Crowd-driven mid-scale layout design

Feng, Tian; Yu, Lap-Fai; Yeung, Sai-Kit; Yin, KangKang; Zhou, Kun

doi:10.1145/2897824.2925894

Cited by 79 publications

(44 citation statements)

References 54 publications

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“…In the future, we plan to discuss such evacuation guidance with potential users, seek their feedback, and eventually develop a practical application. It would be compelling to compute evacuation routes combined with traffic [51] and layout design [52]. Finally, it would be important to improve the crowd simulation based on human factors and the data extracted from crowd videos [47].…”

Section: Discussionmentioning

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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Section: Discussionmentioning

confidence: 99%

Optimized evacuation route based on crowd simulation

et al. 2017

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“…Their subsequent work [PYB*16] proposes an integer‐programming‐based approach to generate networks starting from functional specifications. Feng et al [FYY*16] focus on mid‐scale layout modeling based on human crowds. Given a layout domain, their approach synthesizes crowd‐aware layouts by considering the crowd flow.…”

Section: Related Workmentioning

confidence: 99%

MIQP‐based Layout Design for Building Interiors

Fan

Liu

et al. 2018

Computer Graphics Forum

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We propose a hierarchical framework for the generation of building interiors. Our solution is based on a mixed integer quadratic programming (MIQP) formulation. We parametrize a layout by polygons that are further decomposed into small rectangles. We identify important high‐level constraints, such as room size, room position, room adjacency, and the outline of the building, and formulate them in a way that is compatible with MIQP and the problem parametrization. We also propose a hierarchical framework to improve the scalability of the approach. We demonstrate that our algorithm can be used for residential building layouts and can be scaled up to large layouts such as office buildings, shopping malls, and supermarkets. We show that our method is faster by multiple orders of magnitude than previous methods.

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“…Feng et al. [FYY*16] propose an approach to generate mid‐scale layout designs optimized by crowd properties that assume each agent knows the locations of their destinations. They use non‐linear trained regressors to avoid hundreds of long‐time simulations and, given a domain like a shopping mall, the method can find the paths and sites optimizing mobility, accessibility and coziness.…”

Section: Related Workmentioning

confidence: 99%

“…Overall, our approach has three main differences as compared to prior work: (i) we use the contagion concept from [BDM*15] to model the interaction among people and urban signs and to provide a way of simulating the sharing of visible information in an initially unknown pedestrian environment; (ii) we use inverse modelling to determine a parameterized procedural representation of an urban walkway system and (iii) we simulate large‐scale human crowds' one order of magnitude faster than [FYY*16] and [dLBRM*12].…”

Section: Related Workmentioning

confidence: 99%

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Urban Walkability Design Using Virtual Population Simulation

Mathew

Knob

Musse

et al. 2018

Computer Graphics Forum

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We present a system to generate a procedural environment that produces a desired crowd behaviour. Instead of altering the behavioural parameters of the crowd itself, we automatically alter the environment to yield such desired crowd behaviour. This novel inverse approach is useful both to crowd simulation in virtual environments and to urban crowd planning applications. Our approach tightly integrates and extends a space discretization crowd simulator with inverse procedural modelling. We extend crowd simulation by goal exploration (i.e. agents are initially unaware of the goal locations), variable‐appealing sign usage and several acceleration schemes. We use Markov chain Monte Carlo to quickly explore the solution space and yield interactive design. We have applied our method to a variety of virtual and real‐world locations, yielding one order of magnitude faster crowd simulation performance over related methods and several fold improvement of crowd indicators.

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Crowd-driven mid-scale layout design

Cited by 79 publications

References 54 publications

Optimized evacuation route based on crowd simulation

Optimized evacuation route based on crowd simulation

MIQP‐based Layout Design for Building Interiors

Urban Walkability Design Using Virtual Population Simulation

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