COURSE INFO
VECTOR[3-0-0:3]
PREVIOUS CODEINTR 6000E
DESCRIPTIONThis course will introduce traffic control system concepts, components, algorithms, and tools for evaluating their effectiveness. With the instruction, assignments, and projects in this course, students are expected to learn about traffic system control devices, working principles, and popular algorithms. Additionally, the VISSIM traffic simulation package will be introduced in greater detail so that students can use it for evaluating the performance of traffic operation plans.

INTR 5130 - Traffic Control and Simulation (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6151) We 01:30PM - 04:20PMRm 222, W1ZHU, Meixin3011190 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONIntelligent Transportation Systems (ITS) apply a variety of technologies to monitor, evaluate, and manage transportation systems to enhance their efficiency, safety, and sustainability. This postgraduate-level course introduces the basic functional components in ITS and how they are designed and operated to manage multi-modal transportation systems., including both passenger and freight transportation systems and infrastructure. The course topics cover the following three main parts: (i) Emerging vehicle technologies and mobility services, data management, and institutional issues; (ii) Multi-modal freight operations and management in road, rail, maritime and inter-modal systems; (iii) Analytical methods including fundamentals of system analysis, risk and regression analysis, network flow optimization and algorithm design, etc.

INTR 5200 - Emerging Mobility and Multimodal Freight Systems (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6148) Th 09:00AM - 11:50AMRm 201, E3BAI, Yun
JIA, Shuai
SUN, Xiaotong		207130 
COURSE INFO
VECTOR[3-0-0:3]
EXCLUSIONIOTA 5003
CO-LIST WITHIOTA 5003
DESCRIPTIONThis course aims to develop students’ fundamental understanding of the application scenarios, challenges, and solutions of wireless connectivity in various systems involving autonomous things, and under possible mobility. Topics covered include fundamentals of digital communications, future wireless connectivity requirements, and various solutions to the unique challenges such as dynamic propagation environment, scalability, complexity, and heterogeneity.

INTR 5220 - Wireless Connectivity for Mobile Autonomous Things (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6149) Tu 09:00AM - 11:50AMTBAYAN, Jia
YANG, Liuqing		15960
The classroom is E1102.
 
COURSE INFO
VECTOR[3-0-0:3]
PREVIOUS CODEINTR 6000F
DESCRIPTIONThe course aims to help students master the basic concepts and research methods of Artificial Intelligence (AI) and machine learning, understand future development trends, and lay the foundation for further research in leveraging machine learning and AI in transportation research. Through the study of this course, students will understand and master the basic concepts, ideas and methods of AI and related machine learning techniques, and initially learn and master the ability to use those machine learning techniques to solve practical problems, especially in transportation context.

INTR 5250 - Artificial Intelligence in Transportation (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6150) Mo 09:00AM - 11:50AMRm 222, W1ZHENG, Xinhu3011190 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONThis course introduces methods for analysis and control design of nonlinear systems, which have a wide range of engineering applications including transportation, robotics, biology, energy, and manufacturing systems. The course includes: 1) Mathematical models of nonlinear systems, and fundamental differences between the behavior of linear and nonlinear systems, equilibrium, limit cycles and general invariant sets. 2) Phase plane analysis, Lyapunov stability, Input-to-state stability, Input-output stability, and approximation methods. 3) Feedback linearization and nonlinear control design tools, including Lyapunov-based control and Backstepping. From learning the nonlinear phenomena to understanding the mathematical properties and then analyzing system behaviors, students will be able to grasp the fundamental concepts and advanced tools that are useful in the analysis of nonlinear systems. The control design tools for nonlinear systems from feedback linearization to advanced backstepping control are covered in this course. Students will be proficient in skills of independently assessing the advantages and disadvantages of different nonlinear methods, make a qualified choice of method for analysis and design of nonlinear control systems that arise from various research areas.

INTR 5300 - Nonlinear Control Systems (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6152) Mo 01:30PM - 04:20PMRm 202, E1YU, Huan201370 
[DELI]
Mode of Delivery
COURSE INFO
ATTRIBUTES[BLD] Blended learning
VECTOR[3-0-0:3]
EXCLUSIONROAS 5900
CO-LIST WITHROAS 5900
PREVIOUS CODEINTR 5600
DESCRIPTIONThe course will cover a wide range of analytical methods used in human factors research domain. The students will gain an understanding of the procedures, objectives and limitations of different research methods. The course will also include four case studies so that students would gain first-hand experience in applying the methods in real projects. These contents are required for research investigating users’ behaviors.

INTR 5330 - Analytical Methods in Human Factors Research (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6147) We 09:00AM - 11:50AMRm 202, E1HE, Dengbo141220 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONThis course introduces students to concepts and data-driven methods for analyzing changes required in technologies and public policies across transportation and energy systems to enable global energy transition. Key topics covered in the class include: 1) Developing metrics and conceptual frameworks for evaluating and comparing technology performance 2) Modeling technology and policy mitigation pathways 3) Developing optimal technology portfolios with policy and economic considerations, using optimization and decision-making methods under uncertainties.

INTR 6000I - Transportation Decarbonization and Energy Transition (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6160) Tu 03:00PM - 05:50PMRm 201, E3WEI, Wei208120 
COURSE INFO
VECTOR[3-0-0:3]
DESCRIPTIONThe postgraduate course delves into the fusion of deep learning techniques with human mobility analytics. In an era dominated by extensive data availability, the course addresses the complexities of mobility analytics using cutting-edge deep learning methodologies. Students will gain a foundational understanding of deep learning concepts and apply them to decipher intricate large-scale human mobility data. The course aims to empower students to contribute meaningfully to fields such as urban planning, transportation management, and public health. Through literature review and hands-on projects, students will develop proficiency in applying deep learning to real-world mobility challenges, fostering a well-rounded skill set for addressing the evolving landscape of human mobility analytics.

INTR 6000M - Deep Learning for Human Mobility Analytics (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
L01 (6158) Mo 06:00PM - 08:50PMRm 202, E3LIANG, Yuxuan3013170 
COURSE INFO
VECTOR[0-1-0:0]
DESCRIPTIONSeminar topics presented by students, faculty and guest speakers. Students are expected to attend regularly and demonstrate proficiency in presentation in accordance with the program requirements. Graded P or F.

INTR 6800H - Seminar in Intelligent Transportation (0 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
T01 (6153) Tu 01:30PM - 02:20PMRm 102, W4ZHENG, Xinhu8051290 
COURSE INFO
VECTOR[1-3 credit(s)]
DESCRIPTIONAn independent study on selected topics carried out under the supervision of a faculty member.

INTR 6900A - Independent Study (3 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
R01 (6154) TBATBATBA203170 
COURSE INFO
DESCRIPTIONMaster's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.

INTR 6990 - MPhil Thesis Research (0 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
R01 (6155) TBATBATBA999279720 
COURSE INFO
DESCRIPTIONOriginal and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.

INTR 7990 - Doctoral Thesis Research (0 units)

SectionDate & TimeRoomInstructorQuotaEnrolAvailWaitRemarks
R01 (6156) TBATBATBA999479520