Model “Pulp Friction” - Modelling road surface friction (Practical implementation)
Pilot 1: Model “Pulp Friction” - Modelling road surface
friction (practical implementation)
Overview of the Pilot
Finnish road weather observation network consists of about 520 stations (situation in November 2008). 90 of those stations are new types of optical sensors which give an estimation of prevailing friction on the surface, too. In the road weather warning service, which is operated by FMI and Finnish Road Administration together, the road conditions are divided into three categories: normal, bad and very bad road conditions. There is a link between friction and road conditions: friction above 0.3 means normal road conditions, friction 0.15…0.3 bad road conditions and friction below 0.15 is linked to very bad road conditions (by Yrjö Pilli-Sihvola, Finnish Road Administration, see table 1). Estimated friction data from the road weather stations is not included in the weather warning service system so far, but in the Pulp Friction pilot the usability will be studied.
Purpose of the Pilot
The main purpose of the pilot is to look for a closer relationship between weather and road condition/friction. Also road weather modelling is developed so, that friction is included in the model(s). Friction data is collected from automatic measurements (for example optical sensors and acoustic data). This will give an analysis of the state of the roads. The information can be used by road maintenance personnel, service providers and drivers as end users to improve traffic safety by real-time warnings.
Idea and Motivation
Icy and slippery road conditions may exist on high latitude and altitude regions several months during winter time. The risk for car accidents is much higher in slippery than in dry condition. Road maintenance activities try to ensure good driving conditions for drivers. Two main maintenance activities are salting and ploughing. Salting melts existing ice on the surface and pre-icing prevents wet surface to become icy when road temperature decreases below zero degrees Celsius. Snow on the surface is taken away by doing ploughing operations.
It is known that the state of the road as well as friction can vary dramatically even within short distances. That can cause difficult driving circumstances for car and truck drivers. Good observations and modern road weather forecasts and warnings help drivers to take into account bad driving situations. Nowadays road weather models can determine the state of the road so it would be useful to take into account the value of the friction because there are friction observations available nowadays. Real-time observations can be included in the weather model. With the help of more precise and better road weather forecasts driving is safer and the winter maintenance activities more effective.
Due to the global warming especially wintertime temperatures are going to rise. That creates more moisture and near zero temperatures to the southern and central part of Finland which causes more slippery conditions. It is important to develop new techniques to forecast road weather.
Friction and road weather
Friction is a coefficient which means the grip between the surface and the tyre. The value of friction can vary between 0–1. The closer to 1 the value is, the better the friction and grip are. Respectively, the values closer to 0 mean more slippery situation. The friction on the dry and clean road surface is about 0.8 whereas the friction on the icy road can descend at the worst to 0.1.
The results of the friction studies are planned to give better information on the prevailing and forecasted road weather. Guidelines of the road maintenance activities are strongly connected to the numerical value of friction. Winter time road weather can be divided into three different classes: normal, bad and very bad road weather.
- During normal road weather traffic flow runs with the conventional winter time speed limit. Some snow or local slipperiness can exist here and there.
- During bad road weather some snowfall is possible and snow can weaken the prevailing visibility. Also, road surface can be slippery because of snowfall or freezing rain. Strong wind can cause more disadvantage. Risk for the car accidents is raised compared to the normal road weather.
- During very bad road weather large scale hard snowfall or freezing rain is expected. Also, strong wind can be dangerous. Road maintenance personnel may not have time to handle all the roads. The risk of a car accident is ten times (or even more) higher than in the normal winter weather. Travelling times become longer if the weather is very bad. Situations of very bad road weather covers about 5 % of all the winter days.
In Finland there are guidelines for the relationship between friction and road weather (defined by Yrjö Pilli-Sihvola, Finnish Road Administration):
- Friction > 0.3 Normal road weather
- Friction 0.15 – 0.3 Bad road weather
- Friction < 0.15 Very bad road weather
In Finland the guidelines for the quality requirements of the winter road surface are partly based on the friction values. Finnish Road Administration has set limits for the road surface friction and those limits may not go below without penalty. Limits are checked by tests. Nowadays there are some road weather stations installed by friction measurement device, but there is no technique available to forecast the value of friction.
The Challenge for Innovation
Friction is a pretty complicated parameter to handle. For example different kinds of methods to observe friction can give different values for friction in the same situation. In the pilot the definitions for the friction must be done. Friction included in the road weather model is probably a new innovation itself.
Available Data Sources
FMI, Klimator and Foreca (at least) have their own road weather models in use. Also, some free road weather models are available (e.g. MeTRO model). Some of those models can be developed to take into account friction. Also, some other friction models can be developed during this project. The model can be totally separate from the existing road weather models or it can be somehow connected or linked to the existing models.
Friction measurements are available from last years. For example Finnish Road Administration has installed Vaisala’s optical road weather stations (Vaisala DSC 111) which define also friction. Those measurements are available for ROADIDEA project and can be compared to the prevailing weather situation. Those observations may give lots of information when developing the friction model.
Also, some other friction measurements can be used if such observations are available. For example VTT has done friction research during last years.
Necessary Local Partners
Friction measurement data is needed as well as weather and road weather observations. The project has permission to use the road weather observations gathered from the Finnish road network (including also the friction measurements from here and there collected during the past 2 years). The owner of the road weather observations in Finland is Finnish Road Administration.
Necessary ROADIDEA Partners
FMI and Klimator have experience about road weather modelling and they have their own road weather models so those two partners are the leaders of the “Pulp Friction” research. Also, especially VTT has knowledge about the friction research so their experience is needed.
Data Needs of the Pilot
The needed input data is road weather observations (including friction observations) and road weather models inputs and outputs. FMI’s road weather model is an operative product already, so it will not need any new inputs. Road weather classification indexes for last winter are compared to the prevailing friction value and the connection between those values will be studied. The road weather classification index data for previous winters is stored in FMI.
All input data is available at FMI already so probably there is no need to get any input data from the ROADIDEA platform.
Data Input from the Pilot
The Pulp Friction pilot will provide friction analysis and forecasts to the ROADIDEA platform. Also, road weather classification index based on the friction can be delivered to the platform. The data includes single values and the position (coordinates) information. Output from FMI to the platform will be friction values and road weather classification (normal, bad or very bad road weather).
The data from FMI is transferred to the platform using e.g. ftp. The values are produced in a certain format (e.g. xml format). Destia, as a manager of the platform, takes care of the visualisation of the data.
Next Steps and Outlook
The planning of the works and schedule must be done together with FMI and Klimator which are the leading partners in this pilot. Next steps should be:
- Setting up of a local team consisting of ROADIDEA members and local partners and pilot kick-off
- Collection and Analysis of identified data sources with FMI and Klimator
- Clarification of conditions for the receipt of data
- Further conceptual ideas on the model and the modelling concept
- Gather information from scientific articles considering friction and/or road weather
- Identification of the need for further research into the process.
Estimated Pilot Schedule
The aim is to start the pilot during Q1 of the year 2009.
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PLEASE NOTE!
Pilot Site Questionnaire
Introduction
This questionnaire is part of WP6 (Creation of pilot services) of ROADIDEA project. The purpose of the survey is to gather information that will be necessary when planning and implementing the pilots. The questionnaire is sent to the responsible people of the four pilot sites. The answers will be exploited already in the deliverable D6.1 Pilot specifications as well as in the latter work phases of WP6.
Please send the filled questionnaires to hanne.lindqvist@destia.fi by 7th of November.
Basic Information
Pilot name:
Name(s) and contact information of the person(s) completing the questionnaire:
Questions
Question 1. Please write up a concise description of the pilot you are leading. The description should include at least the following aspects: data needs of the pilot, input process, outcome of the pilot. Please describe also the use case of the pilot - e.g. in what kind of end user service the pilot can be used.
Question 2. What kind of data (if any) is needed from the ROADIDEA platform to implement the pilot?
Question 3. What kind of data (if any) does the pilot provide for the ROADIDEA platform? (Static or dynamic, attach an example if available)
Question 4. What is the communication protocol used in the pilot when communicating with the ROADIDEA platform? Please provide an example scheme and data sample if possible.
Question 5. Does the pilot require some components that should be installed in the ROADIDEA platform? If yes, please describe these components in detail.
Question 6. Please describe the outcome of the pilot in two levels: a) what is the expected data output of the pilot and b) what the use description of the pilot is.