An Analysis of Temperature and Pressure Data from Connected Vehicles in the Developmental Testbed Environment

The use of vehicle sensor data to improve weather and road condition products, as envisioned as part of the Research and Innovative Technology Administration (RITA), could revolutionize the provision of road weather information to transportation system decision-makers, including travelers. For example, vehicle-based probe data will significantly increase the density of weather observations near the surface and also provide unique datasets for deriving and inferring road-condition information. However, the amount of data flowing through a fully functional connected vehicle network could be immense, and many prospective users likely will not be capable of handling this vast quantity of data in its native form.With funding and support from the United States Department of Transportation Research and Innovative Technology Administration (USDOT RITA) and direction from the Federal Highway Administration (FHWA) Road Weather Management Program, the National Center for Atmospheric Research (NCAR) is developing a Vehicle Data Translator (VDT) that incorporates vehicle-based measurements of the road and surrounding atmosphere with other weather data sources and creates road and atmospheric hazard products. In support of VDT development, this report (1) analyzed archived probe message data from the Proof-of-Concept (PoC), Data Use Analysis and Processing (DUAP), and Development Testbed Environment 2009 (DTE09) experiments, and (2) provided hardware recommendations for processing data. Major conclusions include: (a) The Sensor Range Test (SRT), Climatological Range Test (CRT), Neighboring Surface Station Test (NST), and Combined Algorithm Test (CAT) provide a robust Quality Checking (QCh) set; (b) For DTE09, the Jeep Cherokees proved superior to the Ford Edges and Nissan Altima; (c) For all three data sets, temperature measurements are superior to pressure measurements; (d) Environmental conditions (precipitation, temperature) might affect the QCh pass rates, but vehicle characteristics (speed) and time of day do not. The effects of environmental conditions on these datasets were not statistically significant for the most part, and physically the differences were small; (e) For the temperature observations that passed QCh in DTE09, the resulting statistics indicate that the vehicle data is very similar to Detroit Metropolitan Wayne County Airport (KDTW); and (f) Storage of vehicle and ancillary data will require considerable disk space.