Improving Road Weather Hazard Products with Vehicle Probe Data

Abstract

One of the goals of RITA's IntelliDrive initiative is utilization by the public and private organizations that collect, process, and generate weather products of vehicle sensor data to improve weather and road condition hazard products. Some users may not be able to, or not want to, contend with the complexities associated with vehicle data, such as data quality, representativeness, and format. With funding and support from the U.S. Department of Transportation's RITA IntelliDrive initiative and direction from FHWA's Road Weather Management Program, the National Center for Atmospheric Research is conducting research to develop a vehicle data translator (VDT) to address these vehicle-based data challenges. This paper first describes the VDT quality check (QCh) concept and then examines QCh pass rates for temperature and pressure data collected from 11 specially equipped vehicles operating in the Detroit test bed in April 2009. Results show that temperature pass rates are higher than pressure pass rates. Additionally, pass rates are somewhat affected by vehicle type, vehicle speed, ambient temperature, and precipitation occurrence for both temperature and pressure.

A Geostatistical Investigation into the Effective Spatiotemporal Coverage of Road Weather Information Systems in Alberta, Canada

“…Next, data that fell outside of the reasonable ranges was recognized as erroneous. The reasonable ranges were determined based on sensor specifications, locationspecific climatological ranges, and historical data ranges [16,17]. Then, in the model analysis test, data that fell beyond acceptable regions was reported as invalid.…”

“…In addition to the basic atmospheric observations, the data from onboard vehicle sensors, such as wiper state and antilock braking systems, can also be used in road weather condition estimation. With CV-enabled data in hand, Drobot et al [16,17] designed a quality and accuracy check process, which includes crosschecks with sensor specifications, climatological ranges, neighboring vehicle, and station measurements, for weather-related data from probe vehicles. Other data analysis shows that the quality of temperature and pressure data is affected by many factors, such as vehicle type, speed, and precipitation occurrence [16], and the temperature data from probe vehicles closely resembles data from stationary weather stations [17].…”

Potential of Intelligent Transportation Systems in Mitigating Adverse Weather Impacts on Road Mobility: A Review

“…Recent development of technologies to collect road weather data through vehicle-based sensor systems has been providing more forecast capabilities to transportation professionals [46]. Sensor-equipped maintenance vehicles can provide close to the ground road weather information compared with all other weather information sources.…”

Realizing the Potential of Vehicle-Based Observations

“…Potential Solutions: A solid set of sensor studies in the mobile environment may provide vehicle manufacturers and others with standards regarding elements such as optimal sensor type and placement. For example, studies indicate that placement of a temperature sensor near the front grill is optimal (2), producing temperatures accurate to less than 1.00°C, with a bias less than 0.25°C (9,10). To allow manufacturers the flexibility to select the optimal location for a given model, it may be necessary to articulate standards in terms of principles and guidelines rather than specific locations and other requirements.…”

“…Based on recent research (2,5,9,10) and expert opinion of the committee members, a list of desired vehicle data elements have been identified and are listed in Table 3. These data elements…”