Winter Maintenance Activities Research Articles

Nonlinear modelling of the association between winter weather severity and maintenance expenditures

The winter weather severity plays a crucial role in determining the resources required for winter maintenance activities. This study utilized nonlinear models to examine the relationship between winter weather variables (temperature, wind speed, and snowfall) and winter maintenance expenditures (labor, material, and equipment) based on data from the state of Illinois. The data were collected and aggregated by year and district to align with the expenditure data, and the state was divided into three climatic zones, with separate models developed for each. The ROUT method was employed to identify and eliminate outliers before conducting nonlinear modelling. The best-fitting model was selected using cross-validation and R2 evaluation. The results demonstrate that the chosen nonlinear models effectively depict the connection between winter weather and winter maintenance expenses. These findings can aid agencies in efficiently allocating resources for winter maintenance.

Impact of deicing salts on pervious concrete pavement

Two pervious concrete projects (named as SR28 and SR431), with the same mixture design but different winter maintenance activities, were included in this research. Both projects are located in the Lake Tahoe area, Nevada, United States. Testing results indicated that the mechanical properties were significantly higher in SR28 cored samples than the ones in SR431. It was found that the SR28 pieces have fewer air voids, while the SR431 samples have higher water absorption and hydraulic conductivity, and the SR28 samples show fare better performance against repeated freezing and thawing cycles than the SR431 ones. scanning electron microscope pictures of crack surfaces in cores taken from SR28 indicate that the cement binder phase has been largely retained. However, in the coring sample of SR431, needle-shaped residues can be seen within the cement binder phase and an abundance of precipitated micro-sized crystalized particles can be observed. On a micrometer scale, the μCT examination reveals that the porosity of SR28 samples is significantly less than that of SR431. The analyzing results give a clue to demonstrate the durability of pervious concrete pavement can be attributed to the construction quality control, maintenance activity, or the weather and locations of the field sites.

Urban resilience to extreme weather - Sub-seasonal and seasonal forecasts for winter maintenance activities in Helsinki

Urban resilience to extreme weather - Sub-seasonal and seasonal forecasts for winter maintenance activities in Helsinki

Impact of Weather on Pedestrians’ Slip Risk

Pedestrians’ slipping injuries are a very typical problem in the Nordic countries, causing varying degrees of injuries and in the worst case, long sick leaves. There is a clear seasonal variation in the number of slips. Sidewalk slipperiness and the risk of slips is a complex combination of weather, winter maintenance activities, number of walkers, and the grip between shoes and surface, as well as human behavioral and physical factors. In this study, the effect of weather on pedestrians’ slipping injuries is studied. Daily weather observations are compared to the slip statistics that have been collected from commuting accident statistics in cases where the way of commuting has been walking. A total of 16 cities from Finland for 14 winters are included in this study. The results reveal that snow on the ground increases the slip risk more than three times compared to no-snow situations. Near zero temperatures and precipitation are very typical on days when slip injuries occur more than usual. However, there are also days when high amounts of slips cannot be explained with the weather. The study also shows that there are significant differences as to the number and timing of slips between different parts of the country.

Use of Simulation Tools for Optimization of the Time Duration of Winter Maintenance Activities at Airports

Aviation and climate change are often associated. The effects of climate change have increasing impact on the safe operation of airports. Due to both climate and weather conditions changes, airport winter maintenance is a significantly important activity of airports, especially in areas where a harsh winter season is expected. Continuous optimization of airport winter maintenance processes is necessary. The aim of this article is to present a possible way to optimize maintenance processes using simulation tools. The team of researchers identified key factors that are necessary for the application of the optimization. The article presents a procedure designed for safe handling of one of the model situations in winter maintenance of airports. The model of simulation defines critical points in the maintenance procedures designed for maintenance optimization using the data obtained from an international airport. Based on the determination of critical points of the maintenance procedures processed using a Gantt chart, the authors analyzed the differences of the performed procedures applied in the airport. The result of applied research is the identification of the next critical points in the simulation that may potentially represent critical activities of the winter maintenance procedure and have an influence on their optimization.

Snowplow Truck Performance Assessment and Feature Importance Analysis Using Machine-Learning Techniques

Snowplow trucks serve a crucial role in winter maintenance activities by removing, loading, and disposing of snow. A performance-monitoring and analysis process can assist transportation agencies in effectively managing snowplow trucks and maintaining the normal functioning of roadways. Previous literature suggests that most snowplow truck performance analysis is done through life-cycle cost assessment at the macro level to determine the optimal life cycle for the entire truck fleet. However, this can lead to a waste of resources and may incur bias due to ignorance of performance variations resulting from endogenous and exogenous features. More important, such analysis fails to identify the factors that contribute to performance deterioration. With the proliferation of operational data on snowplow operations, these concerns can be addressed through predictive machine-learning (ML) techniques in a data-driven fashion. In this study, we applied a popular ML technique, random forest (RF), to predict the performance of snowplow trucks, which was quantified via the rank of major repair times. Another ML technique, linear support vector machine (SVM), was also applied for benchmarking and comparison. Using the snowplow truck fleet managed by the Utah Department of Transportation (UDOT), both models were implemented and it was demonstrated that RF outperforms linear SVM with regard to prediction accuracy. Further, a feature importance analysis from the RF model can help transportation agencies to improve truck replacement strategies by identifying crucial performance factors. Lastly, a sample application of the developed prediction model using RF suggests the threshold of work intensity for preventing the rapid deterioration of truck performance in various working environments. Compared with the life-cycle cost analyses used in previous studies, the prediction model proposed here can help transportation agencies to better prioritize fleet replacement.

Maintenance Facility Location Optimization Review

State departments of transportation (DOTs) are responsible for operating and maintaining the highway system in a safe and efficient manner to facilitate the movement of people and goods. Maintenance facilities play a critical role in the operations of DOTs by storing equipment and materials, providing a base of operation for department of transportation personnel, and serving as the beginning and ending location for maintenance activities. Maintenance activities occur year-round, but winter maintenance activities are typically the most time and resource intensive for northern state DOTs. Maintenance operations generally consist of facilities, routes, and equipment. The life spans of maintenance facilities are typically measured in decades, which compounds any inefficiencies in their locations over a long time horizon. Less research has been conducted to optimize facility locations than routes and fleets. This paper reviews the available literature related to facility optimization, including maintenance facilities and non-maintenance facilities. Several specific takeaways were documented from the research reviewed. DOTs have conducted research to optimize the locations of their facilities. These works have typically examined a small area and included only a few facilities. The larger-scale optimizations only located facilities at the town level. A second level of facilities may be necessary to improve the cost effectiveness of the optimization. Such facilities could include material storage depots strategically placed between maintenance sections to reduce the amount of deadheading. At a certain point, further consolidation of maintenance facilities will increase the overall costs because more vehicles and staff are required to reach the further extents of maintenance areas.

Using Genetic Algorithm For Winter Maintenance Operations: Multi Depot K-Chinese Postman Problem

In this study, the assignment and routing problem of one of Istanbul’s winter maintenance activities, salt pouring, was scrutinized. The starting point of the study considers the high cost of winter maintenance work, a shrinking assigned budget, high numbers of vehicles and streets to service that the increase in difficulty to solve the problem due to their high numbers. In this respect, the problem was modeled as multi depot k-Chinese postman problem, a type of arc routing problem. This mathematical model was solved by genetic algorithm. For comparison, the current solution, Clarke and Wright Algorithm and Sweep Algorithm were used.

Evaluation of Management Alternatives for Truck Wash Water Generated During Winter Maintenance Activities

The purpose of this research was to identify alternative strategies for managing wash water generated during routine washing of salt trucks at Ohio Department of Transportation (ODOT) maintenance facilities lacking access to sanitary sewer and to assess their costs. Eighteen potential management strategies were identified and evaluated. Six of these strategies were included in a detailed cost analysis, which indicated that site-specific conditions directly affect the cost of alternative management strategies and that tying a facility into the sanitary sewer is not always the most cost-effective strategy. For a county maintenance facility with 12 trucks and 30 winter events, tying into the sanitary sewer was the most cost-effective strategy when the capital cost was less than US$173,640; however, when the capital cost was greater than US$285,333, four of the five alternative strategies identified were more cost-effective than tying into the sanitary sewer.

Speed Levels of Heavy Vehicles on Norwegian Mountain Pass

This paper presents results from a study of how speed varies among vehicle categories under variable winter conditions and how incline affects traffic flow. The study was divided into two parts. The first part was a case study with observations of traffic behavior influenced by weather events. The case study formed the basis for hypotheses about how winter conditions could influence speed. The second part of the study tested some of these hypotheses through information about traffic, climate, friction, and winter maintenance activities over 2 to 4 years. The study found that speeds in all vehicle categories decreased when the coefficient of friction fell below 0.30. If snow was falling as well, the speed decreased further. For trucks, it appeared that snow, in conjunction with a corresponding reduction in visibility and poor driving conditions, reduced speed substantially. On a straight stretch with no incline, there was less difference in speed levels among vehicle categories, and load seemed to have little or no effect at all on speed. Concern arose that the speed level did not decrease more when the coefficient of friction fell below 0.3. This finding indicated that drivers of both passenger cars and trucks drove with elevated risk when the friction was reduced. When it was snowing, it seemed that drivers adapted better to driving conditions.

Prediction of Salt on Road Surface

The competing goals of safety, accessibility, and environmental protection, together with limited funding, increase the need for cost-effective use of resources in the pursuit of winter maintenance activities. One way to minimize the amount of salt used in winter maintenance is to predict better the amount of residual salt on a road surface. This paper combines an empirical model developed in Sweden with data on residual salt, road surface wetness, and traffic from 18 Danish field case studies. The resulting model is presented as a mathematical function and in a graph. Decision makers might use such a model as a tool for understanding the durability of a dose of salt under various conditions (e.g., traffic, road surface wetness) and therefore minimize the amount of salt needed. The results of this study showed that the decay of residual salt could be modeled with traffic as an independent variable with a fair to quite good fit. Road surface wetness, as shown from the wheel tracks, related positively to the rate of residual salt loss. The wetter the surface, the faster the salt left the wheel tracks. On a wet road surface, the salt in the wheel tracks was almost gone after only a couple of hundred vehicles had traveled across the surface, whereas on a moist road surface, it would take a couple of thousand vehicles to reach the same result.

Benefit-Cost Analysis of Weather Information for Winter Maintenance

Surface transportation in the United States is continuously affected by adverse weather conditions, which contribute to thousands of highway fatalities and billions of dollars in economic loss every year. Winter weather has its own peculiar challenges, to which transportation agencies respond through winter maintenance operations. Recent trends toward proactive winter maintenance operations have placed a premium on the value of timely and accurate weather information that reflects current and forecast conditions in the roadway environment. However, few studies have sought to quantify this value and compare it to the costs of obtaining such customized weather information. The Utah Department of Transportation (DOT) implemented a weather operations program that assists the agency's operations, maintenance, and construction functions by providing detailed, often customized, area-specific weather forecasts. This program's genesis provides a useful case study to quantify the cost-effectiveness of weather information. Described is the application of an artificial neural network model using winter maintenance cost data from dozens of Utah DOT maintenance sheds for the 2004 to 2005 winter to estimate the cost-effectiveness of this program. The model estimated the value and additional saving potential of the Utah DOT weather service to be 11% to 25% and 4% to 10% of the Utah DOT labor and materials cost for winter maintenance, respectively. On the basis of the program's cost, the benefit-cost ratio was calculated at over 11:1. The results highlight the potential benefits that may be realized by an agency using improved weather information to direct its winter maintenance activities.

Pilot Study of Speed-Recovery Duration as a Measure of Winter Maintenance Performance

Many state and local governments in the United States are seeking improved methods of providing winter highway maintenance to meet the increasing demands of today's drivers. Winter maintenance activity can improve road conditions for travel in terms of mobility, safety, and economic benefit. The benefits and costs of winter maintenance make it very important that these activities be completed effectively and efficiently. To improve the effectiveness and the efficiency of winter maintenance activities, the performance of the approach taken must be measured. Winter maintenance performance measures were developed on the basis of speed data from automatic traffic recorders (ATRs) and winter storm report data. An attempt was made to combine the ATR speed data and the storm report data to determine both the average vehicle speed reduction during a snow event relative to normal vehicle speeds at a location and the time needed from the minimum value to regain normal or average vehicle speeds. A determination was made related to whether this speed-recovery duration might be an appropriate performance measure for winter maintenance.

Methods for Measuring and Reporting Winter Maintenance Activities

The Winter Friction Project in Norway deals with practical, technical, and economic problems that arise in providing good friction conditions on winter roads. The project started in 1997, and the final report is scheduled for 2002. A main activity throughout the project period is to carry out field studies. The field studies consist of a testing program (scientific studies), to document performance of different friction improvement methods, and a follow-up study on roads in 10 counties, to document existing winter maintenance practice on both salted and sanded roads. The project has a need for measuring and reporting winter maintenance activities and winter standards in connection with scientific studies and as a part of the follow-up study. A system has been developed to evaluate the effects of different actions. The difference in standard achieved between salted and sanded roads is clear and is reflected in the number of measures and the friction standard. The results so far show that there is a difference in practice, which can be explained in part by different climatic and traffic conditions. But the results also show that there are differences in practice where the outer conditions are similar. This indicates that there is a potential for improvement, and changes will be made in view of the results from the scientific study.

Anti-Icing Operations with Prewetted Fine-Graded Salt

The Kansas Department of Transportation and the Wisconsin Department of Transportation in cooperation with the Brown and Columbia County Highway Departments conducted a 2-year study of various gradations of road salt used during winter storm events in an anti-icing application. The objectives of the study were to document the advantages of two finer gradations of prewetted salt used during anti-icing operations and to evaluate the ability of current salt spreader equipment to distribute various gradations of salt. The four-task study consisted of laboratory and field testing of various prewetting rates for the different gradations of salt, field observations and documentation of actual winter maintenance activities, analysis of data collected during actual storm events, and reporting of results. Results and conclusions from the 2 years of data collection were limited because only a minimal number of storm events could be documented. The finer gradation of salt did produce a faster salt brine reaction on the pavement, but it did not last as long as the standard gradation of salt, which resulted in more frequent reapplication of the finer gradation of salt.