An Artificial Intelligence-Based Vehicular System Simulator

2017 ◽  
Vol 9 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Marvin T. Chan ◽  
Jonathan T. Chan ◽  
Christine Chan ◽  
Craig Gelowitz
Keyword(s):  
Artificial Intelligence ◽  
Three Dimensional ◽  
Driving Behavior ◽  
Simulation System ◽  
Cognitive Computing ◽  
Game Engine ◽  
Current Version ◽  
Design And Implementation ◽  
Human Player ◽  
Road System

This paper presents a vehicular system simulator, which enables the human player to race a car against three system-controlled cars in a three-dimensional road system. The objective of the vehicular system simulator is not to support defeating the opponent in a car race, but to provide the player with a challenging and enjoyable racing experience. Therefore, it is important that the system simulates human driving behavior and adopts cognitive computing. The paper discusses development of the vehicular system simulator using the artificial intelligence (AI) techniques that are supported in the game engine of Unity. The design and implementation of the vehicular system simulator are presented. The discussion includes some possible extensions of the current version of the system so that it can be adapted to be a simulation system for education purposes

An Artificial Intelligence-Based Vehicular System Simulator

2020 ◽  
pp. 708-721
Author(s):  
Marvin T. Chan ◽  
Jonathan T. Chan ◽  
Christine Chan ◽  
Craig Gelowitz
Keyword(s):  
Artificial Intelligence ◽  
Three Dimensional ◽  
Driving Behavior ◽  
Simulation System ◽  
Cognitive Computing ◽  
Game Engine ◽  
Current Version ◽  
Design And Implementation ◽  
Human Player ◽  
Road System

This paper presents a vehicular system simulator, which enables the human player to race a car against three system-controlled cars in a three-dimensional road system. The objective of the vehicular system simulator is not to support defeating the opponent in a car race, but to provide the player with a challenging and enjoyable racing experience. Therefore, it is important that the system simulates human driving behavior and adopts cognitive computing. The paper discusses development of the vehicular system simulator using the artificial intelligence (AI) techniques that are supported in the game engine of Unity. The design and implementation of the vehicular system simulator are presented. The discussion includes some possible extensions of the current version of the system so that it can be adapted to be a simulation system for education purposes

scholarly journals Development of a Car Racing Simulator Game Using Artificial Intelligence Techniques

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Marvin T. Chan ◽  
Christine W. Chan ◽  
Craig Gelowitz
Keyword(s):  
Artificial Intelligence ◽  
Video Games ◽  
Three Dimensional ◽  
Search Techniques ◽  
Artificial Intelligence Techniques ◽  
Car Racing ◽  
History Of ◽  
Human Player

This paper presents a car racing simulator game calledRacer, in which the human player races a car against three game-controlled cars in a three-dimensional environment. The objective of the game is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. To ensure that this objective can be accomplished, the game incorporates artificial intelligence (AI) techniques, which enable the cars to be controlled in a manner that mimics natural driving. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the AI techniques that were implemented in the development ofRacer.A comparison of the AI techniques implemented in the Unity platform with traditional AI search techniques is also included in the discussion.

scholarly journals Virtual Loom: a tool for the interactive 3D representation of historical fabrics

2021 ◽  
Author(s):  
Cristina Portalés ◽  
Manolo Pérez ◽  
Pablo Casanova-Salas ◽  
Jesús Gimeno
Keyword(s):  
Art History ◽  
3D Modelling ◽  
Current Version ◽  
Close Collaboration ◽  
Design And Implementation ◽  
Different Types ◽  
Interactive 3D ◽  
Silk Fabrics ◽  
Definition Of ◽  
3D Representations

Abstract3D modelling of man-made objects is widely used in the cultural heritage sector, among others. It is relevant for its documentation, dissemination and preservation. Related to historical fabrics, weaves and weaving techniques are still mostly represented in forms of 2D graphics and textual descriptions. However, complex geometries are difficult to represent in such forms, hindering the way this legacy is transmitted to new generations. In this paper, we present the design and implementation of SILKNOW’s Virtual Loom, an interactive tool aimed to document, preserve and represent in interactive 3D forms historical weaves and weaving techniques of silk fabrics, dating from the 15th to the 19th centuries. To that end, our tool only requires an image of a historical fabric. Departing from this image, the tool automatically subtracts the design, and allows the user to apply different weaves and weaving techniques. In its current version, the tool embeds five traditional weaving techniques, 39 weaves and six types of yarns, which have been defined thanks to close collaboration of experts in computer graphics, art history and historical fabrics. Additionally, users can change the color of yarns and produce different 3D representations for a given fabric, which are interactive in real time. In this paper, we bring the details of the design and implementation of this tool, focusing on the input data, the strategy to process images, the 3D modelling of yarns, the definition of weaves and weaving techniques and the graphical user interface. In the results section, we show some examples of image analysis in order to subtract the design of historical fabrics, and then we provide 3D representations for all the considered weaving techniques, combining different types of yarns.

scholarly journals Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2338
Author(s):  
Sofia Agostinelli ◽  
Fabrizio Cumo ◽  
Giambattista Guidi ◽  
Claudio Tomazzoli
Keyword(s):  
Artificial Intelligence ◽  
Renewable Energy ◽  
Energy Management ◽  
Three Dimensional ◽  
Cost Effective ◽  
Automation System ◽  
Climate Conditions ◽  
Digital Twin ◽  
Building Energy Management ◽  
Computing Paradigm

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

Optimization of the Navy’s three-dimensional mine impact burial prediction simulation model, Impact35, using high-order numerical methods

2021 ◽  
pp. 154851292110286
Author(s):  
Athanasios Donas ◽  
Ioannis Famelis ◽  
Peter C Chu ◽  
George Galanis
Keyword(s):  
Numerical Analysis ◽  
Numerical Methods ◽  
Prediction Model ◽  
Simulation Model ◽  
Three Dimensional ◽  
Simulation System ◽  
High Order ◽  
Alternative Methodology ◽  
Runge Kutta ◽  
Fifth Order

The aim of this paper is to present an application of high-order numerical analysis methods to a simulation system that models the movement of a cylindrical-shaped object (mine, projectile, etc.) in a marine environment and in general in fluids with important applications in Naval operations. More specifically, an alternative methodology is proposed for the dynamics of the Navy’s three-dimensional mine impact burial prediction model, Impact35/vortex, based on the Dormand–Prince Runge–Kutta fifth-order and the singly diagonally implicit Runge–Kutta fifth-order methods. The main aim is to improve the time efficiency of the system, while keeping the deviation levels of the final results, derived from the standard and the proposed methodology, low.

Research on the university intelligent learning analysis system based on AI

2021 ◽  
pp. 1-10
Author(s):  
Meng Huang ◽  
Shuai Liu ◽  
Yahao Zhang ◽  
Kewei Cui ◽  
Yana Wen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Academic Performance ◽  
Clustering Algorithm ◽  
Back Propagation ◽  
Three Dimensional ◽  
Training Model ◽  
Future Trend ◽  
Artificial Intelligence Technology ◽  
Visualization Technology

The integration of Artificial Intelligence technology and school education had become a future trend, and became an important driving force for the development of education. With the advent of the era of big data, although the relationship between students’ learning status data was closer to nonlinear relationship, combined with the application analysis of artificial intelligence technology, it could be found that students’ living habits were closely related to their academic performance. In this paper, through the investigation and analysis of the living habits and learning conditions of more than 2000 students in the past 10 grades in Information College of Institute of Disaster Prevention, we used the hierarchical clustering algorithm to classify the nearly 180000 records collected, and used the big data visualization technology of Echarts + iView + GIS and the JavaScript development method to dynamically display the students’ life track and learning information based on the map, then apply Three Dimensional ArcGIS for JS API technology showed the network infrastructure of the campus. Finally, a training model was established based on the historical learning achievements, life trajectory, graduates’ salary, school infrastructure and other information combined with the artificial intelligence Back Propagation neural network algorithm. Through the analysis of the training resulted, it was found that the students’ academic performance was related to the reasonable laboratory study time, dormitory stay time, physical exercise time and social entertainment time. Finally, the system could intelligently predict students’ academic performance and give reasonable suggestions according to the established prediction model. The realization of this project could provide technical support for university educators.

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