scholarly journals Path and Control Planning for Autonomous Vehicles in Restricted Space and Low Speed

2020 ◽  
Author(s):  
Maksym Diachuk ◽  
Said Easa ◽  
Joel Bannis
Keyword(s):  
Autonomous Vehicles ◽  
Optimal Solution ◽  
Control Laws ◽  
Low Speed ◽  
Output State ◽  
Original Algorithm ◽  
Nonlinear Motion ◽  
Space Of Constant Curvature ◽  
Kinematic Models ◽  
And Control

The paper presents models of path and control planning for parking, docking, and movement of autonomous vehicles at low speeds considering space constraints. Given the low speed of motion, and in order to test and approve the proposed algorithms, vehicle kinematic models are used. Recent works on the development of parking algorithms for autonomous vehicles are reviewed. Bicycle kinematic models for vehicle motion are considered for three basic types of vehicles: passenger car, long wheelbase truck, and articulated vehicles with and without steered semitrailer axes. Mathematical descriptions of systems of differential equations in matrix form and expressions for determining the linearization elements of nonlinear motion equations that increase the speed of finding the optimal solution are presented. Options are proposed for describing the interaction of vehicle overall dimensions with the space boundaries, within which a maneuver should be performed. An original algorithm that considers numerous constraints is developed for determining vehicle permissible positions within the closed boundaries of the parking area, which are directly used in the iterative process of searching for the optimal plan solution using nonlinear model predictive control (NMPC). The process of using NMPC to find the best trajectories and control laws while moving in a semi-limited space of constant curvature (turnabouts, roundabouts) are described. Simulation tests were used to validate the proposed models for both constrained and unconstrained conditions and the output (state-space) and control parameters' dependencies are shown. The proposed models represent an initial effort to model the movement of autonomous vehicles for parking and has the potential for other highway applications.

scholarly journals Path and Control Planning for Autonomous Vehicles in Restricted Space and Low Speed

2020 ◽  
Vol 5 (5) ◽  
pp. 42 ◽  
Author(s):  
Maksym Diachuk ◽  
Said M. Easa ◽  
Joel Bannis
Keyword(s):  
Autonomous Vehicles ◽  
Optimal Solution ◽  
Control Laws ◽  
Low Speed ◽  
Output State ◽  
Original Algorithm ◽  
Nonlinear Motion ◽  
Space Of Constant Curvature ◽  
Kinematic Models ◽  
And Control

This paper presents models of path and control planning for the parking, docking, and movement of autonomous vehicles at low speeds, considering space constraints. Given the low speed of motion, and in order to test and approve the proposed algorithms, vehicle kinematic models are used. Recent works on the development of parking algorithms for autonomous vehicles are reviewed. Bicycle kinematic models for vehicle motion are considered for three basic types of vehicles: passenger car, long wheelbase truck, and articulated vehicles with and without steered semitrailer axes. Mathematical descriptions of systems of differential equations in matrix form and expressions for determining the linearization elements of nonlinear motion equations that increase the speed of finding the optimal solution are presented. Options are proposed for describing the interaction of vehicle overall dimensions with the space boundaries, within which a maneuver should be performed. An original algorithm that considers numerous constraints is developed for determining vehicle permissible positions within the closed boundaries of the parking area, which are directly used in the iterative process of searching for the optimal plan solution using nonlinear model predictive control (NMPC). The process of using NMPC to find the best trajectories and control laws while moving in a semi-limited space of constant curvature (turnabouts, roundabouts) are described. Simulation tests were used to validate the proposed models for both constrained and unconstrained conditions and the output (state-space) and control parameters’ dependencies are shown. The proposed models represent an initial effort to model the movement of autonomous vehicles for parking and have the potential for other highway applications.

Development and Testing of an Autonomous Driving Module for Critical Driving Conditions

2008 ◽  
Author(s):  
Francesco Biral ◽  
Enrico Bertolazzi ◽  
Daniele Bortoluzzi ◽  
Paolo Bosetti
Keyword(s):  
Autonomous Vehicles ◽  
Gasoline Engine ◽  
Autonomous Driving ◽  
Great Effort ◽  
Control Laws ◽  
Test Platform ◽  
High Level ◽  
And Control ◽  
Nonlinear Receding Horizon Control ◽  
High Range

In the last years a great effort has been devoted to the development of autonomous vehicles able to drive in a high range of speeds in semi-structured and unstructured environments. This article presents and discusses the software framework for Hardware-In-the-Loop (HIL) and Software-In-the-Loop (SIL) analysis that has been designed for developing and testing of control laws and mission functionalities of semi-autonomous and autonomous vehicles. The ultimate goal of this project is to develop a robotic system, named RUMBy, able to autonomously plan and execute accurate optimal manoeuvres both in normal and in critical driving situations and to be used as a test platform for advanced decision and autonomous driving algorithms. RUMBy’s hardware is a 1:6 scale gasoline engine R/C car with onboard telemetry and control systems. RUMBy’s software consists of three main modules: the manager module that coordinates the other modules and take high level decision; the motion planner module which is based on a Nonlinear Receding Horizon Control (NRHC) algorithm; the actuation module that produces the driving command for the vehicle. The article describes the details of RUMBy architecture and discusses its modular configuration that easily allows HIL and SIL tests.

Loss of stability of guidance and control laws for autonomous vehicles

1993 ◽  
Vol 8 (2) ◽  
pp. 101-125
Author(s):  
Fotis A. Papoulias
Keyword(s):  
Autonomous Vehicles ◽  
Loss Of Stability ◽  
Control Laws ◽  
Guidance And Control ◽  
And Control

Speed Planning and Control of Low-Speed Autonomous Vehicles at Intersections

2019 ◽  
Vol 2019 (0) ◽  
pp. 2A1-E01
Author(s):  
Hidetoshi TAKEMURA ◽  
Pongsathorn RAKSINCHAROENSAK
Keyword(s):  
Autonomous Vehicles ◽  
Low Speed ◽  
Planning And Control ◽  
And Control

Motion Control of Electric Propulsion Spacecraft Transfers between the Libration Points L1 and L2 of the Earth–Moon System

2019 ◽  
pp. 66-74
Author(s):  
M.K. Fain ◽  
O.L. Starinova
Keyword(s):  
Electric Propulsion ◽  
Optimal Solution ◽  
Libration Points ◽  
Coordinate Frame ◽  
Control Laws ◽  
Moon System ◽  
The Earth ◽  
Nonlinear Motion ◽  
Sequential Linearization ◽  
L1 And L2

This article presents a study of nonlinear motion of an electric propulsion spacecraft. Spacecraft transfers between the libration points L1 and L2 of the Earth-Moon system are analyzed. The influence of the shaded areas and gravitational effects of the Earth, the Moon and the Sun is taken into account. The mathematical model of the transfers is described within the barycentric coordinate frame. The exact optimal solution of the problem is obtained using Pontryagin’s maximum principle formalism and the numerical solution of the boundary value problem. The method of optimizing the parameters and controls of interplanetary trajectories of the spacecraft based on the optimization of dynamic system components and on Fedorenko’s method of sequential linearization is applied in this study. This method allows limitations on composite functions with Fréchet derivatives. As the results of the simulation, the control laws and corresponding trajectories are obtained.

Autonomous Vehicles in the Mobility System

2020 ◽  
pp. 500-514
Author(s):  
Thilo von Pape
Keyword(s):  
Artificial Intelligence ◽  
Mobile Phones ◽  
Mobile Communication ◽  
Autonomous Vehicles ◽  
Communication Research ◽  
Collective Control ◽  
System P ◽  
Mobility System ◽  
And Control ◽  
Transportation Technologies

This chapter discusses how autonomous vehicles (AVs) may interact with our evolving mobility system and what they mean for mobile communication research. It juxtaposes a conceptualization of AVs as manifestations of automation and artificial intelligence with an analysis of our mobility system as a historically grown hybrid of communication and transportation technologies. Since the emergence of railroad and telegraph, this system has evolved on two layers: an underlying infrastructure to power and coordinate the movements of objects, people, and ideas in industrially scaled speeds, volumes, and complexity and an interface to seamlessly access this infrastructure and control it. AVs are poised to further enhance the seamlessness which mobile phones and cars already lent to mobility. But in assuming increasingly sophisticated control tasks, AVs also disrupt an established shift toward individual control, demanding new interfaces to enable higher levels of individual and collective control over the mobility infrastructure.

AVDM: A hierarchical command-and-control system architecture for cooperative autonomous vehicles in highways scenario using microscopic simulations

2021 ◽  
Vol 35 (1) ◽  
Author(s):  
Thomas Braud ◽  
Jordan Ivanchev ◽  
Corvin Deboeser ◽  
Alois Knoll ◽  
David Eckhoff ◽  
...  
Keyword(s):  
Control System ◽  
System Architecture ◽  
Autonomous Vehicles ◽  
Command And Control ◽  
And Control ◽  
Control System Architecture ◽  
Command And Control System
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