Using data analysis and interactive reporting/presentation techniques in R, Python, and Jupyter Notebooks, the team is able to relay results from analyses quickly as projects progress. The team has also developed a number of skills for visualizing origin-destination characteristics and travel patterns from passive data and roadway networks, including interactive graphics (MAG External Travel Study)…
Emerging Data and Methods
Understanding Bias Emerging big data sources unlike traditional surveys come with their own biases, which could be distinct across space, time and socio-demographics. This is because, these data sources are more of a convenience sample heavily influenced by the purpose of software application generating it, from which it is derived. Thus, it makes them more…
National Performance Management Research Data Set
The FHWA has acquired a national data set (called NPMRDS) of average travel times on the National Highway System for use in its performance measures and management activities. TTI is a part of the NPMRDS project team and provides geospatial data integration (i.e., GIS conflation) services. In particular, TTI conflates selected HPMS attributes onto the…
Pedestrian and Bicyclist Research
TxDOT Pedestrian and Bicyclist Count Data Program TTI has worked with the Texas Department of Transportation (TxDOT) since 2016 to improve the availability and quantity of pedestrian and bicyclist count data in Texas. The most visible product of this work has been a statewide database called the Texas Bicycle and Pedestrian Count Exchange, which is…
Transportation System Management and Operations for Freight
With the emergence of connected and automated vehicle (CAV) telecommunications, TSMO strategies fit right in by making the best use of opportunities to coordinate freight movement and modal infrastructure in highly efficient ways. Some of TTI’s state-of- the-art research capabilities include: CAV Technology Leading CAV technology efforts with the Texas Department of Transportation (TxDOT) as…
Big Data and Machine Learning Analytics
TTI’s Travel Survey and Passive Data research team are leaders in the integration of passive data from GPS connected vehicle data and Location Based Services (LBS) data with transportation planning practices. The team’s efforts focus on data fusion of these data sets with traditional survey and aggregate data sources. Increasingly machine learning methods are implemented…
Support for Urban Mobility Analyses
“Support for Urban Mobility Analyses” (SUMA) is the latest project title for this study. Currently, SUMA sponsors include 16 state DOTs, the District of Columbia DOT and FHWA. Over the years, the project has covered a number of aspects of urban mobility analyses. Tasks of mutual interest to all the study sponsors over the years…
Truck Drivers’ Routing Decisions
Evaluating the Impact of Real-Time Mobility and Travel Time Reliability Information on Truck Drivers’ Routing Decisions Publication: Transportation Research Record: Journal of the Transportation Research Board Authors: Xiaoqiang Kong, William L. Eisele, Yunlong Zhang, and Daren B. H. Cline Abstract The research analyzed 14,538 global positioning system devices recording trips on the I-495 crossing through…
Mobility Analysis Visualization Tools
Congestion Management Process Analysis Tool The Congestion Management Process Analysis Tool (COMPAT) is a web-based product that allows the user access to annual traffic congestion statistics on the majority of roads in an individual Texas metropolitan area. COMPAT is designed to help local agencies such as metropolitan planning organizations monitor traffic congestion on area roadways…
Traffic Congestion & Reliability
Mitigating congestion is a high priority for the Federal Highway Administration, which has established congestion mitigation as a key focus area. This report supports this effort by providing a review of congestion issues and solutions in the United States. The emphasis of the report is on measuring trends in travel time reliability and making travel…