|| Stephen Boyles |
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
Curriculum vitae (updated November 19, 2018)
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
- 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