4B.2 Testing and Implementation of Mobile Road Condition Information to Serve the Transportation System

Tuesday, 9 January 2018: 9:00 AM
Room 10AB (ACC) (Austin, Texas)
Virve Karsisto, Finnish Meteorological Institute, Helsinki, Finland; and P. Nurmi

Road weather information and observations play a highly relevant role in wintertime weather forecasting and road maintenance actions serving the transportation systems in Finland and other Northern countries. Monitoring of road conditions is fundamental in providing services for all road users against adverse driving conditions. Fixed road weather stations (RWS) have been the major source of road weather information for decades. However, their information is limited to specific road points along major roads, so there are wide gaps in observations in between RWSs and on minor roads. The advancements in ICT development have quite recently made it possible to collect data from moving sources in addition to stationary ones. Modern cars are equipped with multiple sensors and can provide means to obtain even meteorological information in unforeseen dense spatial scales. However, the data quality from such sources must be carefully assessed before implementation to weather forecasting applications and ITS (Intelligent Transport System) solutions. The Finnish Meteorological Institute (FMI) has long-standing experience and know-how in developing intelligent road weather applications to provide accurate road weather information to improve road safety under extreme driving conditions.

Receiving information from car’s CAN bus system is not straightforward. However, mobile road condition information can also be obtained from additional sensors attached to cars. One device of this kind is the Teconer RCM411 which measures friction and road status optically and is often complemented with the optical surface temperature sensor RTS411. FMI has conducted research where observations originating from Teconer devices were compared against measurements from Vaisala RWSs. Mobile devices are more exposed to disturbances like exhaust fumes and drifting snow. Possible systematic differences between the data sources must be assessed before mobile observations can be reliably combined with road weather station information. The occurrences when a vehicle passed a road weather station were extracted from the data in the comparison study. The comparison was not totally unambiguous, because the measurements were usually not from exactly the same spot. However, some conclusions can be drawn by making use of a large dataset. The study contained data from three winter periods, 2014-2015, 2015-2016 and 2016-2017. The results showed that Teconer surface temperature measurements are on average warmer than measurements made by Vaisala DRS511 instrument installed directly in asphalt at the RWS. There were also systematic differences between individual Teconer devices. The mean difference between Teconer and RWS measurements were more dependent on the individual RTS411 device than the RWS location, so the installation of the device on the vehicle can considerably affect the measurements. As a conclusion, mobile Teconer surface temperature observations provide highly useful information in between RWSs and can be combined with RWS information, but some statistical corrections may be needed depending on the installation.

FMI participates in several international projects which have the objective to find new ways to optimize the use of mobile observations in intelligent road weather forecasting applications. WiRMa (Industrial Internet Applications in Winter Road Maintenance) project covers the major roads in Northern Finland, Sweden and Norway with the goal to enhance maintenance operations by using new sensor data in the analysis of the current situation and in the road weather forecasts. Intelligent Arctic Trucks is a smaller scale project where mobile vehicle observations are collected from mining trucks driving a dedicated route between the Kevitsa copper and nickel mine and Kemi harbor in Northern Finland. Sod5G project will set up 5G network testing environment for intelligent transport in the area of Sodankylä airport in Lapland. Road weather information will be collected from two RWSs and from mobile test track vehicles which will be used to provide detailed road weather services for the test track. All these projects will add to improved services serving the entire transport system.

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