CEGE 3102
Uncertainty and decision analysis
Fall 2024
Embedded Files
Many of the engineering systems we design are subject to uncertain conditions. Road congestion depends on driver variability, bad weather, and accidents, all of which vary from day to day. Structures are designed without perfect knowledge of future wind loads and weather deterioration. Water resource infrastructure must deal with too much rain in some years and too little in others. To incorporate uncertainty into our engineering designs, we need to be able to describe them quantitatively. After completing CEGE 3102, you will be familiar with the fundamentals of probabilistic modeling and how to apply it to engineering problems. Many subsequent CEGE classes will rely on concepts and skills from CEGE 3102.
This course will introduce you to planning, analysis, and design of transportation systems. Topics include travel demand modeling, mode choice, network analysis principles, and transit operations; traffic flow principles, level of service, and signal control; and roadway geometric design. After completing this course, you will have a fundamental understanding of transportation system concepts and experience with problem-solving in the transportation engineering context.
This course provides an overview of the civil air transportation system design and operations. After completing this course, you should be able to describe the operations of civil transport aircraft from the pilot, company, and air traffic control perspectives; conduct basic economic analysis on airline operations and demand; conduct capacity analysis for airspace and airports; and conduct basic optimization for air transportation operations. This course will prepare students for working with the civil aviation industry.
This course is available at both the 4xxx (undergraduate) and 5xxx (graduate) levels.
This course provides a mathematical and rigorous coverage of traffic flow parameters and relationships, queueing models of traffic flow, kinematic wave theory and solution methods, mesoscopic node models, and optimal control. Class time is primarily spent working collaboratively to prove analytical properties of traffic flow theory, which is designed to advance your proof skills as well as their subject knowledge. Assignments emphasize implementation of analytical concepts in software to facilitate dynamic network loading on city networks. After completing this course, you should have a deep analytical understanding of the standard traffic flow models as well as the skills to further develop them through independent research.
CEGE 1201
Emerging technologies in transportation: automated and electric vehicles
Spring 2024
Emerging battery and computer technologies are revolutionizing our daily transportation. Vehicle automation has the potential to reduce congestion, create new methods of traffic control, and change our travel patterns. 29% of United States greenhouse gas emissions come from transportation, and electric vehicles could help reduce the environmental impacts. This course presents an introductory exploration into automated and electric vehicle technologies from a transportation systems perspective. As you study emerging technologies, you will also get exposed to the engineering methods used to design current transportation systems.
Programming tutorials
These tutorials are intended to help new graduate students learn the programming skills needed to implement algorithms for research. They are designed around solving standard problems, and after completing them students will have a working implementation of the solution algorithm. Tutorials are written in the Java programming language. Each tutorial is separated into multiple steps in roughly increasing difficulty. Some explanation with links to relevant Java language skills are included for each step. Some starting code is provided, and autograding is used to check correctness for each step.
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