The Federal Highway Administration (FHWA) has been collecting the annual Highway Performance Monitoring System (HPMS) data, monthly traffic volume count data, and travel behavior data under the umbrella of the National Household Travel Survey (NHTS) for a long time. More recently, the FHWA has been acquiring what is known as the National Performance Management Research Data Set (NPMRDS) from private businesses. The NPMRDS data is a probe-based travel time dataset providing segment-level travel times in 5-minute increments for over 440,000 directional miles of roads designated as the National Highway System (NHS) for the entire nation. These data are unprecedented in terms of coverage, granularity, and historical continuity and offer an opportunity for integrated data analysis.
The selected applicant will explore integrated usage of the HPMS, traffic counts, NHTS, NPMRDS, and other data to analyze how travel behavior affects highway incidents, fuel consumption, and traveler route choices. Specifically, the objectives of this research are to (1) integrate the NPMRDS, HPMS, count, NHTS, and safety datasets to improve the effectiveness of future data collection; (2) investigate potential connections among travel behavior (e.g., trip purpose), volume, class, speeds, crashes, and other factors at both macro and micro levels to direct more effective data collection and analysis; and (3) explore the relationships among fuel consumption, route choices, and travel behavior at both the macro and micro levels.
The selected applicant will reside in FHWA’s Office of Highway Policy information at the USDOT/FHWA Headquarters in Washington, DC. In addition, the selected applicant is expected to interact with a wide range of USDOT modal Administrations and Offices, including FHWA Office of Safety, Office of Operations, Office of Planning, Office of Infrastructure, the National Highway Traffic Safety Administration (NHTSA), and the Federal Motor Carrier Safety Administration (FMCSA), and different University Transportation Centers (UTCs).
The selected applicant is expected to be an independent thinker and a self-starter. Talented analysts with innovative ideas and expertise in analyzing big datasets involving geospatial information and large volumes of structured and unstructured data are encouraged to apply. Knowledge associated with travel behavior data is highly desired. In addition to the highly needed logical reasoning capacity, candidates should have basic software skills such as statistical programs (e.g., SAS, R), geospatial programs (e.g., ArcGIS), and programming languages (e.g., Python).
HPMS; NHTS: travel behavior; count data; NPMRDS; road safety; geographic information systems; statistical analyses; big data