INTR 6000A Traffic Flow Systems and Control
2022 Spring
The course introduces the fundamentals of traffic flow theory and will describe traffic flow models of micro-and macroscopic levels, governed by dynamical systems including Partial Differential Equation and Ordinary Differential Equation. Control system tools include system modeling, state-space representations, stability analysis, state observer, feedback control, and optimization. Classic traffic management schemes (by ramp metering, and variable speed limits) and advanced control and sensing strategies by connected and autonomous vehicles will be discussed. Students will be able to understand key concepts and the physics of the transport phenomena, use elegant mathematical models to study the causes of traffic congestion, and apply the systems & control tools to develop traffic control strategies to alleviate congestion.
本课程介绍交通流理论的基础知识，并描述微观和宏观层面的偏微分方程和常微分方程交通流模型。 控制系统工具包括系统建模、状态空间表示、稳定性分析、状态观测器、反馈控制和优化。 本课程将讨论经典交通管理方案（匝道信号的控制和可变速度限制）以及网联车和自动驾驶车辆的高级控制和传感策略。 通过本课程的学习，学生将能够理解交通现象的关键概念和物理原理、使用数学模型研究交通拥堵的原因、并应用系统和控制工具制定交通控制策略以缓解拥堵。
INTR 6800 Seminar on Intelligent Transportation
2021 Fall
The research topics that are covered in a series of seminars include:
本研讨课的主题将涵盖以下方面：
- Macroscopic traffic flow modeling and boundary control
- Connected and automated vehicles
- Traffic prediction and control by connected vehicles
- Reinforcement learning control of transportation system
- Electrical vehicles and vehicle grid integration
- Infrastructure resilience of large-scale road networks
- Railway safety regulation
- Carpooling and tolling for transportation systems
- 宏观交通流模型和边界控制
- 网联车和自动驾驶车辆
- 基于网联车的交通预测和控制
- 交通系统的强化学习控制
- 电动汽车及汽车并网
- 大型道路网络的基础设施弹性
- 铁路安全法规
- 运输系统的拼车与收费
MDC Lab @ HKUST(GZ) 