Before-and-After Empirical Bayes Evaluation of Achieving Bare Pavement using Anti-Icing on Urban Roads

Author(s):  
Maged Gouda ◽  
Karim El-Basyouny

Canadian municipalities are increasingly choosing to achieve bare pavement (BP) for snow and ice control during fall/winter seasons. When a snowstorm event is forecasted, one strategy is to apply anti-icing chemicals to the pavement surface to prevent the snow and ice from forming a bond with the road surface. Such an approach facilitates a more efficient plowing operation and reduces the amount of deicing chemicals needed to achieve BP. This study assesses the safety performance of achieving BP using anti-icing compared with the traditional reactive winter road maintenance (WRM) approach on urban roads using the before-and-after Empirical Bayes technique. Results suggest that achieving BP significantly reduces all collision types and severities on midblocks with a reduction value in the range of 13.7% to 19.7%. Attaining BP at intersections was found to be very effective in reducing injury collisions with an estimated reduction of 12.5%. When sites were grouped based on a WRM priority-basis, it was found that anti-icing was effective for reducing the majority of collision types and severities at the different priority levels with reductions ranging from 8.7% to 49.83% on midblocks and between 5.37% and 13% at intersections. All reductions were statistically significant. The monetary benefits of the reductions in property-damage only and nonfatal injury collisions were estimated at 60 million Canadian dollars using a 1.92% interest rate and a 2-year service life. These findings provide unequivocal evidence that achieving BP using anti-icing can lead to significant societal safety benefits that economically translate to huge collision cost savings.

ICTE 2011 ◽  
2011 ◽  
Author(s):  
Chaozhe Jiang ◽  
Jianchen Zheng ◽  
Jiajun Liu ◽  
Lu Wu ◽  
Jin Yang

2017 ◽  
Vol 12 (2) ◽  
pp. 127-134 ◽  
Author(s):  
Tomas Ratkevičius ◽  
Alfredas Laurinavičius

The limited funding for the road industry leads to economizing in the planning of road network maintenance, to identifying the appropriate priorities of the activities with the greatest benefit for the society. The level of maintenance is the direct assessment of the road operation and maintenance service provided to the road users; it directly affects the road maintenance and for road users costs the better is road maintenance, the road users incur the fewerexpenses and vice versa. Insufficient road maintenance in the winter time causes not only the danger of traffic accidents but also worsens the driving conditions, increases the fuel consumption, vehicle depreciation, transportation becomes more expensive. Many results of studies showed that the current choice of maintenance levels in the winter time taking into account only the road category and traffic volume does not ensure the indicators of the most advanced world countries and road functional purpose. The principle of the minimal expenses for the society should be the main criterion in identifying the optimal levels of winter road maintenance. The experience of Lithuania and foreign countries helped in creating the model of assessment of winter maintenance levels for Lithuanian roads of national significance, which can be applied in the other foreign countries as well. This model could be an effective tool for the selection of the optimal maintenance levels, which would economically substantiate the winter road maintenance strategy, that best corresponds to the needs of the society.


2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Xu Wang ◽  
Lian Gu ◽  
Tae J. Kwon ◽  
Tony Z. Qiu

Inclement weather acutely affects road surface and driving conditions and can negatively impact traffic mobility and safety. Highway authorities have long been using road weather information systems (RWISs) to mitigate the risk of adverse weather on traffic. The data gathered, processed, and disseminated by such systems can improve both the safety of the traveling public as well as the effectiveness of winter road maintenance operations. As the road authorities continue to invest in expanding their existing RWIS networks, there is a growing need to determine the optimal deployment strategies for RWISs. To meet such demand, this study presents an innovative geostatistical approach to quantitatively analyze the spatiotemporal variations of the road weather and surface conditions. With help of constructed semivariograms, this study quantifies and examines both the spatial and temporal coverage of RWIS data. A case study of Alberta, which is one of the leaders in Canada in the use of RWISs, was conducted to indicate the reliability and applicability of the method proposed herein. The findings of this research offer insight for constructing a detailed spatiotemporal RWIS database to manage and deploy different types of RWISs, optimize winter road maintenance resources, and provide timely information on inclement road weather conditions for the traveling public.


Author(s):  
Takashi Nakatsuji ◽  
Takashi Fujiwara ◽  
Toru Hagawara ◽  
Yuki Onodera

In Japan, the regulation of studded tires requires the establishment of new countermeasures for effective ice control on slippery roads in winter. The most important information for snow and ice control systems is determining the slipperiness of road surfaces. To detect the slipperiness simply and precisely, a monitoring system was examined in which drivers judged the slipperiness. To evaluate the suitability of such slipperiness data, three investigations were carried out: (a) the relationship between the road condition classification and the slipperiness index, (b) the effectiveness of the subdivision of road classification, and (c) the comparison of slipperiness indexes with the actual friction coefficients. To address the first problem, the road conditions were investigated for 1 month with the cooperation of 10 taxi companies. It was found that the subjective slipperiness index was more sensitive to changes in weather conditions than the road classifications, and that icy roads do not always correspond to slippery roads. That is, there was a limitation on expressing road conditions by road classification. For the second problem, a similar investigation was performed by subdividing the road conditions into more classes. It was concluded that the subdivision of road classification is not so effective in precisely representing the slipperiness of roads. For the third problem, it was clarified that the subjective slipperiness indexes more or less agree with the actual friction coefficients. As for the results, the slipperiness index showed potential for use in snow and ice control systems.


Author(s):  
Andreas Kuehnle ◽  
Wilco Burghout

Sweden spends 1.7 billion Crowns on winter road maintenance annually. A large part of this money goes into plowing, salting, and sanding of the roads. The decision about what maintenance to perform is made, in part, based on data received from road weather information stations, some of which are also equipped with video cameras. These video cameras form an additional unexploited sensor for determining the road condition during winter. Images taken from a handheld roadside video camera are investigated here to see if it is possible to determine the road state (dry, wet, snowy, icy, snowy with tracks) from the video images alone. The system is intended to supplement the other weather station measurements, such as temperature and wind speed, and make better maintenance decisions and quality control of maintenance possible. The results indicate that it is possible to distinguish between all road states except for ice/wet and ice/tracks. Typical class separations are a Mahanalobis distance between 0 and 2. Neural networks with three or four input features, three to five hidden neurons, and a sigmoid-sigmoid-linear architecture are used to classify the road state. Rates of correct classification are typically 40 to 50 percent with these networks. There are useful feature combinations, including purely monochrome features, which do not depend on the network architecture.


Author(s):  
Sen Du ◽  
Michelle Akin ◽  
Dave Bergner ◽  
Gang Xu ◽  
Xianming Shi

Winter road maintenance operations, commonly known as snow/ice control operations, are one of the most critical functions of state, provincial and local transportation agencies in cold regions. These operations aim to provide safety and mobility by timely and effective application of materials and plowing. The most common materials used are salt (sodium chloride, solid and brine), magnesium chloride-based, and calcium chloride-based deicers, agro-based additives and blends, and abrasives. In practice, the specific choice and application method and rate of these materials dependent on temperature, precipitation type, level of service goals, budget, and environmental sustainability. Best practices of material application are designed to apply the right type and amount of materials in the right place at the right time. This review presents the literature review and agency interviews that were conducted to assemble the information about the use of materials, including types of materials, application tactics, application rates, and application equipment.


Geografie ◽  
2009 ◽  
Vol 114 (3) ◽  
pp. 218-229
Author(s):  
David Konečný

The aim of this paper is to present road weather information system and map sources which can be used by winter maintenance system operator to clarify his perception of road meteorological situation in order to be able to take well-founded decision while managing maintenance activities. Presently the so-called status map showing current warnings from road weather stations is the principal map in winter maintenance. In its new version displaying the map of any feature measured by outstations as well as layer handling and zooming will be available. Map outputs of the model forecasting the road condition and temperature are described in the last chapter.


2012 ◽  
Vol 29 (6) ◽  
pp. 846-856 ◽  
Author(s):  
Patrik Jonsson ◽  
Mats Riehm

Abstract There is significant interest among road authorities in measuring pavement conditions to perform appropriate winter road maintenance. The most common monitoring methods are based on pavement-mounted sensors. This study’s hypothesis is that the temperature distribution in a pavement can be measured by means of a nonintrusive method to retrieve the topmost pavement temperature values. By utilizing the latest infrared (IR) technology, it is possible to retrieve additional information concerning both road temperatures and road conditions. The authors discovered that surface temperature readings from IR sensors are more reliable than data retrieved from traditional surface-mounted sensors during wet, snowy, or icy road conditions. It was also possible to detect changes in the road condition by examining how the temperatures in wheel tracks and in between the wheel tracks differ from a reference dry road condition. The conclusion was that nonintrusive measurement of the road temperature is able to provide an increase in relation to the knowledge about both the road temperature and the road condition. Another conclusion was that the surface temperature should not be considered as being equal to the ground temperatures retrieved from traditional surface-mounted sensors except under conditions of dry, stable roadways.


Safety ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 17
Author(s):  
Aleksander Pedersen ◽  
Tanita F. Brustad

Road conditions during the winter months in Nordic countries can be highly unstable. Slippery roads combined with heavy haul traffic and ordinary road users can create dangerous, even lethal, situations if road maintenance is unsuccessful. Accidents and critical road conditions may lead to blocked roads, putting strain on a limited number of main roads in many regions, and may in the worst case isolate areas entirely. Using sensors in winter road assessment has been a popular topic for over 20 years. However, with today’s developments connected to smaller and cheaper sensors, new opportunities are presenting themselves. In this study, we performed preliminary experiments on a variety of sensors, both commercial and experimental, to evaluate their benefits in possible hybrid sensor technology, which can give a more complete characterization of the road surface than what is possible from just one sensor. From the collected data and visual analysis of the results, the idea of a hybrid sensor seems promising when considering the differences in the tested sensors and how they may complement each other.


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