behaviour produced by the multi-scale pedestrian route choice model. Finally, simulation experiments are used to explore the impacts of restrictions to pedestrian movement. The results demonstrate the potential insights that can be gained by linking street scale movement and interactions with neighbourhood level mobility patterns

    Occupant-Centric Simulation-Aided Building Design Theory, Application, and Case Studies

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    This book promotes occupants as a focal point for the design process

    Agora : unified framework for crowd simulation research

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    Crowd simulation focuses on modeling the movements and behaviors of large groups of people. This area of study has become increasingly important because of its several applications in various fields such as urban planning, safety, and entertainment. In each of these domains, the presence of virtual agents exhibiting realistic behavior greatly enhances the quality of the simulations. However, the inherently multifaceted and intricate nature of human behavior presents a unique challenge, necessitating the effective combination of multiple behavior models. This thesis introduces a novel theoretical framework for modeling human behavior in crowd simulations, addressing the unresolved issue of combining a plethora of behavior models, often developed in isolation. The proposed framework decomposes human behavior into fundamental driving stimuli, which are then represented graphically through the heatmap paradigm. Subsequently, the agent behavior is influenced by the heatmaps, which guide them toward attractive areas and steer them away from repulsive locations based on the encoded stimuli. A key advantage of this approach lies in the ability to combine heatmaps using well-defined color operations, effectively integrating different aspects of human behavior. Furthermore, the heatmap paradigm facilitates objective comparison of simulation output with real-world data, employing image similarity metrics to evaluate model accuracy. To realize this framework, the thesis presents a modular software architecture designed to support various tasks involved in crowd simulation, emphasizing the separation of concerns for each task. This architecture comprises a collection of abstract modules, which are subsequently implemented using appropriate software components to realize the underlying features, resulting in the Agora framework. To assess the ability of Agora to support the various tasks involved in crowd simulation, two case studies are implemented and analyzed. The first case study simulates tourists visiting Þingvellir national park in Iceland, examining how their behavior is influenced by the visibility of the surrounding environment. The second case study employs Agora to model the thermal and density comfort levels of virtual pedestrians in an urban setting. The results demonstrate that Agora successfully supports the development, combination, and evaluation of crowd simulation models against real-world data. The authoring process, assisted by Agora, is significantly more streamlined compared to its native counterpart. The integration of multiple models is achieved by combining the heatmaps, resulting in plausible behavior, and the model assessment is made convenient through the evaluator within the framework. The thesis concludes by discussing the implications of these findings for the field of crowd simulation, highlighting the contributions and potential future directions of the Agora framework.Mannfjöldahermun fæst við gerð líkana af hreyfingu og hegðun stórra hópa af fólki. Mikilvægi þessa rannsóknasviðs hefur vaxið stöðugt vegna hagnýtingar á margvíslegum vetvangi, eins og til dæmis á vetvangi borgarskipulags, öryggis og afþreyingar. Þegar sýndarmenni hegða sér á sannfærandi hátt, leiðir það til betri hermunar fyrir þessi notkunarsvið. En mannleg hegðun er í eðli sínu margbrotin og flókin og því er það sérstök áskorun við smíði sýndarmenna að sameina, með áhrifaríkum hætti, mörg mismunandi hegðunarlíkön. Þessi ritgerð kynnir nýja fræðilega umgjörð líkanasmíði mannlegrar hegðunar fyrir mannfjöldahermun, sem tekur á þeim óleysta vanda að sameina fjölda hegðunarlíkana, sem oft eru þróuð með aðskildum hætti. Umgjörðin brýtur mannlega hegðun niður í grundvallar drifáreiti, sem eru sett fram grafískt útfrá hugmyndafræði hitakorta. Sýndarmennin hegða sér síðan undir áhrifum frá hitakortunum, sem vísa þeim í áttina að aðlaðandi svæðum og stýra þeim burt frá fráhrindandi svæðum, útfrá hinu umritaða áreiti. Lykilkostur þessarar nálgunar er sá eiginleiki að geta blandað saman hitakortum með vel skilgreindum litaaðgerðum, sem eru þá í raun samþætting mismunandi hliða mannlegrar hegðunar. Hitakortshugmyndafræðin auðveldar ennfremur hlutlægan samanburð hermunarúttaks og raungagna með notkun myndsamanburðarmælinga, til að meta nákvæmni líkana. Varðandi útfærslu, þá kynnir þessi ritgerð einingadrifna hugbúnaðarhögun sem er hönnuð til að styðja við ýmsa ferla mannfjöldahermunar, með áherslu á aðskilnað helstu viðfangsefna hvers ferlis. Þessi högun inniheldur safn huglægra eininga, sem síðan eru útfærðar með viðeigandi hugbúnaðarhlutum, sem raungera undirliggjandi eiginleika. Útkoman er sjálf Agora umbjörðin. Tvö sýnidæmi eru útfærð og greind til að meta getu Agoru til að styðja við ýmis mannfjöldahermunarverkefni. Fyrra dæmið hermir eftir ferðamönnum sem heimsækja Þingvallaþjóðgarð, og skoðar hvernig hegðun þeirra verður fyrir áhrifum sýnileika umhverfisins sem umleikur þá. Seinna dæmið nýtir Agoru til að smíða líkan af hitauppstreymis- og þéttleikaþægindum hjá sýndarvegfarendum í borgarumhverfi. Niðurstöðurnar sýna góðan árangur Agoru við að styðja þróun, samþættingu og mat mannfjöldahermunarlíkana gagnvart raungögnum. Þróunarferlið er verulega þjálla með Agoru en með hefðbundnum aðferðum. Samþætting margra líkana tókst með blöndun hitakorta, möguleg hegðun var framkölluð og mat á líkönunum varð þægilegra með umgjörðinni. Ritgerðinni lýkur með því að fjalla um áhrif þessara niðurstaðna á svið mannfjöldahegðunar, með áherslu á nýstálegt framlag þessarar rannsóknar og mögulega framtíðarþróun Agora umgjarðarinnar

    People flor maps for socially conscious robot navigation

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    With robots becoming increasingly common in human occupied spaces, there has been a growing body of research into the problem of socially conscious robot navigation. A robot must be able to predict and anticipate the movements of people around it in order to navigate in a way that is socially acceptable, or it may face rejection and therefore failure. Often this motion prediction is achieved using neural networks or artificial intelligence to predict the trajectories or flow of people, requiring large amounts of expensive and time-consuming real-world data collection. Therefore, many recent studies have attempted to find a way to create simulated human trajectory data. A variety of methods have been used to achieve this, the main ones being path planning algorithms and pedestrian simulators, but no study has evaluated these methods against each other and real-world data. This thesis compares the ability of two path planning algorithms (A* and RRT*) and a pedestrian simulator (PTV Vissim) to make realistic maps of dynamics. It concludes that A*-based path planners are the best choice when balancing the ability to replicate realistic people flow with the ease of generating large amounts of data

    Measuring the effect of park-and-ride facilities and interchange station on passenger ridership at the urban rail station in Kuala Lumpur

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    This paper is to measure the contribution of the park-and-ride facility and interchange station on passenger ridership in Kuala Lumpur using March 2018 passenger ridership, park-and-ride, and interchange station data for each station along Sri Petaling – Ampang lines. The data were gathered and analyzed using correlations and multiple regression. The result found that the interchange station has contributed 38.5% in determining passenger ridership for the Sri Petaling – Ampang lines. Park-and-ride facilities, however, were found to be statistically insignificant in determining passenger ridership. Therefore, the interchange station is crucial for future urban rail development, to increase ridership, improve mobility and uplift public transport modal split. Further studies should identify the irrelevancy of park-and-ride facilities in contributing to passenger ridership for rail lines. A better characteristic of park-and-ride facilities must be formulated to tackle their weaknesses and to improve existing park-and-ride and their future development

    LIPIcs, Volume 277, GIScience 2023, Complete Volume

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    LIPIcs, Volume 277, GIScience 2023, Complete Volum
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