With the national raw data updated each year, the UMD team ensures that the highest quality raw data sources for person and truck travel, respectively, are employed in the NextGen NHTS OD Data Program. Raw data panel quality is evaluated based on sample size, representativeness, location data accuracy, data frequency, data consistency, and other quality metrics. The UMD team will identify all trips from the raw location data, as well as trip origin, destination, start time, and end time. For each identified trip, imputation algorithms will then be applied to produce travel mode, trip purpose, and distance estimates. After these steps, a “national all-trip roster” is obtained and stored in a trip roster format for person travel and truck travel, respectively.
The entire national all-trip roster will be used by the UMD team to develop national OD products. Trips will be weighted based on traffic counts, population and employment data, imputed socio-demographics, and a multi-level weighing method. The UMD team will calibrate and validate OD products based on HPMS, NTD, DB1B/T-100, NHTS core survey control totals, and other validation datasets. Before delivering national OD data products, a rigorous four-step quality assurance and quality control (QA/QC) procedure will be implemented, which includes: (1) an internal UMD check; (2) a non-UMD team member check; (3) an FHWA check; and (4) an expert panel check.
UMD will also work with FHWA and the project expert panel to establish raw data and final product quality standards for pooled fund OD tables. A state DOT, MPO, or another organization in the NextGen NHTS OD pooled fund program can also procure their customized local OD products. Trip weighting and product validation will be conducted separately for local OD products based on local area control totals and validation datasets. UMD will be in charge of the production, quality control and quality assurance of all local OD products and ensure the consistency between local OD and national OD products from the same NextGen NHTS OD Data Program.
Commitment to Transparency
The University of Maryland-led team is committed to providing high-quality and credible passenger and truck travel OD data products at the national and local levels to FHWA and NHTS pooled fund partners.
Our team members understand that ensuring data and method transparency and data credibility is critical for gaining public acceptance and user confidence in OD data products derived from passively collected data sources. With this understanding, we will:
- Ensure methods transparency and statistical validity in addition to final product quality assurance and quality control;
- Summarize and report technical issues encountered, methods used to overcome the issue, and suggestions of improvements as part of our project deliverables;
- Publish data quality metrics to improve data transparency, and;
- Provide open access to computation algorithms developed by University of Maryland with FHWA funding to improve methods transparency.