Urban Walkability Design Using Virtual Population Simulation

Abstract

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.

Authoring Virtual Crowds: A Survey

“…Then, the scheduler takes these descriptions for building a sequence of tasks to be performed, minimising the effort measured by the distance that agents have to move to complete the activities. Mathew et al [MKMA19] also deal with user‐specified goals and intentions, modifying the urban layout according to those specifications. A visual example of their framework can be seen in Figure 4.…”

“…Urban walkability design example from [MKMA19]. Inputs of the framework are: urban layout (a), agent goals and intentions from which 2D (b) and 3D (c) layout modifications can be inferred, and editable attributes such as densities (d), (e).…”

A history of crowd simulation: the past, evolution, and new perspectives

“…In addition, the authors considered the complexity of the environment and a statistical distribution to represent, respectively, the impact of obstacles and the other agents in future positions of agents. Mathew [64] propose an inverse approach that is useful both to crowd simulation in virtual environments and urban crowd planning applications. Indeed, the authors propose a way where the crowd impacts the environment using optimization algorithms.…”

DataStorm: Coupled, Continuous Simulations for Complex Urban Environments

“…Data-driven models and computer simulations that take into account available domain knowledge, in addition to past data and observations, represent a promising approach in understanding and predicting complex urban processes [4,15,33,45] and in information-driven decision-making in the presence of shifting demands and available resources [8]. Therefore, data-driven models and simulations for preparedness and response are increasingly critical in predicting geo-temporal evolution of urban systems and effectively managing emergencies through intervention measures [10,11,31,32,35,39].…”

“…As discussed in the introduction, simulations are being increasingly used for understanding and predicting complex urban processes [4,15,33,45], including in applications including disaster preparedness and response [8,10,11,31,32,35,39]. In this section, we provide an overview of some of the key technologies underlying complex coupled simulation and decision flow systems.…”