 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | INTR 6000E |
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6151) | 02-SEP-2024 - 06-DEC-2024 We 01:30PM - 04:20PM | Rm 222, W1 | ZHU, Meixin | 30 | 11 | 19 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Intelligent 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6148) | 02-SEP-2024 - 06-DEC-2024 Th 09:00AM - 11:50AM | Rm 201, E3 | BAI, Yun JIA, Shuai SUN, Xiaotong | 20 | 7 | 13 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| EXCLUSION | IOTA 5003 |
| CO-LIST WITH | IOTA 5003 |
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6149) | 02-SEP-2024 - 06-DEC-2024 Tu 09:00AM - 11:50AM | TBA | YAN, Jia YANG, Liuqing | 15 | 9 | 6 | 0 | The classroom is E1102. |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | INTR 6000F |
| DESCRIPTION | The 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6150) | 02-SEP-2024 - 06-DEC-2024 Mo 09:00AM - 11:50AM | Rm 222, W1 | ZHENG, Xinhu | 30 | 11 | 19 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6152) | 02-SEP-2024 - 06-DEC-2024 Mo 01:30PM - 04:20PM | Rm 202, E1 | YU, Huan | 20 | 13 | 7 | 0 |
| ATTRIBUTES | [BLD] Blended learning |
|---|---|
| VECTOR | [3-0-0:3] |
| EXCLUSION | ROAS 5900 |
| CO-LIST WITH | ROAS 5900 |
| PREVIOUS CODE | INTR 5600 |
| DESCRIPTION | The 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6147) | 02-SEP-2024 - 06-DEC-2024 We 09:00AM - 11:50AM | Rm 202, E1 | HE, Dengbo | 14 | 12 | 2 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6160) | 02-SEP-2024 - 06-DEC-2024 Tu 03:00PM - 05:50PM | Rm 201, E3 | WEI, Wei | 20 | 8 | 12 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | The 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6158) | 02-SEP-2024 - 06-DEC-2024 Mo 06:00PM - 08:50PM | Rm 202, E3 | LIANG, Yuxuan | 30 | 13 | 17 | 0 |
| VECTOR | [0-1-0:0] |
|---|---|
| DESCRIPTION | Seminar 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| T01 (6153) | 02-SEP-2024 - 06-DEC-2024 Tu 01:30PM - 02:20PM | Rm 102, W4 | ZHENG, Xinhu | 80 | 52 | 28 | 0 |
| VECTOR | [1-3 credit(s)] |
|---|---|
| DESCRIPTION | An independent study on selected topics carried out under the supervision of a faculty member. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6154) | TBA | TBA | TBA | 20 | 3 | 17 | 0 |
| DESCRIPTION | Master'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. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6155) | TBA | TBA | TBA | 999 | 27 | 972 | 0 |
| DESCRIPTION | Original 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. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6156) | TBA | TBA | TBA | 999 | 47 | 952 | 0 |