Researchers at the University of Michigan, Ann Arbor, have produced improved rainfall estimates by combining weather radar with windshield wiper observations from connected vehicles. An open-access paper on their work is published in the journal Scientific Reports.
Existing methods for measuring precipitation are subject to spatial and temporal uncertainties that compromise high-precision applications like flash flood forecasting. Windshield wiper measurements from connected vehicles correct these uncertainties by providing precise information about the timing and location of rainfall.
Using co-located vehicle dashboard camera footage, we find that wiper measurements are a stronger predictor of binary rainfall state than traditional stationary gages or radar-based measurements. We introduce a Bayesian filtering framework that generates improved rainfall estimates by updating radar rainfall fields with windshield wiper observations. We find that the resulting rainfall field estimate captures rainfall events that would otherwise be missed by conventional measurements.—Bartos et al.
The team noted that urban flash flooding is perhaps the best illustration of the need for high-resolution precipitation estimates. Flooding is the leading cause of natural disaster fatalities worldwide, with flash floods accounting for a majority of flooding deaths in developed countries.
However, flash flood forecasting is to a large extent hindered by a lack of high-resolution precipitation data, with spatial resolutions of <500 m and temporal resolutions of 1–15 minutes required for urban areas. The rise of connected vehicles may provide a solution.
While dedicated sensor networks are expensive to deploy and maintain, fleets of connected vehicles can capture real-time data at fine spatial and temporal scales through the use of incidental onboard sensors, the researchers said.
With regard to rainfall measurement, windshield wiper activity offers a novel means to detect the location and timing of rainfall with enhanced precision. When used in conjunction with modern signal processing techniques, wiper-based sensing offers several attractive properties: (i) vehicles achieve vastly improved coverage of urban areas, where flood monitoring is important; (ii) windshield wiper intensity is easy to measure and requires little overhead for processing (as opposed to video or audio data); and (iii) vehicle-based sensing can be readily scaled as vehicle-to-infrastructure communication becomes more widespread. Moreover, many new vehicles come equipped with optical rain sensors that enable direct measurement of rainfall intensities. When paired with data assimilation techniques, these sensors may enable even higher-accuracy estimation of rainfall fields compared to wipers alone.—Bartos et al.
Matthew Bartos, Hyongju Park, Tian Zhou, Branko Kerkez & Ramanarayan Vasudevan (2019) “Windshield wipers on connected vehicles produce high-accuracy rainfall maps”Scientific Reports doi: 10.1038/s41598-018-36282-7