Steve Boyles Stephen Boyles
Associate Professor

Civil, Architectural, and Environmental Engineering
The University of Texas at Austin
Ernest Cockrell, Jr. Hall (ECJ) 6.204
301 E. Dean Keeton St. Stop C1761
Austin, TX 78712-1172

Phone: 512-471-3548
Fax: 512-475-8744
Email: sboyles at mail dot utexas dot edu

Curriculum vitae (updated September 20, 2017)

[Teaching] [Research] [Group] [Trivia] [Music]

Hello! I am a transportation engineering faculty member at The University of Texas at Austin. I'm interested in a variety of network modeling problems, as described more fully below. If you're looking for information on a course I'm teaching (or have taught in the past), follow the link to my teaching page. If you're interested in reading publications I've authored or learning about projects I work on, follow the link to my research page. More information on my research group and their interests can be found on their page.

Some of the topics I'm interested in are:

  • Simulation: I'm interested in integrating land use and travel demand models into regional traffic simulators. This has the potential to accurately model the complex interactions between human behavior, economics, traffic, and measures of effectiveness such as mobility, air quality, and environmental justice. In particular, I believe that recent advances in mesoscopic simulation give rural regions the ability to represent very large spatial areas, perhaps even on the statewide scale.
  • Pricing: The topic of roadway pricing, or tolling, has received a huge amount of attention for agencies seeking congestion relief or find alternate revenue stream to support maintenance and infrastructure expansion. There are many interesting problems in mathematics and economics about the best way to apply tolls; furthermore, there is a strong political dimension to toll policies which I find fascinating. I'm particularly interested in aspects of pricing problems which apply uniquely to rural regions, where travel demand patterns and agency objectives diverge sharply from most of the research done in urban pricing contexts.
  • Asset Management: The importance of maintaining infrastructure is often overlooked by the public, but is a need which is vitally known by all public agencies in this country. Furthermore, as recent events have shown, predicting future economic conditions, and their impact on maintenance spending, is all but impossible: just a few years ago, skyrocketing construction and materials costs forced agencies to re-evaluate their maintenance plans. Then recession hit, and states were faced with declining tax revenues to support critical maintenance projects. I'm interested in developing optimization models for public agencies, or engineering firms in a public-private partnership, allowing them to best spend the funds available for maintenance, and to plan for the future, recognizing that the future may not turn out as originally planned.
  • Routing: The amount of time needed to travel from one point to another can never be known in advance, due to congestion, accidents, bad weather, construction work, special events, and myriad other factors. This often leads to wasted time, for instance, when people leave for work or the airport earlier than needed, to hedge against the possibility of bad traffic. A host of technologies has been developed to help address this problem - variable message signs notifying travelers of accidents, in-vehicle navigation devices with real-time congestion information, and transit information systems notifying riders when thir bus will arrive are but three examples. New and improved algorithms are needed to model how travelers use this information to choose their travel routes and modes, and how it can be deployed to best service the public.
  • Traffic Assignment: Traffic assignment is the natural generalization of routing problems, which are concerned with how individuals behave. Traffic assignment, on the other hand, is concerned with the collective behavior of a population, including where congestion forms, and which neighborhoods and groups of people are most affected by different transportation policies. A huge number of opportunities exist for making traffic assignment models more realistic (for instance, accounting for uncertain travel conditions) or more efficient (for instance, being ableto solve problems in real-time), and I'm very interested in both.

Feel free to drop me an email if you want to talk about any of these!

Last updated July 18, 2014