Here’s a snapshot of the current research and active projects under Team Machemehl. Some of these projects are happening in collaboration with more than one agency. If you wish to discuss any of these pieces of work, feel free to drop me an email at rbm@mail.utexas.edu.
Pedestrian Fatality Analysis on I-35
The Austin District of TxDOT has a number of pedestrian fatalities occurring on controlled-access highways. Since these facilities are not at all built for pedestrians, it is not clear why pedestrians choose to cross at these locations. This works aims to investigate pedestrian fatalities incidents on I-35 during the last five years to inform crash mitigation efforts. Documentation includes crash locations, time of day, contributing factors, traffic impacts, and comprehensive public cost estimates.
Early Warning System for Pavement damage
The Early Warning System has been built to detect changes in land use and predict truck traffic increases during construction activity and post-construction traffic patterns. The idea for The System originally was conceived by Mike Murphy and Mike Arellano as a solution to an issue with excessive truck loading in Travis County. Instead of spending $10 million to fix a damaged road where a factory was built, $1 million could be spent to reinforce the pavement prepare for such heavy loading in advance of construction. These kinds of savings are significant and valuable to the taxpayer. At present, the GIS-based system is currently maintained by Team Machemehl and considered pavement development from urban growth and fracking activities in the Austin District of TxDOT.
Highway Safety Improvement Project selection tool
The Highway Safety Improvement Program (HSIP) is a competitive funding program to address critical safety needs. The HSIP requires each district within TxDOT to develop eligible safety project lists to compete for the available funding. Moreover, this program contains various funding categories each with different eligibility criteria. Therefore, this work aims to create a tool tailored to the Austin District to reduce the time needed to develop eligible project lists, distribute projects into the various funding categories, and identify high benefit-cost safety improvement projects. The tool will allow the Austin District to quickly responding to HSIP funding calls and to reduce the time required to develop the safety project lists.
Bicycle Signal Experiments
Twelve intersections are proposed for experimentation with bicycle signal faces under MUTCD Interim Approval IA-16 in the City of Austin. We will collect data at eleven intersections before and after new bicycle signals are installed. All data will be collected during the spring semester when school is in session. At three intersections, the City of Austin will collect and process data. We will evaluate the data and include conclusions in their results. With before and after data, we will evaluate measures of effectiveness between periods including travel time, stop frequency, stopped delay, minor-street delay, traffic speed profile, cycle length, fuel consumption, and emissions to assess the traffic operational and environmental benefits of the adaptive signal system. All tasks will be conducted in close coordination with City of Austin Transportation Department (ATD).
Timing of Right of Way Closures
Closure of street lanes is often necessary to permit the maintenance of many different types. Most Austin streets have hours during typical days in which lane closures could be executed without large incremental traffic delay, however the hours of the day during which traffic demands would best enable lane closures may be different across street functional classes and geographic areas of the City. Therefore, this effort will use 24-hour traffic counts and other available data sources to identify the hours of typical days that would best permit lane closures for each geographic area of the City.
Estimating Impacts of Bicycle Facilities: Forecasting Numbers of Users
Most methods for estimating impacts of bicycle facilities have been focused on very large scale analyses, however, impacts of specific bicycle facilities or impacts upon specific population segments are rarely reported. Potential positive impacts of bicycle facilities are dependent upon the numbers of bicycle riders who actually use the facility once it is constructed. Predictive models for bicycle facility usage are developed using a combination of bicycle facility user counts, origin-destination surveys and socioeconomic data. A direct estimation method, as well as a two-step estimation procedure, are developed to estimate usage of a proposed bicycle facility. The use of zonal socioeconomic characteristics as predictor variables is intended to enable the models to predict bicycle facility usage by population segments. Usage predictions can form the basis for broad-spectrum estimates of bicycle facility impacts upon health, food availability, employment access, and ultimately regional sustainability. The generalized objective of this project is to develop a methodology to estimate the impacts of bicycle facility provision. However, the implied objective is the development of a methodology for estimating numbers of bike facility users. If facility usage can be estimated well, many positive impacts can be quantified including those on health, mobility, food availability, and commuter travel.
Study of the Texas driver’s license Process
The Texas Legislature required the Texas Department of Public Safety (DPS) to do this study of their driver license renewal process, and The University of Texas was selected by DPS to do the study. We are conducting surveys and focus groups gauging Texas citizens’ attitudes and impressions of the in-person and virtual renewal system. Based on these responses and further research, we will present to the DPS and the Texas Legislature on how to improve the online renewal system to shorten wait times at Texas DPS offices.
