Partitioning algorithms for agent-based crowd simulation

Unlike conventional crowd simulations for what-if analysis, agent-based crowd simulations for real-time applications are an emerging research topic and an important tool for better crowd managements in smart cities. Recent studies have attempted to incorporate the real-time crowd observations into crowd simulations for real-time crowd forecasting and management; however, crowd flow forecasting considering individual-level microscopic interactions, especially for large crowds, is still challenging. Here, we present a method that incorporates crowd observation data to forecast a large crowd flow, including thousands of individuals, using a microscopic agent-based model. By sequentially estimating both the crowd state and the latent parameter behind the crowd flows from the aggregate crowd density observation with the particle filter algorithm, the present method estimates and forecasts the large crowd flow using agent-based simulations that incorporate observation data. Numerical experiments, including a realistic evacuation scenario with 5000 individuals, demonstrated that the present method could successfully provide reasonable crowd flow forecasting for different crowd scenarios, even with limited information on crowd movements. These results support the feasibility of real-time crowd flow forecasting and subsequent crowd management, even for large but microscopic crowd problems.

In this paper, we present an algorithm for circuit partitioning with complex resource constraints in large FPGAs. Traditional partitioning methods estimate the capacity of an FPGA device by counting the number of logic blocks, however this is not accurate with the increasing diverse resource types in the new FPGA architectures. We first propose a network flow based method to optimally check whether a circuit or a subcircuit is feasible for a set of available heterogeneous resources. Then the feasibility checking procedure is integrated in the FM‐based algorithm for circuit partitioning. Incremental flow technique is employed for efficient implementation. Experimental results on the MCNC benchmark circuits show that our partitioning algorithm not only yields good results, but also is efficient. Our algorithm for partitioning with complex resource constraints is applicable for both multiple FPGA designs (e.g., logic emulation systems) and partitioning‐based placement algorithms for a single large hierarchical FPGA (e.g., Actel′s ES6500 FPGA family).

Agent-based crowd simulation: an in-depth survey of determining factors for heterogeneous behavior

Simulating turbulent flows in a city of many thousands of buildings using general high-resolution microscopic simulations requires a grid number that is beyond present computer resources. We thus regard a city as porous media and divide the whole hybrid domain into a porous city region and a clear fluid region, which are represented by a macroscopic k–\({\varepsilon}\) model. Some microscopic information is neglected by the volume-averaging technique in the porous city to reduce the calculation load. A single domain approach is used to account for the interface conditions. We investigated the turbulent airflow through aligned cube arrays (with 7, 14 or 21 rows). The building height H, the street width W, and the building width B are the same (0.15 m), and the fraction of the volume occupied by fluid (i.e. the porosity) is 0.75; the approaching flow is parallel to the main streets. There are both microscopic and macroscopic simulations, with microscopic simulations being well validated by experimental data. We analysed microscopic wind conditions and the ventilation capacity in such cube arrays, and then calculated macroscopic time-averaged properties to provide a comparison for macroscopic simulations. We found that the macroscopic k–\({\varepsilon}\) turbulence model predicted the macroscopic flow reduction through porous cube clusters relatively well, but under-predicted the macroscopic turbulent kinetic energy (TKE) near the windward edge of the porous region. For a sufficiently long porous cube array, macroscopic flow quantities maintain constant conditions in a fully developed region.

Simulation cloning is an efficient way to analyze multiple configurations in a parameter exploration task. This paper presents a generic approach to perform incremental agent-based simulation cloning and discusses its implementation on GPU. Compared with the incremental cloning of parallel and distributed simulation (PADS), cloning agent-based simulation (ABS) has new challenges due to the unique way how ABS is executed. In this paper, to support incremental cloning, mechanisms for both actively and passively cloning agents are proposed. A scheme to maintain the correct context of each cloned ABS instance is developed. In addition, a strategy to restrain the propagation of passive cloning in order to maximize computation sharing amongst cloned ABS instances is also investigated. The implementation of our proposed approach on GPU supports concurrent execution of agents within each simulation instance as well as concurrent execution of multiple simulation instances. Performance of the proposed approach is evaluated and analyzed using a case study of an agent-based evacuation simulation on a NVIDIA Quadro 2000 GPU. Our experiment results demonstrate that cloning can significantly speed up the overall parameter exploration task. The proposed approach achieves 2.4 to 5.1 times speedup for parameter exploration tasks containing 8 to 125 simulation instances that evaluate different parameter configurations.

Quicksort is an important algorithm that uses the divide and conquer concept, and it can be run to solve any problem. The performance of the algorithm can be improved by implementing this algorithm in parallel. In this paper, the parallel sorting algorithm named the Multi-Deque Partition Dual-Deque Merge Sorting algorithm (MPDMSort) is proposed and run on a shared memory system. This algorithm contains the Multi-Deque Partitioning phase, which is a block-based parallel partitioning algorithm, and the Dual-Deque Merging phase, which is a merging algorithm without compare-and-swap operations and sorts the small data with the sorting function of the standard template library. The OpenMP library, which is an application programming interface used to develop the parallel implementation of this algorithm, is implemented in MPDMSort. Two computers (one with an Intel Xeon Gold 6142 CPU and the other with an Intel Core i7-11700 CPU) running Ubuntu Linux are used in this experiment. The results show that MPDMSort is faster than parallel balanced quicksort and multiway merge sort on the large random distribution data. A speedup of 13.81times and speedup per thread of 0.86 can be obtained. Thus, developers can use these parallel partitioning and merging algorithms to improve the performance of related algorithms.

This paper presents the results of an experimental study to evaluate the effectiveness of multiple synchronization protocols and partitioning algorithms in reducing the execution time of switch-level models of VLSI circuits. Specific contributions of this paper include: (i) parallelizing an existing switch-level simulator such that the model can be executed using conservative and optimistic simulation protocols with minor changes, (ii) evaluating effectiveness of several partitioning algorithms for parallel simulation, and (iii) demonstrating speedups with both conservative and optimistic simulation protocols for seven circuits, ranging in size from 3K transistors to about 87K transistors.

Road traffic prediction is a major challenge for urban operators and planners alike, as it is difficult to model (drivers’ behaviours being complex). Different types of urban traffic simulators have been proposed in the past: macroscopic simulators, fast but not particularly accurate; microscopic simulators, accurate but slow; and mesoscopic simulators, a trade-off between macroscopic and microscopic simulators. The challenge is that a good simulator has to be both accurate and fast, as the prediction tasks required by traffic operators and planners often need to be done quickly. In this paper, we present RONIN, an open-source traffic simulator that is both orders of magnitude faster than the state-of-the-art microscopic simulator (SUMO) while being more accurate than a typical macroscopic simulator. RONIN is designed as a mesoscopic urban traffic simulator and exploits the location of individual vehicles while also only estimating their trajectories. Besides, unlike most simulators, RONIN is interoperable with a microscopic simulator (i.e., SUMO) by design thus allowing the operators to mix microscopic and mesoscopic speed/accuracy in their traffic management.

This paper proposes a rule-based motion planning system for agent-based crowd simulation, consisting of sets of rules for both collision avoidance and collision response. In order to avoid an on-coming collision, a set of rules for velocity sampling and evaluation is proposed, which aims to choose a velocity with an expected time to collision larger than a defined threshold. In order to improve the efficiency over existing methods, the sampling procedure terminates upon finding an appropriate velocity. Moreover, the proposed motion planning system does not guarantee a collision-free movement. In case of collision, another set of rules is also defined to direct the agent to make a corresponding response. The experiment results show that the proposed method can be applied into different scenarios, while making the simulation execution efficient.

The paper provides support for the definition of COVID-19 protocols in order to allow the safe re-opening of an educational building. It also derives a reusable approach extendable to other building typologies. The integrated adoption of multiple simulation-oriented technologies is investigated. A case study is considered, where crowd simulation, agent-based simulation, and communication tools have been integrated with a hybrid approach. By means of computer games, the adoption of which is within the scope of this paper, end-users can experience school use processes within a virtual environment (1) contributing to the realism of the simulation and (2) obtaining useful information regarding the protocols in force to re-duce COVID-19 risks.

Microscopic simulation is an established tool in traffic engineering and research in which aggregated traffic performance measures are inferred from the simulation of individual agents. Measures describing the safety and efficiency of road user interactions gain importance for recent developments such as automated vehicles and urban cycling. However, current simulation frameworks model interactions including cyclists without considering the constraints of two-wheeler dynamics (mechanics of a bicycle in motion) that limit feasible maneuvers in a cycling conflict. To address this issue, we propose to bring bicycle dynamics to traffic simulation. We demonstrate that a novel reformulation of the social force framework can create input signals for a controlled inverted pendulum bicycle model and thereby enable more realistic two-dimensional open space simulation of cyclist interactions. The inverted pendulum model introduces the need to stabilize the bicycle as a constraint to the reactive behavior of simulated cyclists. Furthermore, it enables the simulation of countersteering and weaving for stabilization. Our cyclist social forces have anisotropic force fields with respect to relative interaction position and orientation to describe the varying interaction constellations in open space. With these models, we simulate the yaw angle step response and four test cases with up to three cyclists to show that the generated trajectories notably differ from results obtained from a 2D bicycle model without roll angle simulation. Measurements of the maximum lateral path deviation and post-encroachment time show that these differences are relevant for typical applications. Our work demonstrates the potential of introducing physics-based bicycle dynamics to the microscopic simulation of individual road user interactions and the fundamental capability of our reformulated cyclist social forces to do so. Going further, we plan to calibrate and validate our model based on naturalistic cycling data to support the initial results of this work.

Soil-water interaction is important to understand various soil behaviors. However, the theoretical understanding of soil-water interaction mechanisms is still incomplete especially in the adsorptive regime of soil water retention curves. Molecular simulation techniques were introduced herein to fill historical knowledge gaps in classical soil mechanics, to provide a novel angle to characterize soil behaviors and to promote the theoretical understanding of soil-water interaction. First, a general framework was developed to determine the contact angles of soil minerals. This procedure was employed to simulate the contact angles of α-quartz, orthoclase and muscovite. The simulated contact angles showed good agreement with the reported experimental or numerical results and thus substantiated the feasibility and accuracy of the proposed method. Second, molecular dynamics was employed to investigate the freezing and melting of water confined in nano-size pores. A general framework based on molecular dynamics simulations was developed to investigate the phase transition behavior of water confined in nano-size pores. It is found that the Young-Laplace equation may not apply in the low temperature range. An unfreezable threshold was identified in the phase composition curves and found to correspond to a pore diameter of 2.3±0.1 nm. Third, molecular dynamics was utilized to understand stress states of porous materials. A general framework was developed to extract effective stress from molecular simulations. Numerical simulations showed that the intergranular stress is different from the effective stress. Then, another simulation procedure was established to characterize nanoscale liquid bridges. Comparisons between macroscopic solution and simulation results revealed that the interplay of adsorption and capillarity is substantial at the nanoscale. At last, a general theoretical framework based on metadynamics was proposed to determine the lowest matric potential. The matric potential was derived from partial volume free energy and can be further calculated by the adsorption free energy. The lowest matric potential was determined as -2.00 GPa. In all of these studies, molecular simulations have shown strong potentials to resolve critical issues in soil behavior involving multiple phases. It is expected that the proposed general frameworks will open a new window to characterize soil-water interaction.

Agent-based simulations are an increasingly popular means of exploring and understanding complex social systems. In order to be useful, these simulations must capture a range of aspects of the modeled situation, each possibly requiring distinct expertise. Moreover, different paradigms may be useful in modelling, ranging from those that use many lightweight reactive agents, to those that use cognitive agents, to those that focus on agent teams and organisational structures. There is need for an architecture which supports the development of a large simulation, through the integration of separately developed modules. This paper describes a framework and architecture which facilitates the integration of multiple agent-based simulations into a single global simulation. This architecture naturally supports distributed simulation and incremental development, which are ways of addressing the computational and conceptual complexity of such systems. In this paper we focus particularly on how to ensure proper management of simulation data that is affected by agents in different modules, at the same logical time. We also provide some preliminary performance evaluation addressing scalability, as well as a comparison of how other available systems handle the issue of shared data.

Pedestrian simulation is a challenging and fruitful application area for agent-based modeling and simulation in the traffic and transportation domain. In this paper we will present the concepts and results of a particular project study: an agent-based simulation of pedestrian traffic of the complete railway station of Bern during the most busy morning hours. Overall more than 40 000 agents are passing through during 1,5 virtual hours. Going beyond traditional approaches for microscopic pedestrian simulation, our simulated pedestrians are not only capable of moving without collisions between two pre-defined locations, but are able to flexibly plan and re-plan their way through the railway station. A short glance and some discussion about the potential of agent-based pedestrian simulation closes this contribution.

Article Free Access Share on A general purpose multiple way partitioning algorithm Authors: Ching-Wei Yeh Computer Science and Engineering Department, University of California, San Diego Computer Science and Engineering Department, University of California, San DiegoView Profile , Chung-Kuan Cheng Computer Science and Engineering Department, University of California, San Diego Computer Science and Engineering Department, University of California, San DiegoView Profile , Ting-Ting Y. Lin Electrical and Computer Engineering Department, University of California, San Diego Electrical and Computer Engineering Department, University of California, San DiegoView Profile Authors Info & Claims DAC '91: Proceedings of the 28th ACM/IEEE Design Automation ConferenceJune 1991 Pages 421–426https://doi.org/10.1145/127601.127706Online:01 June 1991Publication History 53citation315DownloadsMetricsTotal Citations53Total Downloads315Last 12 Months7Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF