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Algorithm implementation for a
“Road Weather Information System”:
the CLEAN-ROADS project case study
ing. Gianluca Antonacci, CISMA Srl - Bolzano
Description of the development of a set of algorithms within a “decision
support system” by means of open source tools.
●
Case study: the EU Life+ Project CLEAN-ROADS
●
Problem identification
●
Open source software tools
●
Achieved results
Summary
The Life+ “CLEAN-ROADS” Project has been founded by EC and carried out by
the following partners
• Autonomous Province of Trento
• IDM Südtirol
• FAMAS System
AIM of the project
●
Forecast of road temperature in advance in order to support
road maintenance services in winter conditions in the Province of Trento
●
Improve the efficiency of the use of de-icing chemicals
●
Reduce negative environmental impact and costs
by means of
●
a Maintenance Decision Support System (MDSS)
CISMA was contracted by IDM and responsible for part of the algorithm
implementation, to be included in the decision support system toolchain
Case study
• Ice forms on road pavements in high-humidity conditions when road surface
temperatures are below 0°C → Slippery roads increase accident risk
• Spreading de-icers is common practice but excessive / uncontrolled use is both
hazardous for the environment and cost-demanding for road maintenance system
(source: CLEAN-ROADS flyer – clean-roads.eu)
Problem identification (1)
●
Reliable temperature forecast needed to optimize maintenance costs and reduce
the risk → weather forecast tools need to be included in the DSS
●
A decision support system has to cope with differente “languages”, in this case
not only informatics, but also engineering, statistics & physics
Problem identification (2)
decision
support
system
Test Area
Implementation area
• DSS should rely on already existing procedures and data, not everything can be
re-engineered from scratch → customization of interfaces
●
Different competence needed
●
Calculus model needed ...
●
… with the requisite of being able to “talk” to different preexistent tools,
procedures, data
Problem analysis
statistics:
environmental
data analysis
engineering:
on field de-icing
procedure +
data acquisition
physics:
modelization
of physical
processes
informatics:
data elaboration,
transfer &
visualization
DSS algorithms
Adopted software tools:
- an open source temperature forecast model (named METRo)
- high level statistical tools (R )
- GIS software (GRASS, QGIS)
- scripting tools (bash / python / php)
- plotting (gnuplot and R)
Adopted software tools:
- an open source temperature forecast model (named METRo)
- high level statistical tools (R )
- GIS software (GRASS, QGIS)
- scripting tools (bash / python / php)
- plotting (gnuplot and R)
Schematics (1)
Road temperature forecast scheme
European
Weather
Forecast
Local
weather
service
Extraction of air
temperature
forecast on
selected points
Database
Road-weather
stations (real time
data delivery)
Thermal mapping
(scheduled delivery)
Single point
temperature
forecast (METRo)
Spatialization
& mapping
web service
& graphics
Schematics (2)
METRo model
●
One of the most widely used models for road weather predictions.
●
Created in 1999 by Canadian Environmental Agency, distributed under the GPL license and
actively mantained
●
Is a so called 1D model, i.e. performs forecasts at single points
●
Mainly written in Python but also use FORTRAN and C
Necessary input data:
●
Data measured at a road weather station
●
Weather forecast (atmospheric data)
●
Road characteristics description
Advantages
●
Its code is freely available and well documented (http://home.gna.org/metro/.)
●
Performs well under a variety of weather conditions
●
Relatively easy to acquire, install and use.
Software tools
physics informatics
Data automatically
gathered from installed
road weather stations
access to DB through WSDL
protocol → interface + data
validity check (python)
Weather sensors: precipitation
temperature, relative humidity and
global solar radiation
Road sensors: surface
temperature, sub-surface
temperature, surface condition
Famas System instrumentation
(picture Final workshop presentation, Servizio Gestione Strade
Provincia Autonoma di Trento http://clean-roads.eu)
Data gathering
physics informatics engineering
●
METRo software code was modified & adapted in the physical modelization in order to cope
with our target (in fact is developed for Canadian area, not entirely suitable for our case),
e.g. road emissivity, diffuse radiation, ground stratigraphy
●
Multiple runs with different parameter settings → calibartion phase
●
Tools: compilers, “R” statistical software and… a hardcopy meteorology manual!
Software setup
physics statisticsinformatics
METRo is a 1D model, which performs forecasts
at single points
To spazialize forecast, thermal mapping is
performed: acquisition of temperature via an
infrared thermometer mounted on a vehicle
Thermal mapping permits to identify the pattern
and distribution of warm and cold sections
along a road.
Thermal mapping permits to identify the pattern
and distribution of warm and cold sections
along a road.
(picture from: Thermal mapping as a valuable tool for road weather forecastand winter road
maintenance - An example from the Italian Alps, RSCY 2016)
Spatialization
physics informatics engineering
Signal noise removal
• Temperature noisy signal from termal mapping due to different road characteristic → low-
pass Gaussian filter to remove this noise
●
Semi-automated process by means of “R” statistical packages (www.r-project.org)
Data analysis (1)
physics statistics
characteristic thermal fingerprint and spatialized forecasts
Also this stage performed by means of “R” software
cold
warm
Data analysis (2)
physics statistics
The combination of “single
point” METRo forecast with
the “thermal map” of the route
allows to predict temperature
over the entire route at
selected times.
GIS based elaboration (SHP /
KML files which can be
overlayed on a map)
Mapping
informaticsengineering
Web page accessible history
PHP and HTML coding, graphics generated on the fly using
gnuplot program
Data publication
informatics
●
The calculus system of a complex decision support system was successfully
developed entirely adopting open source software
●
Customization of well established calculus system (METRo) possible thanks to
code accessibility
●
Exploitation and scalability of the system is limited to the more general part;
when integrating a tool in a already existent toolchain you're mostly forced to
adapt the new part → the interfaces are really custom and not always reusable.
●
The system has been running for nearly two years now from the first
implementation
●
Integration with existing procedures is very important; the system is modular and
therefore maintainable in case of modification of other stages of the toolchain
Conclusion

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SFScon16 - Gianluca Antonacci: "The CLEAN-ROADS project case study"

  • 1. Algorithm implementation for a “Road Weather Information System”: the CLEAN-ROADS project case study ing. Gianluca Antonacci, CISMA Srl - Bolzano
  • 2. Description of the development of a set of algorithms within a “decision support system” by means of open source tools. ● Case study: the EU Life+ Project CLEAN-ROADS ● Problem identification ● Open source software tools ● Achieved results Summary
  • 3. The Life+ “CLEAN-ROADS” Project has been founded by EC and carried out by the following partners • Autonomous Province of Trento • IDM Südtirol • FAMAS System AIM of the project ● Forecast of road temperature in advance in order to support road maintenance services in winter conditions in the Province of Trento ● Improve the efficiency of the use of de-icing chemicals ● Reduce negative environmental impact and costs by means of ● a Maintenance Decision Support System (MDSS) CISMA was contracted by IDM and responsible for part of the algorithm implementation, to be included in the decision support system toolchain Case study
  • 4. • Ice forms on road pavements in high-humidity conditions when road surface temperatures are below 0°C → Slippery roads increase accident risk • Spreading de-icers is common practice but excessive / uncontrolled use is both hazardous for the environment and cost-demanding for road maintenance system (source: CLEAN-ROADS flyer – clean-roads.eu) Problem identification (1)
  • 5. ● Reliable temperature forecast needed to optimize maintenance costs and reduce the risk → weather forecast tools need to be included in the DSS ● A decision support system has to cope with differente “languages”, in this case not only informatics, but also engineering, statistics & physics Problem identification (2) decision support system
  • 7. • DSS should rely on already existing procedures and data, not everything can be re-engineered from scratch → customization of interfaces ● Different competence needed ● Calculus model needed ... ● … with the requisite of being able to “talk” to different preexistent tools, procedures, data Problem analysis statistics: environmental data analysis engineering: on field de-icing procedure + data acquisition physics: modelization of physical processes informatics: data elaboration, transfer & visualization DSS algorithms
  • 8. Adopted software tools: - an open source temperature forecast model (named METRo) - high level statistical tools (R ) - GIS software (GRASS, QGIS) - scripting tools (bash / python / php) - plotting (gnuplot and R) Adopted software tools: - an open source temperature forecast model (named METRo) - high level statistical tools (R ) - GIS software (GRASS, QGIS) - scripting tools (bash / python / php) - plotting (gnuplot and R) Schematics (1)
  • 9. Road temperature forecast scheme European Weather Forecast Local weather service Extraction of air temperature forecast on selected points Database Road-weather stations (real time data delivery) Thermal mapping (scheduled delivery) Single point temperature forecast (METRo) Spatialization & mapping web service & graphics Schematics (2)
  • 10. METRo model ● One of the most widely used models for road weather predictions. ● Created in 1999 by Canadian Environmental Agency, distributed under the GPL license and actively mantained ● Is a so called 1D model, i.e. performs forecasts at single points ● Mainly written in Python but also use FORTRAN and C Necessary input data: ● Data measured at a road weather station ● Weather forecast (atmospheric data) ● Road characteristics description Advantages ● Its code is freely available and well documented (http://home.gna.org/metro/.) ● Performs well under a variety of weather conditions ● Relatively easy to acquire, install and use. Software tools physics informatics
  • 11. Data automatically gathered from installed road weather stations access to DB through WSDL protocol → interface + data validity check (python) Weather sensors: precipitation temperature, relative humidity and global solar radiation Road sensors: surface temperature, sub-surface temperature, surface condition Famas System instrumentation (picture Final workshop presentation, Servizio Gestione Strade Provincia Autonoma di Trento http://clean-roads.eu) Data gathering physics informatics engineering
  • 12. ● METRo software code was modified & adapted in the physical modelization in order to cope with our target (in fact is developed for Canadian area, not entirely suitable for our case), e.g. road emissivity, diffuse radiation, ground stratigraphy ● Multiple runs with different parameter settings → calibartion phase ● Tools: compilers, “R” statistical software and… a hardcopy meteorology manual! Software setup physics statisticsinformatics
  • 13. METRo is a 1D model, which performs forecasts at single points To spazialize forecast, thermal mapping is performed: acquisition of temperature via an infrared thermometer mounted on a vehicle Thermal mapping permits to identify the pattern and distribution of warm and cold sections along a road. Thermal mapping permits to identify the pattern and distribution of warm and cold sections along a road. (picture from: Thermal mapping as a valuable tool for road weather forecastand winter road maintenance - An example from the Italian Alps, RSCY 2016) Spatialization physics informatics engineering
  • 14. Signal noise removal • Temperature noisy signal from termal mapping due to different road characteristic → low- pass Gaussian filter to remove this noise ● Semi-automated process by means of “R” statistical packages (www.r-project.org) Data analysis (1) physics statistics
  • 15. characteristic thermal fingerprint and spatialized forecasts Also this stage performed by means of “R” software cold warm Data analysis (2) physics statistics
  • 16. The combination of “single point” METRo forecast with the “thermal map” of the route allows to predict temperature over the entire route at selected times. GIS based elaboration (SHP / KML files which can be overlayed on a map) Mapping informaticsengineering
  • 17. Web page accessible history PHP and HTML coding, graphics generated on the fly using gnuplot program Data publication informatics
  • 18. ● The calculus system of a complex decision support system was successfully developed entirely adopting open source software ● Customization of well established calculus system (METRo) possible thanks to code accessibility ● Exploitation and scalability of the system is limited to the more general part; when integrating a tool in a already existent toolchain you're mostly forced to adapt the new part → the interfaces are really custom and not always reusable. ● The system has been running for nearly two years now from the first implementation ● Integration with existing procedures is very important; the system is modular and therefore maintainable in case of modification of other stages of the toolchain Conclusion