Sharif Digital Repository

One of the most important capabilities expected from an autonomous vehicle is avoiding collision with obstacles in its path. For this purpose, autonomous vehicle must be able to perform an emergency maneuver as soon as the obstacle is detected. This paper presents a method for designing and performing an emergency maneuver in order to avoid collision with a fixed or moving obstacle in the path. A sinusoidal or exponential trajectory, which is a function of the relative distance between vehicle and obstacle, is designed as the desired trajectory for lateral motion of the vehicle. A sliding mode controller is designed in order to guarantee that the vehicle tracks that desired trajectory. The... 

Nonpharmaceutical measures such as social distancing can play an important role in controlling the spread of an epidemic. In this paper, we use a mathematical model combining human mobility and disease spreading. For the mobility dynamics, we design an agent-based model consisting of pedestrian dynamics with a novel type of force to resemble social distancing in crowded sites. For the spreading dynamics, we consider the compartmental susceptible-exposed-infective (SEI) dynamics plus an indirect transmission with the footprints of the infectious pedestrians being the contagion factor. We show that the increase in the intensity of social distancing has a significant effect on the exposure... 

There are many practical situations where it is desirable or even required to achieve stable convergence in the finite-time domain. In this paper, a simple distributed continuous-time protocol is introduced that guarantees finite-time consensus in networks of autonomous agents. Protocol convergence in weighted directed/undirected and fixed/switching networks is explored based on a Lyapunov analysis. The stability of the system and the solvability of the consensus algorithm are proved for network topologies that contain a spanning tree frequently enough over contiguous time intervals. The decision value for different topologies and for multi-rate integrator agents is investigated, and a novel... 

Motion planning in an autonomous agent is responsible for providing smooth, safe and efficient navigation. Many solutions for dealing this problem have been offered, one of which is, Artificial Potential Fields (APF). APF is a simple and computationally low cost method which keeps the robot away from the obstacles in environment. However, this approach suffers from trapping in local minima of potential function and then fails to produce motion plans. Furthermore, Oscillation in presence of obstacles or in narrow passages is another disadvantage of the method which makes it unqualified for many planning problems. In this paper we aim to resolve these deficiencies by a novel approach which... 

Proliferation of private distributed energy resources (DERs) necessitates devising effective energy management frameworks. This paper aims at establishing a decentralized model for the optimal dispatch of DERs in smart grids. The objective function is to minimize expected procurement cost of demand while profit of private DER owners is not sacrificed. Unit management modules (UMMs) embedded in private DERs and a central agent are autonomous agents of the model. The approach is iterative. In each iteration, the central agent announces to UMMs its procurement strategy, which contains purchased powers and their prices. Then, UMMs optimize and send back their output power and selling price... 

The deployment of multi-agent systems in presence of obstacle deals with autonomous motion of agents toward a specified target by sensing each other and boundaries of obstacles. In this paper, asynchronous, scalable, distributed algorithm is used to deploy agents. Boundaries of obstacles are modeled by virtual agents. Algorithm was implemented by solving continuous n-median problem called generalized Fermat-Weber problem. It is shown that deployment is performed when position of real agents are the geometric median of their Voronoi cells. Simulation results show the validity of the proposed algorithm very well  

We consider the computational complexity of pure Nash equilibria in graphical games. It is known that the problem is NP-complete in general, but tractable (i.e., in P) for special classes of graphs such as those with bounded treewidth. It is then natural to ask: is it possible to characterize all tractable classes of graphs for this problem? In this work, we provide such a characterization for the case of bounded in-degree graphs, thereby resolving the gap between existing hardness and tractability results. In particular, we analyze the complexity of PURE-GG(C, -), the problem of deciding the existence of pure Nash equilibria in graphical games whose underlying graphs are restricted to class... 

Mobile Ad-hoc Networks are networks that have a dynamic topology without any fixed infrastructure. To transmit information in ad-hoc networks, we need robust protocols that can cope with constant changes in the network topology. The known routing protocols for mobile ad-hoc networks can be classified in two major categories: proactive routing protocols and reactive routing protocols. Proactive routing protocols keep the routes up-to-date to reduce delay in real-time applications but they have high control overhead. The control overhead in reactive routing protocols is much less than proactive routing protocols; however, the routes are discovered on demand, which is not suitable for real-time... 

Semantic segmentation is one of the basic, yet essential scene understanding tasks for an autonomous agent. The recent developments in supervised machine learning and neural networks have enjoyed great success in enhancing the performance of the state-of-the-art techniques for this task. However, their superior performance is highly reliant on the availability of a large-scale annotated dataset. In this letter, we propose a novel fully unsupervised semantic segmentation method, the so-called Information Maximization and Adversarial Regularization Segmentation (InMARS). Inspired by human perception which parses a scene into perceptual groups, rather than analyzing each pixel individually, our... 

Making proper decisions in today's complex world is a challenging task for decision makers. A promising approach that can support decision makers to have a better understanding of complex systems is agent-based modeling (ABM). ABM has been developing during the last few decades as a methodology with many different applications and has enabled a better description of the dynamics of complex systems. However, the prescriptive facet of these applications is rarely portrayed. Adding a prescriptive decision-making (DM) aspect to ABM can support the decision makers in making better or, in some cases, optimized decisions for the complex problems as well as explaining the investigated phenomena. In... 

Background and objective There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth. Methods We make an... 

Severe peak rebounds are likely in absence of a system-wide coordination among customers participating in demand response programs. This paper aims to establish a decentralized system-wide framework to coordinate demand response of residential customers in a smart grid. The objective of the framework is to modify system load profile provided that customers' payments are minimized, and their comfort and privacy are preserved. Home load management (HLM) modules, embedded in customers' smart meters are autonomous agents of the framework. The energy service provider iteratively exchanges load information with HLM modules in the hope of achieving his desired load profile. In each iteration, the... 

Expanding the electricity market into the retail domain calls for inexpensive mass-produced smart devices that enable the small customers to participate in local energy transactions by managing the energy production/consumption and submitting buy/sell bids to the market. In this context, this paper presents a mathematically proven as well as practical approach for bidding of an autonomous smart transactive agent in local energy markets. To reach this goal, behaviors of both riskneutral and risk-averse agents selling energy to the market are modeled taking into account expected profit and risk criteria. Based on this modeling procedure, an optimal multi-step quantity-price bidding strategy is... 

This article provides an agent-based model of a hypothetical standalone electricity network to identify how the feed-in tariffs and the installed capacity of wind power, calculated in percentage of total system demand, affect the electricity consumption from renewables. It includes the mechanism of electricity pricing on the Day Ahead Market (DAM) and the Imbalance Market (IM). The extra production volumes of Electricity from Renewable Energy Sources (RES-E) and the flexibility of electrical consumption of industries is provided as reserves on the IM. Five thousand simulations were run by using the agent-based model to gather data that were then fit in linear regression models. This helped... 

The electric power industry is the main part of Science development, and today, with the advent of technology, the demand for electric power has been expanded. On the other hand, smart grids are developing heavily. One of the notable features of these networks is the presence of a plug-in hybrid electric vehicle (PHEV). The addition of these cars to the network has its own advantages and disadvantages. One of the most important issues in smart grids is network management and control of critical system parameters. In this paper the effect of these cars on the grid is investigated. These vehicles impose an increase in production capacity in the uncontrolled charge mode. They also have the... 

Socio-ecological systems include diverse resources of complexity involving complicated interactions, feedback, dynamic behavior patterns, heterogeneity in agents’ characteristics and behaviors, as well as system uncertainties. Agent-based modeling is introduced as a tool to simulate different levels of stakeholders and interactions, including individual, group, and institutional agents in complex socio-ecological systems. In the present study, an agent-based model was developed to explore sustainable solutions in uncertain conditions for groundwater restoration of a critical aquifer in the Lake Urmia Basin, Iran. Different projects for aquifer restoration such as wells monitoring, license... 

This study proposes a novel socio-hydrological modeling framework for assessing the performance of complex water resources systems. It employs and integrates agent-based modeling (ABM) and the theory of planned behavior (TPB) into the socio-hydrological modeling framework to account for agents’ behaviors. Due to farmers’ major role in anthropogenic droughts, this paper mainly focuses on farmers’ behavior. The TPB framework and the agents’ behavioral rules in ABM are structured based on the data obtained from field questionnaires and interviews by the farmers in the Zarrineh River Basin as the main river feeding the Urmia Lake. The proposed modeling framework, including the TPB and ABM... 

The electric power industry is the main part of Science development, and today, with the advent of technology, the demand for electric power has been expanded. On the other hand, smart grids are developing heavily. One of the notable features of these networks is the presence of a plug-in hybrid electric vehicle (PHEV). The addition of these cars to the network has its own advantages and disadvantages. One of the most important issues in smart grids is network management and control of critical system parameters. In this paper the effect of these cars on the grid is investigated. These vehicles impose an increase in production capacity in the uncontrolled charge mode. They also have the...