Winter Road Maintenance Operations Research Articles

Weather event characterization: a catalyst for improved spatial mapping and benefit quantification in winter road maintenance

Monitoring winter road surface conditions (RSC) is essential for optimizing winter road maintenance operations and ensuring public traffic safety and mobility. However, many existing RSC estimation methods focus primarily on local or site-specific conditions, thus lacking effectiveness in comprehensive spatial mapping under varying winter weather events. Additionally, the potential financial benefits these methods could provide to maintenance authorities remain largely unexplored. This study addresses these gaps by introducing a refined methodology that harnesses the K-Means algorithm to characterize various weather events – a significant stride towards improving the generalizability and accuracy of road surface temperature (RST) estimations. The study also incorporates regression kriging (RK), a renowned geostatistical technique, as an integral component of a system for constructing an extensive spatial map of RSC across large highway networks. This strategy maximizes the use of data from existing road weather information systems (RWIS) to bridge their large spatial gaps. This study further quantifies the potential savings derived from optimally placing RWIS stations and reducing traffic collisions. The efficacy of these methods is validated through a real-world case study on two major interstate highways in Iowa, US, with RST estimation discrepancies as low as 0.619 °C. The findings also indicate potential cost savings by conserving up to 10 RWIS stations, which can be further translated into monetary savings of RWIS capital costs, traffic collisions prevention, enhanced traffic mobility and savings in maintenance material usage.

Development of an Autonomous Measurement System for Estimation of Snow Profile on Road Surfaces

This paper presents the development of a novel prototype system to measure the profile of snow and detect ice on road surfaces. While researchers have previously developed methods to estimate the tire-road friction coefficient, methods to create a high resolution map of snow cover and ice on roads have not been developed. The prototype and data processing methods presented in this study provide a potential solution that would greatly benefit winter road maintenance teams. Having a device capable of creating a detailed map of snow and ice cover on roads would allow for more efficient plowing and salt deployment, better informing of the public about current road conditions, as well as better analysis of current plowing techniques to improve winter road maintenance operations. The measurement of the snow profile is based on the use of two types of inexpensive ranging sensors mounted on a rotationally controlled stepper motor platform. The technical challenges addressed in the development include analysis of the scan path over which the system scans the road, differentiation between asphalt, concrete, and snow surfaces using reflection amplitudes, accurate transformation of raw distance measurements to inertial coordinates, and identification of the Euler angles of the sensors using parameters associated with the scanned surface profile. Extensive experimental results and test data are presented, which show that the system is capable of measuring the snow profile on a road with an accuracy of ±1 cm when a reasonable portion of bare road is visible, and ±2 cm when only small portions of bare road are visible.

Development of method for anti-icing materials consumption optimization during winter road maintenance

The object of research is the processes of managing the consumption of anti-icing materials during the winter maintenance of highways. The main hypothesis of the research is the application of mathematical modelling methods to optimize the consumption of anti-icing materials. The study considered the factors that affect the use of both individual types and anti-icing materials as a whole. It was determined that the temperature of the road surface and the selected winter maintenance strategy taking into account the level of service (LOS) are significant factors. A mathematical model of material consumption optimization based on the binary numbering system is proposed. Additional limitations to the model have been established: compliance with the criteria of reliability, preservation of assets, road safety, compliance with user expectations (social factor), environmental friendliness, efficiency of the use of materials. An algorithm for the application of the method of optimizing the consumption of anti-icing materials during the winter maintenance of highways has been developed. It was determined that the developed method solves the main problem of minimizing the costs of anti-icing materials, taking into account the requirements of the level of service, the chosen strategy, the temperature of the road surface and the criteria of impact on winter maintenance. It is proposed to implement the calculation according to this method using the built-in «Parameter selection» function in the Microsoft Excel license environment (USA). The results obtained by the optimization method, based on real data, showed the possibility of saving materials by about 23 %, which confirms the effectiveness of the proposed solutions. The results of calculations based on the method of optimization of material consumption have practical value and can be used to make management decisions regarding the justification of winter road maintenance operations. The proposed method can be used both for the cost planning phase and in the case of analysis in the post-implementation period. This is an important aspect in the conditions of financial and resource uncertainty, including those related to circumstances of force majeure, in particular, martial law in Ukraine.

Advanced thermal and rheological characterization of a sustainable anti-icing hydrogel for winter road maintenance operations

As a part of the advancements in the winter road maintenance, a sustainable anti-icing hydrogel has been recently developed for the treatment of the open-graded asphalt pavements. It is obtained by mixing water, a chemical agent and a phyto-based additive (seaweed fiber powder) having thickening and gelling properties. The product has the ability to form a gel-like structure when hot-sprayed on a cold pavement surface. The influence of the interaction between the solutes, i.e. sodium chloride (marine salt) and seaweed fiber, on the gel behavior was evaluated through a laboratory scale study, based on thermal (differential scanning calorimetry) and rheological (rotational and oscillatory tests) analyses. The research findings offer a substantial support for the definition of most suitable recipe and the configuration of the spray application system. The results revealed that the formulation of the anti-icing hydrogel is predominantly governed by the salt concentration, which establishes the freezing point depression capacity. Once the salt dosage is defined on the basis of the climatic condition and the accepted level of service, the gellant content, which controls the gelation mechanism, can be optimized to obtain a sprayable gel with a sufficient stiffness and strength.

An evaluation of temporal changes in physicochemical properties of gully pot sediments

Diffuse pollution is recognised as a major challenge in achieving EU Water Framework Directive compliance, with urban runoff being a key pathway connecting various sources to receiving waters. Gully pots, as one of the ubiquitous urban drainage infrastructures, are placed at the inlets of piped drainage pipe network and actively drain runoff from urban catchment with suspended solids proportionally retained. The physiochemical properties of these retained solids reflect the activities within the catchment during the accumulation period. In this work, seven gully pots in two catchment types (highway and housing) in Luleå, Sweden were fully emptied and sediments analysed for total mass, particle size distribution and selected metal concentrations by six size fractions. The results of this sampling campaign are compared with the results of a 2005 study of the same gully pots to identify changes in the physicochemical properties of sediments over time and examine whether changes identified can be linked to changes in wider catchment management practices. The results highlight the potential impacts of winter road maintenance operations (e.g. up to a 15-fold higher solids loading rate in road catchment gully pots), reaching a normalised solids accumulation rate of 0.176–0.819 kg m2 year−1. An increase in tyre and road wear associated with winter road maintenance operations is also understood to contribute to the temporal increase of several metals including Cu, Zn, Co, Cr and V in the < 63-µm solids fraction in the road catchment gully pots. The concentrations of As and Pb decrease in all size fractions in both catchments, with the implementation of unleaded fuels (for Pb in housing catchment only), End-of-Life Vehicle Directive (Directive 2000/53/EC) (for Pb in both catchments), and strengthened industrial emission reduction measures suggested as possible drivers. The high contamination load for Zn, Cu, Cd and Pb in < 63-µm sediments from low-traffic housing catchment also emphasised the necessity of tracing and restricting non-traffic-related metal sources. Further seasonal monitoring of gully pot sediments is recommended to fully follow up the development of metals loading in both catchments.

Optimization Models for Snowplow Routes and Depot Locations: A Real-World Implementation

This study developed a series of strategies to reassess the service level of winter road maintenance (WRM) operations on the road network in Perth County, Ontario, Canada. These strategies include rearranging plow routes by sharing the material storage yards and optimizing their numbers and locations while considering operational and legislative constraints such as total circuit time, operating speeds, and the number of available trucks. A methodological framework was then formulated and solved by tackling four practical, yet challenging, tasks in a sequential manner. The first task was to identify existing plow routes and construct a detailed GIS database that was later used for benchmarking the current WRM operations. The second task involved the optimization of existing plow routes, while the third task focused on the optimization of plow routes and depot locations by amalgamating WRM operations of different municipalities within Perth County. The final task was to conduct a clean slate optimization to see the benefits of combining depots and route sharing. The optimization models developed were implemented to transform the existing maintenance operations networks to an optimized, integrated, and unified network of routes, with improved land use utilization for road maintenance yards. The framework then captured the impact of the service order of maintenance routes and arranged routing priority efficiently using the tabu search algorithm. The findings also revealed that, by sharing depots, the county could retire three depots and eight trucks while still meeting legislative requirements, thereby suggesting the potential for substantial monetary savings.

The development of climate services to inform decisions about winter maintenance at different timescales

Snow and ice control programs are critical for the efficiency and safety of transportation systems in all winter climates. Tools that help road authorities plan for, assess, and communicate the relationship between climate and winter road maintenance (WRM) activities are needed. There is increasing evidence that the development of such Climate Services (CS) tools is an iterative, evolving, and long-term process between the producers and users of this climate information, which increases the usability and application of climate science. This paper presents a case study describing the co-production of a climate translation service for a Canadian road authority. The purpose of this study is to: 1) refine an existing Winter Severity Index (WSI) to better understand how winter weather translates into inter-annual variations in WRM activities using publicly available data; 2) apply the index to historical weather observations to assess the magnitude and significance of historical winter weather trends, and 3) apply the index to modelled climate data to project the impacts of climate change on WRM operations in Ontario, Canada. Results indicate that the WSI for Ontario highways has strong fit with maintenance activity, when measured as equipment-hours. Analysis of WRM trends over more than three decades shows that winter severity has increased in some areas and decreased in others. The climate change analysis reveals that winters will experience a reduction in winter severity into the coming century.

Modeling free-flow speed variations under adverse road-weather conditions: Case of cold region highways

This study investigates driver behavior with respect to variations in desired driving speed under adverse road-weather conditions and explores the impacts of applying different data treatment methods in modeling such variations. The study site is located in a cold region highway in Alberta, Canada. The road-weather and traffic data collection devices are located alongside, permitting accurate measurement and association of exact pertaining road-weather and traffic conditions. The study has two main objectives: i) to investigate and model the impacts of road-weather events on the free-flow speed of vehicles, and ii) to explore the variability in models caused by adopting different data treatment methods. Linear and nonlinear regression models were developed with separate models for light and heavy vehicles travelling in shoulder and median lanes. Linear regression models developed with 20-minute aggregated free-flow speeds as dependent variable was found to be the best performing model for describing drivers’ choice of desired speed under adverse road-weather conditions. The study results revealed that slight, moderate and heavy snow will respectively reduce the free-flow speed of light vehicles travelling in the shoulder lane by 0.2%, 3.4% and 0.8%, and by 0.3%, 0.4% and 1.5% when travelling in the median lane. Moreover, heavy vehicles travelling in slight, moderate and heavy snow were estimated to reduce their desired speeds by 1.7%, 0.1% and 1.3% in shoulder lane while the reduction factors for those travelling in slight and moderate snow in median lane was 1.1% and 1% respectively. Estimated reduction factors for free-flow speed variations under adverse road-weather conditions found to be significantly smaller than HCM (2016) recommendations and the findings of other studies. These figures signify the importance of winter road maintenance in extremely cold regions. The frequent snow and ice removal as a result of winter road maintenance operations obviates the need for reducing desired speed and eventually results in less weather-related delays. The significance of driver familiarity with prevailing geographical conditions, i.e. winter driving was also highlighted when investigating the impact of inclement road-weather conditions on traffic operations.

Life cycle assessment of winter road maintenance

Winter road maintenance in the Nordic climate is demanding due to challenging weather conditions, high precipitation, and icy conditions. As a leading country in the transition to low-emission transport, Norway must work to reduce their emissions while providing a safe level of service through winter maintenance operations. This article investigates the environmental impacts of winter road maintenance (WRM) in Norway both today and under a climate change scenario predicted for 2050. Life cycle assessment (LCA) is used to evaluate the environmental impact of the functional unit “average winter road maintenance in Norway on national and county roads per km.lane.” The ReCiPe (hierarchy) method was used to identify and categorize emissions related to WRM to show how different factors affect the system and to reveal hidden emissions hotspots. Real-time data from WRM vehicles were used to determine how fuel consumption is affected by gradient and weather. Producers and operators provided other relevant information on WRM vehicles. Official reports supplied information on deicer quantities used and the total distance driven by WRM vehicles in Norway. The quantity of deicer used is the main source of emissions contributing toward all impact categories. The effect of deicer is likely to be even higher in certain impact categories. The environmental impact of the deicer after application is not included. The representation of WRM in existing emissions data is limited despite the considerable amount of deicer applied and the long distances that WRM vehicles travel. The results document how energy use throughout the system is another important source of emissions. Various parameters, such as road gradient, vehicle properties, driver behavior, and weather, affect the fuel consumption of WRM vehicles, with weather being the most important of these. Significant potential for emissions reductions from WRM was found, and WRM operations should be included in cold-climate road LCA studies. The environmental impacts of deicer application are especially high compared to the mechanical clearing of roads and contribute strongly to impact categories such as terrestrial, freshwater, and human toxicity and to the formation of particulate matter.

Developing Renewable Agro-Based Anti-Icers for Sustainable Winter Road Maintenance Operations

AbstractThis work evaluated the performance and impacts of several agro-based anti-icers along with two traditional chloride-based anti-icers (23% by weight NaCl brine and its beet juice blend). A ...

Identifying Equipment Factors Associated with Snowplow Operator Fatigue

A recent body of research in fatigue management indicates that other factors, including in-cab and external equipment, contribute to operator fatigue. The goal of this project was to identify winter road maintenance equipment (in-cab and external) that may increase or mitigate snowplow operator fatigue. To accomplish this goal, questionnaires from 2011 snowplow operators were collected from 23 states in the U.S. Results confirmed previous research that fatigue is prevalent in winter road maintenance operations. Winter road maintenance equipment that produced excessive vibrations, noise, reduced visibility, and complex task demands were found to increase snowplow operators’ self-reported fatigue. Similarly, equipment that reduced vibrations and external noise, improved visibility, and limited secondary tasks were found to reduce snowplow operator’s self-reported fatigue. Based on the questionnaire responses and the feasibility of implementation, the following equipment may help to mitigate or prevent snowplow operator fatigue: dimmable interior lighting, LED bulbs for exterior lighting, dimmable warning lights, a CD player or satellite radio in each vehicle, heated windshield, snow deflectors, narrow-beam auxiliary lighting, and more ergonomically designed seats with vibration dampening/air-ride technology.

A geostatistical approach to winter road surface condition estimation using mobile RWIS data

In winter, it is critical for cold regions to have a full understanding of the spatial variation of road surface conditions such that hot spots (e.g., black ice) can be identified for an effective mobilization of winter road maintenance operations. Acknowledging the limitations in present study, this paper proposes a systematic framework to estimate road surface temperature (RST) via the geographic information system (GIS). The proposed method uses a robust regression kriging method to take account for various geographical factors that may affect the variation of RST. A case study of highway segments in Alberta, Canada is used to demonstrate the feasibility and applicability of the method proposed herein. The findings of this study suggest that the geostatistical modelling framework proposed in this paper can accurately estimate RST with help of various covariates included in the model and further promote the possibility of continuous monitoring and visualization of road surface conditions.

A Geostatistical Investigation into the Effective Spatiotemporal Coverage of Road Weather Information Systems in Alberta, Canada

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.

Integrated winter road maintenance management — New directions for cold regions research

The purpose of winter road maintenance is to reduce the negative effect of snow and ice on traffic. The current literature on winter maintenance practices is split into two segments: means of forecasting weather in order to plan proper winter maintenance, and optimization of maintenance operations. There is relatively little literature on the opportunities that real-time information, e.g., from maintenance vehicles, would offer for combining these two segments and taking the applied research and practice one step further. It seems, however, that the lack of operational solutions has so far limited empirical research in favour of analysing prospects that the ubiquitous technologies could offer for winter maintenance. Recent field tests show that the technical obstacles to obtaining real-time information from maintenance vehicles can be overcome. Thus it is possible to enhance the benefits of winter road maintenance operations considerably through new designs and architectures. Improving the efficiency of vehicle fleets by using real-time information is one of the first realizable steps. Based on the analysis of current winter road maintenance ecosystems in several countries, this paper suggests how to make effective use of the transparency that real-time information exchange between different actors can offer. Transparent real-time information enables re-engineering of the entire winter maintenance ecosystem and assists road authorities in setting more precise, and at the same time more diverse, objectives for winter maintenance. This also involves real-time monitoring of service providers' performance and realization of these objectives.

An integrated model to solve the winter asset and road maintenance problem

Winter road maintenance operations require many complex strategic and operational planning decisions. The main problems include locating depots, designing sectors and routes, and configuring and scheduling vehicles. The complexity involved in each of these decisions has generally resulted in research that approaches each of the problems separately, which can lead to isolated and suboptimal solutions. In addition to being integrated, a successful approach to these problems must consider the necessary practical aspects of each problem and include a straightforward, easily executable solution methodology; otherwise, it is unlikely to be implemented. This research proposes a systematic, heuristic-based optimization approach to integrate the winter road maintenance planning decisions. The approach is illustrated using an example of the state highway road network in Boone County, Missouri, which is maintained by the Missouri Department of Transportation.

Optimizing winter road maintenance operations under real-time information

This paper introduces a real-time optimization model that can be used by maintenance managers to develop and evaluate alternative resources allocation plans for winter road maintenance operations. The model takes into account a wide range of road and weather condition factors such as road network topology, road class, weather forecasts, and contractual service levels, and produces a vehicle dispatch schedule that is optimal with respect to operating costs and quality of service. The model is then used in an analysis on a realistic case to illustrate the potential impact of improved information on winter maintenance operations.

Friction coefficient measurement for autonomous winter road maintenance

Real-time measurement of tyre–road friction coefficient is extremely valuable for winter road maintenance operations, since knowledge of tyre–road friction coefficient can be used to optimise application of deicing chemicals to the roadway. In this paper, a wheel-based tyre–road friction coefficient measurement system is developed for snowploughs. Unlike a traditional Norse meter, this system is based on measurement of lateral tyre forces, has minimal moving parts and does not use a brake actuator. Hence, it is reliable and inexpensive. A key challenge is quickly detecting changes in the estimated tyre–road friction coefficient while rejecting the high levels of vibratory noise in the measured force signal. Novel filtering and signal processing algorithms are developed to address this challenge, including a biased quadratic mean filter and an accelerometer-based vibration removal filter. Detailed experimental results are presented on the performance of the friction estimation system on different types of road surfaces. It is also shown that disturbances due to lateral and longitudinal vehicle manoeuvres on the estimated friction coefficient can be removed by using accelerometer-based filtering.

The sector design and assignment problem for snow disposal operations

Winter road maintenance operations involve a host of decision-making problems at the strategic, tactical, operational, and real-time levels. Those operations include spreading of chemicals and abrasives, snow plowing, loading snow into trucks, and hauling snow to disposal sites. In this paper, we present a model and two heuristic solution approaches based on mathematical optimization for the problem of partitioning a road network into sectors and allocating sectors to snow disposal sites for snow disposal operations. Given a road network and a set of planned disposal sites, the problem is to determine a set of non-overlapping subnetworks, called sectors, according to several criteria related to the operational effectiveness and the geographical layout, and to assign each sector to a single snow disposal site so as to respect the capacities of the disposal sites, while minimizing relevant variable and fixed costs. Our approach uses single street segments as the units of analysis and we consider sector contiguity, sector balance and sector shape constraints, hourly and annual disposal site capacities, as well as single assignment requirements. The resulting model is based on a multi-commodity network flow structure to impose the contiguity constraints in a linear form. The two solution approaches were tested on data from the city of Montreal in Canada.

A survey of models and algorithms for winter road maintenance. Part I

Winter road maintenance operations involve a host of decision-making problems at the strategic, tactical, operational, and real-time levels. Those operations include spreading of chemicals and abra...

A survey of models and algorithms for winter road maintenance. Part III: Vehicle routing and depot location for spreading

Winter road maintenance planning involves a variety of decision-making problems related to the routing of vehicles for spreading chemicals and abrasives, for plowing roadways and sidewalks, for loading snow into trucks, and for transporting snow to disposal sites. These problems are very difficult and site specific because of the diversity of operating conditions influencing the conduct of winter road maintenance operations and the wide variety of operational constraints. As the third of a four-part survey, this paper reviews optimization models and solution algorithms for the routing of vehicles for spreading operations. We also review models for the location of vehicle and materials depots and for the assignment of crews to vehicle depots. The two first parts of the survey address system design problems for winter road maintenance. The fourth part of the survey covers vehicle routing problems for plowing and snow disposal operations.