arXiv subjects

Hossein Rastgoftar

Publications and source records attributed to Hossein Rastgoftar.

52 records · Page 3Linked to original sources

arXiv2021

Boundary Control of Traffic Congestion Modeled as a Non-stationary Stochastic Process

In this paper, we introduce a new conservation-based approach to model traffic dynamics, and apply the model predictive control (MPC) approach to control the boundary traffic inflow and outflow, so that the traffic congestion is reduced. We establish an interface between the Simulation of Urban Mobility (SUMO) software and MATLAB to define a network of interconnected roads (NOIR) as a directed graph, and present traffic congestion management as a network control problem. By formally specifying the traffic feasibility conditions, and using the linear temporal logic, we present the proposed MPC-based boundary control problem as a quadratic programming with linear equality and inequality constraints. The success of the proposed traffic boundary control is demonstrated by simulation of traffic congestion control in Center City Philadelphia.

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arXiv2021

Conservation-Based Modeling and Boundary Control of Congestion with an Application to Traffic Management in Center City Philadelphia

This paper develops a conservation-based approach to model traffic dynamics and alleviate traffic congestion in a network of interconnected roads (NOIR). We generate a NOIR by using the Simulation of Urban Mobility (SUMO) software based on the real street map of Philadelphia Center City. The NOIR is then represented by a directed graph with nodes identifying distinct streets in the Center City area. By classifying the streets as inlets, outlets, and interior nodes, the model predictive control (MPC) method is applied to alleviate the network traffic congestion by optimizing the traffic inflow and outflow across the boundary of the NOIR with consideration of the inner traffic dynamics as a stochastic process. The proposed boundary control problem is defined as a quadratic programming problem with constraints imposing the feasibility of traffic coordination, and a cost function defined based on the traffic density across the NOIR.

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arXiv2021

Continuum Deformation Coordination of Multi-Agent Systems Using Cooperative Localization

This paper studies the problem of decentralized continuum deformation coordination of multi-agent systems aided by cooperative localization. We treat agents as particles inside a triangular continuum (deformable body) in a2-D motion space and let the continuum deformation coordination be defined by three leaders located at vertices of a triangle, called the leading triangle. The leaders desired trajectories are assigned as the solution of a constrained optimal control problem such that safety requirements are satisfied in the presence of disturbance and measurement noise. Followers distributed inside the leading tri-angle acquire continuum deformation in a decentralized fashion by integrating cooperative localization and local communication. Specifically, cooperative localization estimates the global positions of all agents using relative position measurements based primarily on proximity of agents. Simulation results are presented for a network of ten agents.

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arXiv2021

Safe Affine Transformation-Based Guidance of a Large-Scale Multi-Quadcopter System (MQS)

This paper studies the problem of affine transformation-based guidance of a multi-quadcopter system (MQS) in an obstacle-laden environment. Such MQSs can perform a variety of cooperative tasks including information collection, inspection mapping, disinfection, and firefighting. The MQS affine transformation is an approach to a decentralized leader-follower coordination guided by n +1 leaders, where leaders are located at vertices of an n-D simplex, called leading simplex, at any time t. The remaining agents are followers acquiring the desired affine transformation via local communication. Followers are contained in a rigid-size ball at any time t but they can be distributed either inside or outside the leading simplex. By eigen-decomposition of the affine transformation coordination, safety in a large-scale MQS coordination can be ensured by constraining eigenvalues of the affine transformation. Given the initial and final configurations of the MQS, A-star search is applied to optimally plan safe coordination of a large-scale MQS minimizing the travel distance between the the initial and final configuration. The paper also proposes a proximity-based communication topology for followers to assign communication weights with their in-neighbors and acquire the desired coordination with minimal computation cost.

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arXiv2021

Integration of A-Star Search and Classic Optimal Control for Safe Planning of Continuum Deformation of a Multi-Quadcopter System

This paper offers an algorithmic approach to plan continuum deformation of a multi-quadcopter system (MQS) in an obstacle-laden environment. We treat the MQS as finite number of particles of a deformable body coordinating under a homogeneous transformation. In this context, we define the MQS homogeneous deformation coordination as a decentralized leader-follower problem, and integrate the principles of continuum mechanics, A-Star search method, and optimal control to safety and optimally plan MQS continuum deformation coordination. In particular, we apply the principles of continuum mechanics to obtain the safety constraints, use the A-Star search method to assign the intermediate configurations of the leaders by minimizing the travel distance of the MQS, and determine the leaders' optimal trajectories by solving a constrained optimal control problem. The optimal planning of the continuum deformation coordination is acquired by the quadcopter team in a decentralized fashion through local communication.

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arXiv2021

A Physics-Based Finite-State Abstraction for Traffic Congestion Control

This paper offers a finite-state abstraction of traffic coordination and congestion in a network of interconnected roads (NOIR). By applying mass conservation, we model traffic coordination as a Markov process. Model Predictive Control (MPC) is applied to control traffic congestion through the boundary of the traffic network. The optimal boundary inflow is assigned as the solution of a constrained quadratic programming problem. Additionally, the movement phases commanded by traffic signals are determined using receding horizon optimization. In simulation, we show how traffic congestion can be successfully controlled through optimizing boundary inflow and movement phases at traffic network junctions.

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arXiv2020

Scalable Vehicle Team Continuum Deformation Coordination with Eigen Decomposition

The continuum deformation leader-follower cooperative control strategy models vehicles in a multi-agent system as particles of a deformable body. A desired continuum deformation is defined based on leaders' trajectories and acquired by followers in real-time through local communication. The existing continuum deformation theory requires followers to be placed inside the convex simplex defined by leaders. This constraint is relaxed in this paper. We prove that under suitable assumptions any (n+1)(n=1,2,3) vehicles forming an n-D simplex can be selected as leaders while followers, arbitrarily positioned inside or outside the leading simplex, can acquire a desired continuum deformation in a decentralized fashion. The paper's second contribution is to assign a one-to-one mapping between leaders' smooth trajectories and homogeneous deformation features obtained by continuum deformation eigen-decomposition. Therefore, a safe and smooth continuum deformation coordination can be planned either by shaping homogeneous transformation features or by choosing appropriate leader trajectories. This is beneficial to efficiently plan and guarantee inter-agent collision avoidance in a large-scale group. A simulation case study is reported in which a virtual convex simplex contains a quadcopter vehicle team at any time t; A* search is applied to optimize quadcopter team continuum deformation in an obstacle-laden environment.

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arXiv2019

An Integrative Data-Driven Physics-Inspired Approach to Traffic Congestion Control

This paper offers an integrative data-driven physics-inspired approach to model and control traffic congestion in a resilient and efficient manner. While existing physics-based approaches commonly assign density and flow traffic states by using the Fundamental Diagram, this paper specifies the flow-density relation using past traffic information recorded in a time sliding window with a constant horizon length. With this approach, traffic coordination trends can be consistently learned and incorporated into traffic planning. This paper also models traffic coordination as a probabilistic process and obtains traffic feasibility conditions using linear temporal logic. Model productive control (MPC) is applied to control traffic congestion through the boundary of the traffic network. Therefore, the optimal boundary inflow is assigned as the solution of a constrained quadratic programming problem.

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arXiv2019

Resilient Continuum Deformation Coordination

This paper applies the principles of continuum mechanics to safely and resiliently coordinate a multi-agent team. A hybrid automation with two operation modes, Homogeneous Deformation Mode (HDM) and Containment Exclusion Mode (CEM), are developed to robustly manage group coordination in the presence of unpredicted agent failures. HDM becomes active when all agents are healthy, where the group coordination is defined by homogeneous transformation coordination functions. By classifying agents as leaders and followers, a desired n-D homogeneous transformation is uniquely related to the desired trajectories of n+1 leaders and acquired by the remaining followers in real-time through local communication. The paper offers a novel approach for leader selection as well as naturally establishing and reestablishing inter-agent communication whenever the agent team enters the HDM. CEM is activated when at least one agent fails to admit group coordination. This paper applies unique features of decentralized homogeneous transformation coordination to quickly detect each arising anomalous situation and excludes failed agent(s) from group coordination of healthy agents. In CEM, agent coordination is treated as an ideal fluid flow where the desired agents' paths are defined along stream lines inspired by fluid flow field theory to circumvent exclusion spaces surrounding failed agent(s).

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arXiv2019

Experimental Evaluation of Continuum Deformation with a Five Quadrotor Team

This paper experimentally evaluates continuum deformation cooperative control for the first time. Theoretical results are expanded to place a bounding triangle on the leader-follower system such that the team is contained despite nontrivial tracking error. Flight tests were conducted with custom quadrotors running a modified version of ArduPilot on a BeagleBone Blue in M-Air, an outdoor netted flight facility. Motion capture and an onboard inertial measurement unit were used for state estimation. Position error was characterized in single vehicle tests using quintic spline trajectories and different reference velocities. Five-quadrotor leader trajectories were generated, and followers executed the continuum deformation control law in-flight. Flight tests successfully demonstrated continuum deformation; future work in characterizing error propagation from leaders to followers is discussed.

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arXiv2019

Formal Specification of Continuum Deformation Coordination

Continuum deformation is a leader-follower multiagent cooperative control approach. Previous work showed a desired continuum deformation can be uniquely defined based on trajectories of d +1 leaders in a d-dimensional motion space and acquired by followers through local inter-agent communication. This paper formally specifies continuum deformation coordination in an obstacle-laden environment. Using linear temporal logic (LTL), continuum deformation liveness and safety requirements are defined. Safety is prescribed by providing conditions on (i) agent deviation bound, (ii) inter-agent collision avoidance, (iii) agent containment, (iv) motion space containment, and (v) obstacle collision avoidance. Liveness specifies a reachability condition on the desired final formation.

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arXiv2019

Interactive Physics-Inspired Traffic Congestion Management

This paper proposes a new physics-based approach to effectively control congestion in a network of interconnected roads (NOIR). The paper integrates mass flow conservation and diffusion-based dynamics to model traffic coordination in a NOIR. The mass conservation law is used to model the traffic density dynamics across the NOIR while the diffusion law is applied to include traffic speed and motion direction into planning. This paper offers an analogy between traffic coordination in a transportation system and heat flux in a thermal system to define a potential filed over the NOIR. The paper also develops an interactive light-based and boundary control to manage traffic congestion through optimizing the traffic signal operations and controlling traffic flows at the NOIR boundary nodes. More specifically, a model predictive boundary control optimizes the NOIR inflow traffic while a receding horizon optimizer assigns the optimal movement phases at the NOIR intersections. For simulation, the paper models traffic congestion in a heterogeneous NOIR with a large number of interior and boundary nodes where the proposed interactive control can successfully manage the congestion.

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arXiv2019

Physics-Based Freely Scalable Continuum Deformation for UAS Traffic Coordination

This paper develops a novel physics-inspired traffic coordination approach and applies it to Unmanned Aircraft System (UAS) traffic management. We extend available physics-inspired approaches previously applied to 1-D traffic flow on highways and urban streets to support models of traffic coordination in higher dimension airspace for cases where no predefined paths exist. The paper considers airspace as a finite control volume while UAS coordination, treated as continuum deformation, is controlled at the airspace boundaries. By partitioning airspace into planned and unplanned spaces, the paper models nominal coordination in the planned airspace as the solution of a partial differential equation with spatiotemporal parameters. This paper also improves resilience to vehicle failures with a resilient boundary control algorithm to update the geometry of the planned space when UAS problems threaten safe coordination in existing navigable airspace channels. To support UAS coordination at the microscopic level, we propose clustering vehicles based on vehicle performance limits. UAS clusters, with each UAS treated as a particle of a virtual rigid body, use leader-follower containment to acquire the macroscopic desired trajectory.

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arXiv2018

Multi-UAV Continuum Deformation Flight Optimization in Cluttered Urban Environments

This paper studies collective motion optimization of a fleet of UAVs flying over a populated and geometrically constrained area. The paper treats UAVs as particles of a deformable body, thus, UAV coordination is defined by a homeomorphic continuum deformation function. Under continuum deformation, the distance between individual UAVs can significantly change while assuring the UAVs dont collide, enabling a swarm to travel through the potentially cluttered environment. To ensure inter-agent and obstacle collision avoidance, the paper formulates safety requirements as inequality constraints of the coordination optimization problem. The main objective of the paper is then to optimize continuum deformation of the UAV team satisfying all continuum deformation inequality constraints. Given initial and target configurations, the cost is defined as a weighted sum of the travel distance and distributed cost proportional to the likelihood of the human presence

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arXiv2018

A Data-Driven Approach for Autonomous Motion Planning and Control in Off-Road Driving Scenarios

This paper presents a novel data-driven approach to vehicle motion planning and control in off-road driving scenarios. For autonomous off-road driving, environmental conditions impact terrain traversability as a function of weather, surface composition, and slope. Geographical information system (GIS) and National Centers for Environmental Information datasets are processed to provide this information for interactive planning and control system elements. A top-level global route planner (GRP) defines optimal waypoints using dynamic programming (DP). A local path planner (LPP) computes a desired trajectory between waypoints such that infeasible control states and collisions with obstacles are avoided. The LPP also updates the GRP with real-time sensing and control data. A low-level feedback controller applies feedback linearization to asymptotically track the specified LPP trajectory. Autonomous driving simulation results are presented for traversal of terrains in Oregon and Indiana case studies.

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arXiv2017

Continuum Deformation of a Multiple Quadcopter Payload Delivery Team without Inter-Agent Communication

This paper proposes continuum deformation as a strategy for controlling the collective motion of a multiple quadcopter system (MQS) carrying a common payload. Continuum deformation allows expansion and contraction of inter-agent distances in a 2D motion plane to follow desired motions of three team leaders. The remaining quadcopter followers establish the desired continuum deformation only by knowing leaders positions at desired sample time waypoints without the need for inter-agent communication over the intermediate intervals. Each quadcopter applies a linear-quadratic-Gaussian (LQG) controller to track the desired trajectory given by the continuum deformation in the presence of disturbance and measurement noise. Results of simulated cooperative aerial payload transport in the presence of uncertainty illustrate the application of continuum deformation for coordinated transport through a narrow channel.

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