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Relationships Between Road Slipperiness, Traffic Accident Risk and Winter Road Maintenance Activity

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Relationships Between Road Slipperiness, Traffic Accident Risk and Winter Road Maintenance Activity CLIMATE RESEARCH Vol. 15: 185–193, 2000 Published September 5 Clim Res Relationships between road slipperiness, traffic accident risk and winter road maintenance activity Jonas Norrman*, Marie Eriksson, Sven Lindqvist Lab. of Climatology, Physical Geography, Dept. of Earth Sciences, Göteborg University, Box 460, 405 30 Göteborg, Sweden ABSTRACT: A method for deriving quantitative relationships between road slipperiness, traffic acci- dent risk and winter road maintenance (WRM) activity is described. The method is also applied to data from an area in southern Sweden. If a specific type of road slipperiness represents a large acci- dent risk despite high WRM activity it is important to increase public awareness during such periods. If the type of slipperiness represents a large accident risk but is accompanied by low WRM activity, it is also important to increase the WRM to reduce the accident risk. In the method, a road slipperiness classification, based on atmospheric processes, is used to classify the road conditions at the time an accident occurred. The road condition is classified either as non-slippery or as one out of 10 types of slipperiness. Data for the slipperiness classification are taken from the Swedish Road Weather Infor- mation System (RWIS). Results from this study show that the traffic accident risk was different for dif- ferent types of road slipperiness. Highest accident risk was associated with road slipperiness due to rain or sleet on a frozen road surface. When accidents occurred in these situations, there was always high WRM activity. This indicates that, in order to reduce the accident rate during these situations, public awareness must be increased by providing information to drivers. The study also demonstrates the benefits of applying a standardized road slipperiness classification to all kinds of sources of road safety information, such as a RWIS, traffic accident reports and WRM reports. With a standardized and objective classification of the road conditions and digitally stored data, all evaluations are easily conducted. KEY WORDS: Road slipperiness · Traffic accidents · Winter road maintenance Resale or republication not permitted without written consent of the publisher 1. INTRODUCTION To detect slippery road conditions, WRM personnel use information from a Road Weather Information Sys- Studies show that there is often a relationship be- tem (RWIS). The Swedish RWIS has more than 600 tween slippery road conditions and traffic accidents, roadside stations equipped with sensors measuring even in areas where winter road maintenance (WRM) several meteorological variables. The large number of is performed (Schandersson 1988, Sävenhed 1995, stations, taking measurements twice an hour, produce Andreescu & Frost 1998). For example, in Finland information with both high temporal and high spatial about 25% of all fatal accidents occur on icy or snowy resolution. road surfaces (Kulmala & Rämä 1995). This is of seri- When slippery road conditions are forecasted, or ous concern, as improving slippery road conditions in have developed, proper maintenance action is taken, order to reduce the number of traffic accidents is the i.e. ploughing, gritting or both. However, even if the main objective for WRM personnel. WRM organization is alerted and out working, it will take some time before the entire area is cleared. Dur- ing this initial period there is a high risk for accidents *E-mail: [email protected] to occur. For example, when snow first starts falling, © Inter-Research 2000 186 Clim Res 15: 185–193, 2000 more accidents happen, but after a while the rate sta- When supplying drivers in Finland with information on bilizes as people get used to the new road conditions road slipperiness it was shown that the average speed (Öberg 1993, Sävenhed 1995). is reduced if warning signs are used (Kulmala & Rämä The accident risk is also a function of the public 1995). In Sweden, no organized warning system is awareness of the problem. Studies have shown that functional today but there are plans to develop a sys- drivers are not good at adjusting the speed of their tem. It is therefore important to investigate during vehicle to the prevailing road conditions, even if the which type of road conditions it is necessary to provide hazard is clearly visible (Öberg 1991, Wallman 1997). information to the driver to reduce the accident rate. Wintertime road conditions also vary between areas In order to know how to improve traffic safety it must and change with time. Johansson (1997) showed that be possible to derive quantitative relationships be- the traffic accident rate during hazardous situations is tween WRM and traffic accident risk. A problem when higher in southern Sweden, where slipperiness on quantifying such relationships is the comparison of the roads is more rare, than in Northern Sweden, where different types of slipperiness that may develop; main- people are used to driving in winter road conditions. It tenance procedures are different for each type. The is important for WRM personnel to know which type of possibility for drivers to detect hazardous road condi- road slipperiness has the highest accident risk in their tions also varies between types. For deriving quantita- area. tive relationships between road slipperiness, traffic Previous studies of relationships between road slip- accident risk and WRM activity it is necessary to dis- periness and risk of traffic accidents have used the stan- tinguish between the different types. dard road condition description in police reports (Frid- This study presents a method for deriving quantita- strøm et al. 1995, Sävenhed 1995, Johansson 1997, tive relationships between road slipperiness, traffic Edwards 1999). There are, however, many other types accident risks and WRM activity in an area where of road slipperiness than the standard descriptions used WRM is performed to increase road safety. The method in police reports. Andreescu & Frost (1998) used linear is applied to data from a region in southern Sweden. regression to explain the relationship between traffic An expert system developed by Norrman (1999) is accidents, snowfall, rain and mean temperature. There used to classify road conditions automatically at the is a chance, though, that the conditions at the meteoro- time of an accident as either ‘not slippery’ or as one out logical station are not the same as at the location of the of 10 different types of slipperiness (Table 1). The clas- accident. If possible, it is therefore better to use high- sification is based on high-resolution meteorological resolution meteorological data such as the RWIS, since data from RWIS stations located no further than 25 km the road surface conditions may vary over short dis- from the location of an accident. The slipperiness clas- tances (Andrey & Olley 1990, Gustavsson 1995). sification is further described in Section 2. If a relationship between traffic accidents and road The classified RWIS observations are then used to slipperiness can be established, the WRM can be com- describe the road surface status at the time of a traffic plimented with other measures to decrease the acci- accident. By using the slipperiness classification it is dent risk. For example, information about prevailing possible to categorize both WRM and traffic accidents road conditions can be used in order to increase public by the type of road slipperiness. awareness of the situation or to decrease the speed limit The present study also demonstrates the benefits of in the area according to the prevailing road condition. applying a standardized road slipperiness classifica- Table 1. The 10 different types of slipperiness on roads used in the study and the variables neccessary for expert system classifi- cation. The presence of precipitation is noted as either ‘yes’ or ‘no’. P: precipitation; Tair, Troad, Tdew: air, road and dewpoint temperatures; Rh: relative humidity; U: wind speed Type of slipperiness Precipitation Variables (1) Precipitation (rain/sleet) on a frozen road surface Yes P, Tair, Troad (2) Precipitation (snow) on a frozen road surface Yes P, Tair, Troad (3) Precipitation (snow/sleet) on a warm road surface Yes P, Tair, Troad (4) Snowfall together with hoarfrost Yes P, Tair, Troad, Tdew (5) Hoarfrost and low visibility No Troad, Tdew, Rh (6) Freezing dew followed by hoarfrost No Troad, Tdew (7) Strong formation of hoarfrost No Troad, Tdew, Rh, U (8) Weak formation of hoarfrost No Troad, Tdew Rh, U (9) Drifting snow Yes P, Tair, Rh, U (10) Watercover which freezes Yes P, Tair, Tdew, Troad, Rh Norrman et al.: Slipperiness, accidents and winter road maintenance 187 tion to all kinds of road safety information, such as tant to emphasize that the classification is based on the meteorological data, traffic accident reports and WRM variables available in the RWIS. An example of a prob- reports. At present, only the descriptions of road condi- lematic road condition that is not possible to detect by tions in the accident reports are standardized. The the RWIS is residual snow from an earlier snowfall on WRM reports used were hard to acquire and analyze the road. as they are archived on paper by each individual WRM Six of the types of slipperiness in Table 1 are due to contractor. Due to these data restrictions RWIS data precipitation and the other 4 are due to sublimation. and traffic accident data from 3 winters, 1991-92, 1993- These 2 atmospheric processes are responsible for the 94 and 1995-96 (a total of 246 accidents), and WRM transportation of water to the road surface. Frozen data from 2 winters, 1993-94 and 1995-96, were used. water is crucial, as it is the medium which reduces road friction to such a degree that the condition can be clas- sified as slippery. If all the criteria for a certain type of 2. DATA AND METHODS slipperiness are fulfilled it means that there is meteoro- logical potential for slipperiness on the road or that The WRM personnel need information about the it will become slippery.
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