Improving heuristics-based model to reproduce lane formation

2018 ◽  
Vol 29 (08) ◽  
pp. 1850069 ◽  
Author(s):  
Ning Guo ◽  
Hao-Xiang Liu ◽  
Rui Jiang ◽  
Bin Jia ◽  
Mao-Bin Hu
Keyword(s):  
Objective Function ◽  
Pedestrian Flow ◽  
Target Direction ◽  
Self Organized ◽  
Wide Range ◽  
Lane Formation ◽  
Simulation Results

Lane formation is an important self-organized phenomenon in bidirectional pedestrian flow. Our experiment shows that in a wide range of pedestrian density, quick lane formation can be observed in a ring corridor. It is shown that the original heuristics-based model fails to reproduce lane formation with the increase of pedestrian density. This is because a pedestrian cannot correctly evaluate the target direction, when he/she is too close to others. We propose an improved heuristics-based model, in which the objective function of the target direction has been modified. Simulation results are in agreement with experimental ones.

scholarly journals Lévy walk process in self-organization of pedestrian crowds

2019 ◽  
Vol 16 (153) ◽  
pp. 20180939 ◽  
Author(s):  
Hisashi Murakami ◽  
Claudio Feliciani ◽  
Katsuhiro Nishinari
Keyword(s):  
Self Organization ◽  
Pedestrian Flow ◽  
Direct Path ◽  
Distributed Resources ◽  
Scale Free ◽  
Lévy Walk ◽  
Self Organized ◽  
Levy Walk ◽  
Movement Strategy ◽  
Lane Formation

Similar to other animal groups, human crowds exhibit various collective patterns that emerge from self-organization. Recent studies have emphasized that individuals anticipate their neighbours' motions to seek their paths in dynamical pedestrian flow. This path-seeking behaviour results in deviation of pedestrians from their desired directions (i.e. the direct path to their destination). However, the strategies that individuals adopt for the behaviour and how the deviation of individual movements impact the emergent organization are poorly understood. We here show that the path-seeking behaviour is performed through a scale-free movement strategy called a Lévy walk, which might facilitate transition to the group-level behaviour. In an experiment of lane formation, a striking example of self-organized patterning in human crowds, we observed how flows of oppositely moving pedestrians spontaneously separate into several unidirectional lanes. We found that before (but not after) lane formation, pedestrians deviate from the desired direction by Lévy walk process, which is considered optimal when searching unpredictably distributed resources. Pedestrians balance a trade-off between seeking their direct paths and reaching their goals as quickly as possible; they may achieve their optimal paths through Lévy walk process, facilitating the emergent lane formation.

scholarly journals Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

2021 ◽  
Vol 11 (8) ◽  
pp. 3623
Author(s):  
Omar Said ◽  
Amr Tolba
Keyword(s):  
Packet Loss ◽  
Large Scale ◽  
Performance Metrics ◽  
Medical System ◽  
Healthcare Data ◽  
High Altitude Platforms ◽  
Wide Range ◽  
Simulation Results ◽  
Healthcare Architecture ◽  
The Internet Of Things

Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage, throughput, percentage of served users, and percentage of each exchanged data type. The simulation results demonstrate that the proposed IoT-enabled healthcare architecture outperforms the traditional healthcare architecture.

scholarly journals Proton Exchange Membrane Fuel Cells Modeling Using Chaos Game Optimization Technique

2021 ◽  
Vol 13 (14) ◽  
pp. 7911
Author(s):  
Ibrahim Alsaidan ◽  
Mohamed A. M. Shaheen ◽  
Hany M. Hasanien ◽  
Muhannad Alaraj ◽  
Abrar S. Alnafisah
Keyword(s):  
Fuel Cell ◽  
Objective Function ◽  
Proton Exchange Membrane ◽  
Optimization Technique ◽  
Proton Exchange ◽  
Simulation Performance ◽  
Terminal Voltage ◽  
Chaos Game ◽  
Simulation Results ◽  
Exchange Membrane

For the precise simulation performance, the accuracy of fuel cell modeling is important. Therefore, this paper presents a developed optimization method called Chaos Game Optimization Algorithm (CGO). The developed method provides the ability to accurately model the proton exchange membrane fuel cell (PEMFC). The accuracy of the model is tested by comparing the simulation results with the practical measurements of several standard PEMFCs such as Ballard Mark V, AVISTA SR-12.5 kW, and 6 kW of the Nedstack PS6 stacks. The complexity of the studied problem stems from the nonlinearity of the PEMFC polarization curve that leads to a nonlinear optimization problem, which must be solved to determine the seven PEMFC design variables. The objective function is formulated mathematically as the total error squared between the laboratory measured terminal voltage of PEMFC and the estimated terminal voltage yields from the simulation results using the developed model. The CGO is used to find the best way to fulfill the preset requirements of the objective function. The results of the simulation are tested under different temperature and pressure conditions. Moreover, the results of the proposed CGO simulations are compared with alternative optimization methods showing higher accuracy.

Aerodynamic Similarity Principles and Scaling Laws for Windmilling Fans

2018 ◽  
Author(s):  
Dilip Prasad
Keyword(s):  
Rotational Speed ◽  
Pressure Loss ◽  
Scaling Laws ◽  
Dynamic Pressure ◽  
Stagnation Pressure ◽  
Design Parameters ◽  
Similarity Parameter ◽  
Wide Range ◽  
Simulation Results ◽  
Good Agreement

Windmilling requirements for aircraft engines often define propulsion and airframe design parameters. The present study is focused is on two key quantities of interest during windmill operation: fan rotational speed and stage losses. A model for the rotor exit flow is developed, that serves to bring out a similarity parameter for the fan rotational speed. Furthermore, the model shows that the spanwise flow profiles are independent of the throughflow, being determined solely by the configuration geometry. Interrogation of previous numerical simulations verifies the self-similar nature of the flow. The analysis also demonstrates that the vane inlet dynamic pressure is the appropriate scale for the stagnation pressure loss across the rotor and splitter. Examination of the simulation results for the stator reveals that the flow blockage resulting from the severely negative incidence that occurs at windmill remains constant across a wide range of mass flow rates. For a given throughflow rate, the velocity scale is then shown to be that associated with the unblocked vane exit area, leading naturally to the definition of a dynamic pressure scale for the stator stagnation pressure loss. The proposed scaling procedures for the component losses are applied to the flow configuration of Prasad and Lord (2010). Comparison of simulation results for the rotor-splitter and stator losses determined using these procedures indicates very good agreement. Analogous to the loss scaling, a procedure based on the fan speed similarity parameter is developed to determine the windmill rotational speed and is also found to be in good agreement with engine data. Thus, despite their simplicity, the methods developed here possess sufficient fidelity to be employed in design prediction models for aircraft propulsion systems.

scholarly journals Passive Target Localization Problem Based on Improved Hybrid Adaptive Differential Evolution and Nelder-Mead Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Maja B. Rosić ◽  
Mirjana I. Simić ◽  
Predrag V. Pejović
Keyword(s):  
Differential Evolution ◽  
Objective Function ◽  
Weighted Least Squares ◽  
Target Localization ◽  
Localization Problem ◽  
Ml Estimation ◽  
Comparison Results ◽  
Adaptive Differential Evolution ◽  
Highly Nonlinear ◽  
Wide Range

This paper considers a passive target localization problem in Wireless Sensor Networks (WSNs) using the noisy time of arrival (TOA) measurements, obtained from multiple receivers and a single transmitter. The objective function is formulated as a maximum likelihood (ML) estimation problem under the Gaussian noise assumption. Consequently, the objective function of the ML estimator is a highly nonlinear and nonconvex function, where conventional optimization methods are not suitable for this type of problem. Hence, an improved algorithm based on the hybridization of an adaptive differential evolution (ADE) and Nelder-Mead (NM) algorithms, named HADENM, is proposed to find the estimated position of a passive target. In this paper, the control parameters of the ADE algorithm are adaptively updated during the evolution process. In addition, an adaptive adjustment parameter is designed to provide a balance between the global exploration and the local exploitation abilities. Furthermore, the exploitation is strengthened using the NM method by improving the accuracy of the best solution obtained from the ADE algorithm. Statistical analysis has been conducted, to evaluate the benefits of the proposed modifications on the optimization performance of the HADENM algorithm. The comparison results between HADENM algorithm and its versions indicate that the modifications proposed in this paper can improve the overall optimization performance. Furthermore, the simulation shows that the proposed HADENM algorithm can attain the Cramer-Rao lower bound (CRLB) and outperforms the constrained weighted least squares (CWLS) and differential evolution (DE) algorithms. The obtained results demonstrate the high accuracy and robustness of the proposed algorithm for solving the passive target localization problem for a wide range of measurement noise levels.

Aerodynamic Similarity Principles and Scaling Laws for Windmilling Fans

2018 ◽  
Vol 140 (12) ◽  
Author(s):  
Dilip Prasad
Keyword(s):  
Rotational Speed ◽  
Pressure Loss ◽  
Scaling Laws ◽  
Dynamic Pressure ◽  
Stagnation Pressure ◽  
Design Parameters ◽  
Similarity Parameter ◽  
Wide Range ◽  
Simulation Results ◽  
Good Agreement

Windmilling requirements for aircraft engines often define propulsion and airframe design parameters. The present study is focused on two key quantities of interest during windmill operation: fan rotational speed and stage losses. A model for the rotor exit flow is developed that serves to bring out a similarity parameter for the fan rotational speed. Furthermore, the model shows that the spanwise flow profiles are independent of the throughflow, being determined solely by the configuration geometry. Interrogation of previous numerical simulations verifies the self-similar nature of the flow. The analysis also demonstrates that the vane inlet dynamic pressure is the appropriate scale for the stagnation pressure loss across the rotor and splitter. Examination of the simulation results for the stator reveals that the flow blockage resulting from the severely negative incidence that occurs at windmill remains constant across a wide range of mass flow rates. For a given throughflow rate, the velocity scale is then shown to be that associated with the unblocked vane exit area, leading naturally to the definition of a dynamic pressure scale for the stator stagnation pressure loss. The proposed scaling procedures for the component losses are applied to the flow configuration of Prasad and Lord (2010). Comparison of simulation results for the rotor-splitter and stator losses determined using these procedures indicates very good agreement. Analogous to the loss scaling, a procedure based on the fan speed similarity parameter is developed to determine the windmill rotational speed and is also found to be in good agreement with engine data. Thus, despite their simplicity, the methods developed here possess sufficient fidelity to be employed in design prediction models for aircraft propulsion systems.

scholarly journals Dynamic Routing and Coordination of Cluster for Unmanned Aerial Vehicle (UAV) Swarms

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ali Abbas ◽  
Bhawani Shankar Chowdhry ◽  
Muhammad Saqib ◽  
Vishal Dattana
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Efficient Solution ◽  
High Mobility ◽  
Combinatorial Problem ◽  
Communication Graph ◽  
Frequent Change ◽  
Swarm Optimization ◽  
Wide Range ◽  
Aerial Vehicle ◽  
Simulation Results

The flying networks provide an efficient solution for a wide range of military and commercial purposes. The demand for portable and flexible communication is directed towards a quick growth in interaction among unmanned aerial vehicles (UAVs). Due to the frequent change in topology and high mobility of vehicles, routing and coordination becomes a challenging task. To maximize the throughput of the network, this study addresses the UAV swarm’s problems related to the coordination and routing and defines the proposed solution to solve these issues. For this, a network is assumed which contains an equal number of dynamic vehicles. It also presents the communication graph concept of UAVs and designs a fixed-wing UAV model to improve the efficiency of the network in terms of throughput. Furthermore, the proposed algorithm based on Cauchy particle swarm optimization (CPSO) aims towards the better performance of UAV swarms and aims to solve the combinatorial problem. The simulation results show and confirm the performance of the proposed algorithm.

scholarly journals FLUCTUATIONS OF THE CARGO TRANSPORTED BY LIFTING CRANE: SIMULATION AND ANALYSIS

2019 ◽  
Vol 16 (5) ◽  
pp. 526-533
Author(s):  
M. S. Korytov ◽  
V. S. Shcherbakov ◽  
V. E. Belyakov
Keyword(s):  
Objective Function ◽  
Arbitrary Order ◽  
Deflection Angle ◽  
Suspension Point ◽  
Program Code ◽  
First Derivative ◽  
Urgent Task ◽  
Acceleration And Deceleration ◽  
The Deflection Angle ◽  
Simulation Results

Introduction. Reducing fluctuations in the load transported by hoisting cranes with a flexible rope suspension of the load is an urgent task since it can significantly reduce the time taken to complete the operation of moving the load. A promising direction for reducing load fluctuations is to optimize the trajectory of movement of the load suspension upper point.Materials and methods. The paper discussed the method of mathematical simulation of plane vibrations of a load moved by a crane with a horizontally moving suspension point, using the software of the MATLAB system. For modeling, the authors used the function of the MATLAB ode45 system, intended for the numerical solution of systems of non-stationary differential equations of arbitrary order.The second-order differential equation used to describe the fluctuations of the transported load and its implementation in the form of program code was presented. Moreover, the authors demonstrated the elements of program code for the analysis and visualization of simulation results.Results. The authors obtained and presented the series of graphs in the inclination angle’s changing of the cargo rope, the acceleration of the suspension point and the value of the objective function with the sinusoidal nature of the acceleration. The objective function was the sum of the absolute values of the deflection angle of the rope and the first derivative at the final moment of the suspension point’s movement with acceleration.Discussion and conclusions. As a result, the paper shows that the system with energy dissipation does not reach the zero value of the objective function even by a symmetrical nature of acceleration and deceleration of the suspension point. Therefore, it is necessary to give asymmetry to the acceleration and deceleration periods of the suspension point in order to completely absorb the residual fluctuations of the load.

Simulating pedestrian flow by an improved two-process cellular automaton model

2017 ◽  
Vol 28 (02) ◽  
pp. 1750016 ◽  
Author(s):  
Cheng-Jie Jin ◽  
Wei Wang ◽  
Rui Jiang ◽  
Li-Yun Dong
Keyword(s):  
Cellular Automaton ◽  
Critical Density ◽  
Maximum Flow ◽  
Cellular Automaton Model ◽  
Open Boundary ◽  
Flow Density ◽  
Open Boundary Conditions ◽  
Pedestrian Flow ◽  
Exchange Rule ◽  
Lane Formation

In this paper, we study the pedestrian flow with an Improved Two-Process (ITP) cellular automaton model, which is originally proposed by Blue and Adler. Simulations of pedestrian counterflow have been conducted, under both periodic and open boundary conditions. The lane formation phenomenon has been reproduced without using the place exchange rule. We also present and discuss the flow-density and velocity-density relationships of both uni-directional flow and counterflow. By the comparison with the Blue-Adler model, we find the ITP model has higher values of maximum flow, critical density and completely jammed density under different conditions.

scholarly journals Glowworm Swarm Optimization and Its Application to Blind Signal Separation

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Zhucheng Li ◽  
Xianglin Huang
Keyword(s):  
Objective Function ◽  
Global Optimum ◽  
Convergence Speed ◽  
Signal Separation ◽  
Blind Signal Separation ◽  
Swarm Optimization ◽  
Blind Signal ◽  
Glowworm Swarm Optimization ◽  
Simulation Results ◽  
Speed And Accuracy

Traditional optimization algorithms for blind signal separation (BSS) are mainly based on the gradient, which requires the objective function to be continuous and differentiable, so the applications of these algorithms are very limited. Moreover, these algorithms have problems with the convergence speed and accuracy. To overcome these drawbacks, this paper presents a modified glowworm swarm optimization (MGSO) algorithm based on a novel step adjustment rule and then applies MGSO to BSS. Taking kurtosis of the mixed signals as the objective function of BSS, MGSO-BSS succeeds in separating the mixed signals in Matlab environment. The simulation results prove that MGSO is more effective in capturing the global optimum of the objective function of the BSS algorithm and has faster convergence speed and higher accuracy, compared with particle swarm optimization (PSO) and GSO.

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