Department Of Automotive Software

• 1-1,2

  CurriculumThis table demonstrates the curriculum accroding to academic year.

  1- 1	SEMINAR FOR ACADEMIC LIFE 1. Summary of the course This course is to assist university freshmen in CRM designing to adapt university life well through the instruction and counselling of supervising professor. (This course is composed of self analysis, personality type test, career research, instruction for the success of university life, career plan and direction setting, CRM designing method and CRM designing. The course should be teaching in classes of the students by supervising professor.) 2. Course objectives This course is to motivate the students before the mid term exam and provide students with self analysis, personality type test (MBTI or TCI) and career research (YAT test). Also, this course shall has a plan to instruct the students to enhance the efficiency of university life through career and time management. In addition, this course is to make a chance for the students to have practical assistance to university life by providing study method, report designing strategy and the information on academic system and various kinds of internal programs of the university. After the mid term exam, the students will be instructed to set the direction of career designing through continuous counselling of supervising professor and the students will be able to establish CRM designing and execution plan.
  1- 1,2	SOCIAL CONTRIBUTION AND SERVICE This course is to cultivate community sense as members of society and the global village for students in order to develop the basic knowledge required as global citizens. Especially, this course is to foster the spirit of cooperation, sharing, service, and creativity and study the social contribution and leadership to solving the challenges the global community faces. As a liberal arts course, it is centered to nurture a leader having the global capability to contribute to community development through learning the knowledge and the case on the value & logic of social responsibility focused on environmental preservation, social contribution, and good governance(ESG). This course aims to foster a generous mind, learn knowledge and technology and build the capacity to contribute to building a society towards a safer and happier world through the study of theory and practice.
  1- 1,2	SOFTWARE AND AI Software and AI (Artificial Intelligence) course aims to educate the basic concepts of software and computational thinking to use them in various applications. It allows students of various majors to experience the core technologies of the 4th industrial revolution, such as big data, machine learning, and AI. It also introduces various applications of AI so that students can easily apply these technologies to their field of study. This course classifies the lecture types into three categories, and adjust the lecture difficulty according to the student's academic ability.

• 2-1,2

  CurriculumThis table demonstrates the curriculum accroding to academic year.

  2- 1	UNDERSTANDING OPEN SOURCE SOFTWARE This class aims to provide students with knowledge and experience in open source software in order to foster a software human resource for the success of the Fourth Industrial Revolution. To accomplish this, the class provides lectures on various open source software, libraries, and configuration management tools that are mainly used for software development in the real-world projects. Through this course, students will be able to understand the software development environment for open source software, and ultimately achieve better open source software development skills.
  2- 1	DIGITAL LOGIC DESIGN In this course, students analyze logic circuits, which are the foundation of digital circuits, and acquire foundational knowledge for constructing digital systems. As detailed topics, they study the basic components that make up combinational and sequential logic circuits, and based on this, learn the design and analysis of digital logic circuits. Students also learn how to design digital logic circuits using HDL (Hardware Description Language).
  2- 1	ENGINEERING MATHEMATICS I - Laplace transform - Vectors - Matrices - Vector calculus - Orthogonal functions and Fourier series - Boundary-value problems - Integral transform method - Functions of a complex variable - Series and residues
  2- 1	PROGRAMMING LANGUAGES This course covers the C programming language, which is utilized in various fields of system programming. In order to acquire systematic programming techniques, the first half of the lecture will focus on the foundational knowledge of structural programming in C, including variables and operations, functions, program control flow (conditional statements, loops), arrays, structures, pointers, and dynamic arrays. In the second half of the lecture, the course will cover data structures based on C, such as array-based priority queues, self-referential structure-based linked lists, and binary search trees.
  2- 2	MCU PROGRAMMING Learn embedded programming theory and various commands based on microcontrollers and conduct various practical exercises using the Arduino board.
  2- 2	AUTOMOTIVE MECHATRONICS This course introduces the case of an automobile system that combines the mechanical, electrical and electronic, and computer engineering. Students learn about mechatronics through simple application examples. We start with the theoretical background and learn about mathematical interpretation, schematic numerical problems, and computer interpretation, etc., which can be directly applied in the industry.
  2- 2	COMPUTER ARCHITECTURES In this course, you will learn about the functions of the major components that make up a computer system and their interactions, and learn about various design techniques used to implement a computer system in a computer architecture view. Major topics include instruction sets, central processing units, pipelining, memory hierarchy, input/output devices, and multiprocessors. You will also learn about the historical review of computer system development and basic knowledge necessary for analyzing the performance of computer systems and the lecture also provides an understanding of the latest technologies from a computer architecture perspective.
  2- 2	OBJECT-ORIENTED PROGRAMMING LANGUAGE This course covers the C++ programming language, which is widely used in large-scale system programming. In the first half of the course, students will learn the basic concepts of object-oriented programming, including classes, data members and member functions, instances, inheritance, and polymorphism. The course also covers templates and the Standard Template Library (STL), which are used to build generalized data structures and algorithms, as well as priority queues. In the second half of the course, students will learn how to implement fundamental data structures and algorithms based on C++. Topics include C++-based linked lists, binary search trees, hash maps, and graph data structures and algorithms.
  2- 2	SIGNAL AND SYSTEM This course covers the fundamental concepts of analog and digital signals and the systems that process them. In the time domain, signal and system behavior is analyzed using differential and difference equations, while in the frequency domain, frequency response is interpreted using the Laplace transform and the z-transform. Key topics include filter design, system performance evaluation, and practical applications of signal processing techniques. Through this course, students will acquire foundational knowledge necessary to solve various engineering problems. The course provides a basis for signal processing, applicable in fields such as communications, control, and computer systems.

• 3-1,2

  CurriculumThis table demonstrates the curriculum accroding to academic year.

  3- 1	AUTOMOTIVE OS This course deals with the important algorithms and theories of operating systems with the view point of the operating systems architecture. Major topics include process management, memory management, peripheral devices management, networking, and security. In addition, in this subject, we learn about automotive operating systems in addition to general operating system contents.
  3- 1	DATA COMMUNICATIONS The Data Communications course focuses on understanding the fundamental concepts and principles of computer networks and communication systems. The course covers how data is converted into digital form, transmitted over various networks, and restored to its original information at the destination. It also explores various protocols and algorithms designed to ensure the efficiency and reliability of data transmission. Key topics include data encoding, transmission media, signal processing, network architecture, protocol layer models, error detection and correction techniques, flow control, and overall network performance analysis.
  3- 1	MACHINE LEARNING Machine Learning (ML) is a field of artificial intelligence that involves training models using data to make predictions or decisions. This course covers the formats and processing methods of data for machine learning, as well as model selection and training techniques. Additionally, it explores representative ML models such as linear regression, polynomial regression, Support Vector Machines (SVM), decision trees, and Artificial Neural Networks (ANN). This course serves as a foundation for acquiring advanced artificial intelligence technologies, including deep learning, and aims to develop the ability to solve various engineering problems using machine learning.
  3- 1	DATA STRUCTURES AND DICTIONARY OF ALGORITHMS Data structures and algorithms are the two most important elements that make up a computer program. This course explores the characteristics and implementation methods of key data structures such as stack, queue, list, tree, map, and graph. Additionally, we will study well-known problems in computer science and the algorithms to solve them, categorized into Divide-and-conquer, greedy method, dynamic programming, etc. We also discuss how the choice of data structure impacts the performance of these algorithms.
  3- 1	FUNCTIONAL SAFETY SOFTWARE This course is a specialized study in functional safety in the automotive field to improve professional knowledge related to standard requirements (ISO26262) and practical applications related to vehicle electrical and electronic systems. Introduces the processes required for the safety life cycle, adopts a situation-based approach to the roles and outcomes of safety analysis and support processes, and covers the description of work products and appropriate handling of safety plans.
  3- 2	AUTOMOTIVE SENSOR Students are encouraged to understand the various sensor systems used in advanced driver assistance and autonomous vehicles. It covers the operating principles, functions, and methods of use of digital camera sensor, lidar sensor, and radar sensor required for major subjects such as deep learning, automotive computer vision, and autonomous driving.
  3- 2	AUTOMOTIVE SOFTWARE ENGINEERING This course introduces fundamental topics related to software engineering paradigms such as the V-Cycle for automotive software development and testing techniques, project management, and the analysis, design, implementation, and maintenance of software requirements. It focuses on automotive standards-compliant in-vehicle software concepts and development methods, with an emphasis on software development methodologies that prioritize safety.
  3- 2	DEEP LEARNING This course covers the basic knowledge of artificial intelligence including deep learning. Students study the principle of neural network, the learning principle of deep learning, and various models for deep learning. To this end, the principles of various deep learning models such as CNN, RNN, LSTM, Attention Mechanism, and Sequence-to-Sequence will be covered. In addition, this course introduces the latest advanced deep learning algorithms and analyzes various cases solved by applying deep learning in real life.
  3- 2	AUTOSAR This course studies the AUTOSAR development environment and development methods based on AUTOSAR (Automotive Open System Architecture), a standardization plan established by major automobile manufacturers (OEMs) and developers.
  3- 2	EMBEDDED SYSTEM Learn various programming techniques based on embedded systems. Also, configure various Linux-based systems, build a cross-compilation environment using Raspberry Pi, and build the Linux kernel. Practice system calls and module programming, and design and implement Raspberry Pi GPIO device drivers.
  3- 2	VEHICULAR NETWORK To enhance both the safety and convenience of vehicles, it is essential to efficiently share information among various electronic control devices. In this course, students study prominent vehicle internal communication systems such as CAN (Controller Area Network), LIN (Local Interconnect Network), and Ethernet. They will learn about the characteristics of information exchanged between electronic control devices through vehicular networks.

• 4-1,2

  CurriculumThis table demonstrates the curriculum accroding to academic year.

  4- 1	AUTOMOTIVE COMPUTER VISION As an application field of digital signal processing, we learn various signal processing techniques for 2D images and 3D point cloud signals captured with camera sensors and lidar sensors. In this course, you first learn the operating principles of digital camera sensors and LiDAR sensors, and then cover various signal processing and computer vision theories necessary for object recognition from two-dimensional images captured by cameras.
  4- 1	SECURITY BASICS In this course, students learn and practice Matlab/Simulink S/W, which is widely used for vehicle control simulation, including the basic vehicle dynamics theory and vehicle modeling required for autonomous driving control system design. In addition, by performing a project to develop an autonomous driving system using CarMaker S/W, students will establish the foundation for becoming an autonomous vehicle engineer in the future.
  4- 1	SOFTWARE DEVELOPMENT WITH MODEL-BASED DESIGN Model-based development (MBD) is a software development methodology that enables faster, more cost-effective development of dynamic systems such as control systems, signal processing, and communication systems, leveraging graphical modeling rather than traditional text-based programming. In this course, we learn how to apply the MBD methodology to reduce development costs and accelerate the release time of embedded software products.
  4- 1	V2X V2X (Vehicle-to-Everything) refers to communication between vehicles and their surrounding environment, which is a critical technology for autonomous driving, smart cities, and traffic management systems. This course, as an application area within automotive software engineering, covers the various technologies and protocols that enable vehicles to interact with road infrastructure, other vehicles, pedestrians, and networks. Students will explore the fundamental concepts and principles of V2X communication and study the various services and application scenarios that are realized through this technology. The course will delve into the differences and specific characteristics of V2X communication technologies such as DSRC (Dedicated Short-Range Communications) and C-V2X (Cellular Vehicle-to-Everything).
  4- 2	AUTOMOTIVE SW INDUSTRY-ACADEMIC PROJECT In this course, you will learn the latest technologies required by the automobile industry and academia, identify problems required by the industry, and perform joint projects with industry experts to solve those problems.
  4- 2	AUTONOMOUS DRIVING This subject acquires knowledge about the autonomous driving system that integrates GPS and vision systems, including the overall contents of self-driving cars such as navigation/environmental recognition/control/data processing methods.
  4- 2	FUTURE VEHICLE PERFORMANCE ANALYSIS This course deals with the analysis of automobile performance through the analysis of the structure of future automobiles and the characteristics of each major part. Through this, it is possible to develop problem definition and anaysis procedures such as acceleration performance, braking performance, cornering performance, ride comfort and stability, and electronic control performance of future automobiles. In addition, it is possible to secure full-car performance analysis and analysis capabilities through mathematical modeling and simulation of future automobiles (including electric and autonomous vehicle performances)
  4- 2	VEHICLE SECURITY In this course, main issues regarding the vehicle security and vehicular network security will be discussed and the students will learn how these issues can be resolved. The main issues are as follows: - elementary theory on security - vehicular network security - in-vehicle network security