Hierarchical Hybrid Predictive Control of an Autonomous Road Vehicle

2015 ◽  
Author(s):  
Qian Wang ◽  
Thomas Weiskircher ◽  
Beshah Ayalew
Keyword(s):  
Decision Making ◽  
Predictive Control ◽  
Particle Motion ◽  
Vehicle Dynamics ◽  
Finite State Machine ◽  
Road Vehicle ◽  
Reduced Order ◽  
Control Framework ◽  
Finite State ◽  
Trajectory Guidance

This paper presents a hierarchical hybrid predictive control framework for an autonomously controlled road vehicle. At the top, an assigner module is designed as a finite state machine for decision-making. Based on the current information of the controlled vehicle and its environment (obstacles, and lane markings, etc), the assigner selects discrete maneuver states through pre-defined switching rules. The several maneuver states are related to different setups for the underlying model predictive trajectory guidance module. The guidance module uses a reduced-order curvilinear particle motion description of the controlled vehicle and obstacle objects as well as a corresponding description of the reference path, lane and traffic limits. The output of the guidance module interfaces with the lower level controller of the continuous vehicle dynamics. The performance of the proposed framework is demonstrated via simulations of highway-driving scenarios.

scholarly journals A VLSI implementation of elevator control based on finite state machine using Verilog HDL

2018 ◽  
Vol 7 (2.8) ◽  
pp. 92
Author(s):  
Naresh Lagadapati ◽  
Manoj Karri ◽  
Tejaswini Vaddineni ◽  
Sk Mahaboob Subhani ◽  
K Hari Kishore
Keyword(s):  
Finite State Machine ◽  
Control Variable ◽  
Vlsi Implementation ◽  
Verilog Hdl ◽  
Control Module ◽  
Control Framework ◽  
Finite State ◽  
Control Procedures ◽  
High Utilization ◽  
Lift Control

In this cutting edge period, lifts have turned into a basic piece of any business or open complex. It encourages the quicker development of individuals and gear between floors. The lift control framework is a standout amongst the most critical perspectives in hardware control module that are utilized as a part of car application. Normally lifts are intended for a particular building considering the fundamental factors, for example, the tallness of the building, the quantity of individuals venturing out to each floor and the normal times of high utilization. The lift framework is composed with various control procedures. This usage depends on FPGA, which can be utilized for a working with any number of floors, with the predetermined sources of info and yields. This controller can be executed for a lift with the required number of floors by just changing a control variable in the HDL code. This approach depends on a calculation which decreases the measure of calculation required, by concentrating just on the pertinent guidelines that enhances the execution of the gathering of lift framework.

scholarly journals Adaptive Cruise Control for Cut-In Scenarios Based on Model Predictive Control Algorithm

2021 ◽  
Vol 11 (11) ◽  
pp. 5293
Author(s):  
Chongpu Chen ◽  
Jianhua Guo ◽  
Chong Guo ◽  
Chaoyi Chen ◽  
Yao Zhang ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Finite State Machine ◽  
Adaptive Cruise Control ◽  
State Machine ◽  
Driving Safety ◽  
Cruise Control ◽  
Finite State ◽  
Distance Model ◽  
Model Predictive Control Algorithm

In a cut-in scenario, traditional adaptive cruise control usually cannot effectively identify the cut-in vehicle and respond to it in advance. This paper proposes an adaptive cruise control (ACC) strategy based on the MPC algorithm for cut-in scenarios. A finite state machine (FSM) is designed to manage vehicle control in different cut-in scenarios. For a cut-in scenario, a method to identify and quantify the possibility of cut-in of a vehicle is proposed. At the same time, a safety distance model of the cut-in vehicle is established as the basis for the state transition of the finite state machine. Taking the quantified cut-in possibility of a vehicle as a reference, the model predictive control (MPC) algorithm, which considers the constraints of driving safety and comfort, is used to realize coordinated control of the host vehicle and the cut-in vehicle. Simulink–Carsim simulation studies show that the ACC strategy for a cut-in scenario can effectively identify a cut-in vehicle and quantify the possibility of cut-in of the vehicle. Faced with a cut-in vehicle, the host vehicle using the ACC strategy can brake several seconds early and switch the following target to the cut-in vehicle. Meanwhile, the acceleration and jerk of the host vehicle changes within a reasonable range, which ensures driving safety and comfort.

Behavior Trees for Computer Games

2017 ◽  
Vol 26 (02) ◽  
pp. 1730001 ◽  
Author(s):  
Yoones A. Sekhavat
Keyword(s):  
Decision Making ◽  
Computer Games ◽  
Finite State Machine ◽  
State Machine ◽  
Gaming Industry ◽  
Behavior Tree ◽  
Behavior Trees ◽  
Finite State ◽  
And Control

Although a Finite State Machine (FSM) is easy to implement the behaviors of None-Player Characters (NPC) in computer games, it is difficult to maintain and control the behaviors with increasing the number of states. Alternatively, Behavior Tree (BT), which is a tree of hierarchical nodes to control the ow of decision making, is widely used in computer games to address the scalability issues. This paper reviews the structure and semantics of BTs in computer games. Different techniques to automatically learn and build BTs as well as strengths and weaknesses of these techniques are discussed. This paper provides a taxonomy of BT features and shows to what extent these features are taken into account in computer games. Finally, the paper shows how BTs are used in practice in the gaming industry.

MARKOV MATHEMATICAL MODEL OF DYNAMIC ADAPTIVE TESTING OF AN ACTIVE AGENT

2018 ◽  
pp. 29-35
Author(s):  
N. V. Brovka ◽  
P. P. Dyachuk ◽  
M. V. Noskov ◽  
I. P. Peregudova
Keyword(s):  
Mathematical Model ◽  
Finite State Machine ◽  
Active Agent ◽  
Adaptive Testing ◽  
State Machine ◽  
Learning Activities ◽  
Independent Learning ◽  
Complex Object ◽  
Total Reward ◽  
Finite State

The problem and the goal.The urgency of the problem of mathematical description of dynamic adaptive testing is due to the need to diagnose the cognitive abilities of students for independent learning activities. The goal of the article is to develop a Markov mathematical model of the interaction of an active agent (AA) with the Liquidator state machine, canceling incorrect actions, which will allow mathematically describe dynamic adaptive testing with an estimated feedback.The research methodologyconsists of an analysis of the results of research by domestic and foreign scientists on dynamic adaptive testing in education, namely: an activity approach that implements AA developmental problem-solving training; organizational and technological approach to managing the actions of AA in terms of evaluative feedback; Markow’s theory of cement and reinforcement learning.Results.On the basis of the theory of Markov processes, a Markov mathematical model of the interaction of an active agent with a finite state machine, canceling incorrect actions, was developed. This allows you to develop a model for diagnosing the procedural characteristics of students ‘learning activities, including: building axiograms of total reward for students’ actions; probability distribution of states of the solution of the problem of identifying elements of the structure of a complex object calculate the number of AA actions required to achieve the target state depending on the number of elements that need to be identified; construct a scatter plot of active agents by target states in space (R, k), where R is the total reward AA, k is the number of actions performed.Conclusion.Markov’s mathematical model of the interaction of an active agent with a finite state machine, canceling wrong actions allows you to design dynamic adaptive tests and diagnostics of changes in the procedural characteristics of educational activities. The results and conclusions allow to formulate the principles of dynamic adaptive testing based on the estimated feedback.

PENERAPAN FINITE STATE MACHINE UNTUK PENGENDALIAN ANIMASI PADA VIDEO GAME RPG NUSANTARA LEGACY

2018 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Mustofa Mustofa ◽  
Sidiq Sidiq ◽  
Eva Rahmawati
Keyword(s):  
Life Cycle ◽  
Video Game ◽  
Finite State Machine ◽  
Role Playing ◽  
State Machine ◽  
Game Development ◽  
Development Life Cycle ◽  
Finite State ◽  
Role Playing Game

Perkembangan dunia yang dinamis mendorong percepatan perkembangan teknologi dan informasi. Dengan dorongan tersebut komputer yang dulunya dibuat hanya untuk membantu pekerjaan manusia sekarang berkembang menjadi sarana hiburan, permainan, komunikasi dan lain sebagainya. Dalam sektor hiburan salah satu industri yang sedang menjadi pusat perhatian adalah industri video game. Begitu banyaknya produk video game asing yang masuk ke dalam negeri ini memberikan tantangan kepada bangsa ini. Tentunya video game asing yang masuk ke negara ini membawa banyak unsur kebudayaan negara lain. Ini semakin membuat kebudayaan nusantara semakin tergeserkan dengan serangan kebudayaan asing melalui berbagai media. Maka dari itu peneliti mencoba untuk menerapkan Finite State Machine dalam merancang sebuah video game RPG (Role-Playing game) yang memperkenalkan kebudayaan. Dalam perancangan video game ini peneliti menggunakan metode GDLC(Game Development Life Cycle) agar penelitian ini berjalan secara sistematis. Dalam suatu perancangan video game tedapat banyak elemen, pada penelitian ini penulis lebih fokus pada pengendalian animasi karakter yang dimainkan pada video game ini. Dari perancangan yang dilakukan, disimpulkan bahwa Finite State Machine dapat digunakan untuk pengendalian animasi yang baik pada video game RPG. Diharapkan video game ini dapat menjadi salah satu media untuk mengenalkan kebudayaan nusantara

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