An Analysis of Temperature and Pressure Data from Connected Vehicles in the Developmental Testbed Environment
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2009-06-09
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Edition:Final; Feb. 2008-Jan. 2013.
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NTL Classification:NTL-INTELLIGENT TRANSPORTATION SYSTEMS-INTELLIGENT TRANSPORTATION SYSTEMS;NTL-INTELLIGENT TRANSPORTATION SYSTEMS-Road Weather Management;
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Abstract:With funding and support from the USDOT RITA and direction from the FHWA Road Weather Management Program, 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 PoC, DUAP, and DTE09
experiments, and (2) provided hardware recommendations for processing data. Major conclusions include: (a) The SRT, CRT, NST, and CAT provide a
robust 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 KDTW; and (f) Storage of vehicle and ancillary data will require considerable disk space.
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