Graduate Courses

Traffic Engineering

A study of both the underlying theory and the use of traffic control devices (signals, signs, pavement markings) and relationships to improve traffic flow and safety, driver and vehicle characteristics, geometric design, and societal concerns. Also includes methods to collect, analyze, and use traffic data.
Traffic Engineering Syllabus

Transportation Planning

This course covers the theoretical foundations of transportation planning methods.  This course will cover the theory and application of aggregate and disaggregate models for trip generation, trip distribution, mode choice, and trip assignment.   The focus of the course will be on passenger based travel demand models but will also introduce state of the art models including activity based models as well as freight forecasting models.   Students will be introduced to transportation planning software through lab tutorials.
Transportation Planning Syllabus 

Data Analysis and Machine Learning

The purpose of this course is to provide students with a solid background in the application of common statistical/econometric analysis techniques for examining transportation systems data and performing related statistical modeling.  This course emphasizes the empirical application of statistical techniques, but underlying theories and their limitations will also be discussed and simple derivations will be performed in class. Transportation systems data sets from regional, state, and national sources will be used as applications and case studies. Although transportation systems applications are used, students from all areas of Civil Engineering are welcome, since the techniques taught have broad applications to civil engineering.  General topics include but are not limited to: (1) Survey sampling- sampling methods and statistical properties of survey sample estimates, (2) Statistical inference- hypothesis tests, nonparametric tests, goodness-of-fit, (3) General linear model- estimation methods and model assumptions, and (4) Advanced modeling- time series, machine learning (neural network, support vector machines, etc.). Advanced topics will be covered if time permits.
Transportation Data Syllabus

Undergraduate Courses

Transportation Systems Engineering

Introduction to transportation systems engineering and planning. Includes the following topics: transportation governance, financing, and the effect on the environment; traffic flow theory; safety; traffic operations and control; capacity; and travel demand modeling. This course is the first of two required classes in transportation engineering at the University of Arkansas.  This course focuses on systems engineering topics.  The second course focuses on infrastructure design. 
Transportation Systems Engineering Syllabus