Environment optimization for crowd evacuation

Berseth, Glen; Usman, Muhammad; Haworth, Brandon; Kapadia, Mubbasir; Faloutsos, Petros

doi:10.1002/cav.1652

Cited by 42 publications

(25 citation statements)

References 28 publications

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“…To explore the performance of the ISAB method, we compare it to the performance of CMA‐ES, an evolutionary strategyoptimization method used in nonconvex problems. CMA‐ES has been used previously in this domain as an offline method for optimizing architectural elements, and it serves as a state‐of‐the‐art for analysis of sampling‐based methods.…”

Section: Discussionmentioning

confidence: 99%

CODE: Crowd‐optimized design of environments

Haworth

Usman

Berseth

et al. 2017

Computer Animation & Virtual

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We present crowd-optimized design of environments (CODE): a "crowd-aware" computational tool for designing environments (e.g., building floor plans). Our system analyses the impact of newly added environment elements (e.g., pillars or doorways) on the resulting crowd flow, using current-generation crowd simulators. The results of the simulation are used to provide feedback to the designer in terms of aggregate statistics and heat maps. Additionally, our system is able to "automatically" optimize the placement of environment elements to maximize crowd flow in egress scenarios, while satisfying constraints that are imposed by the designer. Using CODE, architects and environment designers can iteratively refine upon their original design to quickly accommodate the dynamic properties of crowd simulations in an interactive fashion. CODE is modular and flexible so that designers may build environments, select from different crowd simulators, and specify varying crowd configurations.

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Section: Discussionmentioning

confidence: 99%

CODE: Crowd‐optimized design of environments

Haworth

Usman

Berseth

et al. 2017

Computer Animation & Virtual

Self Cite

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“…As dynamic analysis, we use crowd simulation techniques to model movements of virtual agents in the environments. We integrate three crowd models: Social Forces [Helbing and Molnar 1995] [Berseth et al 2015;Cassol et al 2017;Haworth et al 2017a,b]. A user sets the crowd configuration (e.g.…”

Section: Dynamic Analysis Of Building Designsmentioning

confidence: 99%

Interactive spatial analytics for human-aware building design

Usman

Schaumann

Haworth

et al. 2018

Proceedings of the 11th Annual International Conference on Motion, Interaction, and Games

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We present a computational spatial analytics tool for designing environments that better support human-related factors. Our system performs both static and dynamic analyses: the first relates to the building geometry and organization, while the second additionally considers the crowd movement in the space. The results are presented to the designers in the form of numerical values, traces and heat maps displayed on top of the floor plan. We demonstrate our approach with a user study whereby novice architects have tested the proposed approach to iteratively improve a building accessibility in real-time with respect to a selected number of static and dynamic metrics. The results indicate that the users were able to successfully improve their design solutions and thus generate more human-aware environments. The usability and effectiveness of the tool where also measured, yielding positive scores. The modular and flexible nature of the tool enables further extension to incorporate additional static and dynamic spatial metrics. CCS CONCEPTS • Computing methodologies → Visual analytics; Modeling and simulation; • Applied computing → Computer-aided design; Architecture (buildings); • Human-centered computing → Empirical studies in visualization;

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“…Tang et al [9] proposed a pseudo-polynomial-time dynamic programming algorithm to compute evacuation routes for a threedimensional network. Berseth et al [10] conducted a study to evaluate how the placement of pillars and doors affects pedestrian flows during evacuation of a building; a similar study was presented in Ref. [11].…”

Section: Evacuationmentioning

confidence: 99%

Optimized evacuation route based on crowd simulation

et al. 2017

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An evacuation plan helps people move away from an area or a building. To assist rapid evacuation, we present an algorithm to compute the optimal route for each local region. The idea is to reduce congestion and maximize the number of evacuees arriving at exits in each time span. Our system considers crowd distribution, exit locations, and corridor widths when determining optimal routes. It also simulates crowd movements during route optimization. As a basis, we expect that neighboring crowds who take different evacuation routes should arrive at respective exits at nearly the same time. If this is not the case, our system updates the routes of the slower crowds. As crowd simulation is non-linear, the optimal route is computed in an iterative manner. The system repeats until an optimal state is achieved. In addition to directly computing optimal routes for a situation, our system allows the structure of the situation to be decomposed, and determines the routes in a hierarchical manner. This strategy not only reduces the computational cost but also enables crowds in different regions to evacuate with different priorities. Experimental results, with visualizations, demonstrate the feasibility of our evacuation route optimization method.

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Environment optimization for crowd evacuation

Cited by 42 publications

References 28 publications

CODE: Crowd‐optimized design of environments

CODE: Crowd‐optimized design of environments

Interactive spatial analytics for human-aware building design

Optimized evacuation route based on crowd simulation

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