An increase in cycling mode share and cycling performance is an essential part of future transport development (Buehler and Pucher 2011; Schwanen 2015). In order to achieve the climate goals of the Federal Republic of Germany, the share of cycling must be significantly increased (BMVI 2021). An important part of this is to make cycling safe also in harsh weather conditions as seen in winter. While cycling mode shares have increased in the other seasons in recent years, a slump in cycling performance can be observed especially in winter (Nobis 2019). Studies to date have attributed this to weather conditions (temperature, precipitation) (Winters et al. 2011) and, above all, to the declining subjective feeling of safety among cyclists. Many German municipalities are therefore working on a winter service concept for cycling in order to mak.e cycling safe even in winter conditions. ... Therefore, an environmentally sound alternative for winter maintenance on segregated cycle paths that is acceptable to cyclists must be found. In many German cities but also globally, the challenge is to find a balanced solution between environmental protection and safe cycling. However, possible alternatives have to go through an approval process before they can be used. To solve those questions, we conducted several surveys which are summarized in this paper. lt consists of five sections: Section 2 highlights the wishes and demands on cycling(infrastructure) in winter from the cyclists' point of view. In section 3, the current state of winter maintenance in German cities is reviewed. Section 4 describes the selection and ecological footprint of alternative gritting materials, while section 5 describes the experiences of users in a field test. [From: Introduction]

NIRA is a company based in Linköping and operates within the automotive industry. NIRA's Tire Grip Indicator is one of their products used to create friction values during normal driving conditions. This data is, together with additional sensor information from the vehicle, such as environmental sensors, collected in NIRA's cloud environment RSI. Utilising hundred of thousand of vehicles, several products are created and offered to the market. This master thesis will focus on the winter maintenance industry business where NIRA provides refined information to support decision making and quality control for the winter maintenance operations both in Sweden and internationally. The master thesis will be conducted in close cooperation with several actors active in the winter maintenance business within the scope of a collaboration project.  The thesis explores how road surface information can be used as decision support for actors within road maintenance. The thesis starts with a literature study describing different perspectives of winter maintenance and its relation to decision support systems. Through the study, several decision support systems are used to analyse the road climate and the maintenance operations in the city of Gothenburg. The analysis takes the form of a case study where each day during the winter season is analysed. Several features are extracted from the cases and are used to classify each case as one of 6 categories. Finally, the cases are valued within three cost areas: traffic accidents, accessibility, and fuel consumption.  The findings of the thesis show that the different systems within the project fulfil different functions in the work for more efficient winter road maintenance operations, where the forecasting tools can be seen as tools for planning measures. At the same time, friction data from fleets of connected vehicles can help evaluate the outcome of maintenance actions. This applies especially to the possibility of implementing and evaluating preventive measures. The findings also show several potential benefits in using road surface forecasts and road friction data in terms of financial, socio-economic, and environmental perspectives.

This thesis research has attempted to address two challenging problems in winter road maintenance, namely road surface condition (RSC) estimation and forecasting. For RSC estimation, the goal of the research was to develop models to discriminate RSC classes based on continuous friction measurements (CFM) and other available data such as temperature and precipitation history. A systematic exploratory study was conducted on an extensive field data set to identify the categorical relationship between RSC and various aggregate CFM measures, such as those related to probability distribution and spatial correlation. A new multi-level model structure was designed, under which binary logistic regression models were calibrated and validated utilizing several carefully chosen aggregate measures to classify major RSC types. This model structure was found to be effective in capturing the overlapping nature of CFM ranges over different RSC types -- a problem which has not been addressed adequately in the past studies. An alternative model with support vector machine (SVM) was also developed for benchmarking the performance of the proposed logit model. It was found that the two types of models are comparative in performance, confirming the high performance of the proposed multi-level model. For road surface condition forecasting, a novel conceptual framework for short-term road surface condition forecasting is proposed, under which the short-term changing process of surface temperature, friction level and contaminant layer depths, is comprehensively explored and analyzed. This study framework is designed to consider all important conditional factors, including weather, traffic and maintenance operations. The maintenance operations, especially salting, are handled by loosening the strict Markovian assumption, i.e., a history instead of one single time interval of salting operations is considered. In this way, the variation of snow/ice melting speed caused by both residual salt amounts and salt/contaminant mixing states is incorporated in the forecasting model, which enables accurate short-term forecasting for contaminant layers. This approach practically circumvents a major limitation of previous studies, making the post-salting RSC forecasting more reliable and accurate. Under the proposed model framework, several advanced time series modelling methodologies are introduced into the analysis, which can capture the highly complex interactions between RSC measures and conditional factors simultaneously. Those methodologies, especially the univariate and multivariate ARIMA methods, are for the first time applied to the winter RSC evolution process. The forecasting errors of surface temperature, friction level and contaminant layer depths are all found to be small, implying that both the proposed study framework and the resulting solutions closely match the real-world observations. The proposed forecasting models are simple in structure, easy to interpret and mostly consistent with physical knowledge. Compared to the existing models, the proposed models provide extra flexibility for refactory, tuning and deployment. Furthermore, all the modelled RSC measures are numerical and the forecast errors are relatively small, suggesting empirical models could be an efficient alternative to physical models. With the well-designed modelling methods, the resulting empirical models as calibrated in our study can be implemented into a decision support and simulation tool with high temporal resolution and accuracy.

Efficient winter road maintenance is crucial for safety and societal function during the winter months in Sweden. This report aims to evaluate the MetCoOp ensemble system CMEPS and investigate its potential use as a basis for formulating criteria for snow removal that accounts for forecasted weather. Today the criteria for activating snow removal in Sweden are static, meaning they start after a set amount of snow and should end within a set time span. The verification metrics rank-histogram, continuously rankprobability score, reliability diagram, and Brier score were used to evaluate temperature and solid precipitation. Observations used as verification were taken at the measuring station Geocentrum in Uppsala during the winters of 2020/2021, 2021/2022, and November-December 2022. The analysis shows the temperature forecast to be under-dispersive and with a cold bias. The ensemble system is shown to be less reliable for predicting temperatures below 0 °C the first 24 hours after the forecast is issued. Still, the forecast generally performs better for short lead times. The forecast overestimates solid and liquid precipitation. The wet bias is greatest for short lead times and long accumulation times. Short lead times are most reliable regarding solid precipitation over 1mm and 3mm. The first 24-30 hours are most important for an application in winter road maintenance, and based on how the forecast system performs for these lead times in this study, it would need calibration. For larger amounts of snow, new criteria could help adjust the starting time and time limits. Before implementing such criteria, practical questions as if dynamic criteria would lead to an improvement and how high the probability threshold should be must be answered. The sample size is also found to be too small, and further analysis is required, especially with data allowing for evaluation of higher thresholds. / En ensembleprognos består av flera prognoser som genom att baseras på något olika information beskriver ett antal möjliga framtida väderutfall. Idag används sannolikhetsprognoser i många delar av samhället då det ger möjligheten att se vilken sannolikhet en viss väderhändelse har. I det här arbetet har ensembleprognosen bestående av 30 medlemmar från MetCoOp utvärderats för temperatur och snö. I rapporten diskuteras även om det finns potential för att sannolikheter om det framtida vädret kan användas i kriterier för att bestämma när åtgärder för snö och is ska påbörjas och avslutas. Effektiv snöröjning och halkbekämpning är samhällsviktiga uppdrag som är kostsamma och kräver mycket planering. Sannolikhetsprognoser används redan som en hjälp för de som jobbar med vinterväghållning, främst för halkbekämpning, men kriterierna är idag fasta och snöröjning påbörjas när en viss mängd snö är uppmätt. Observationer av temperatur, nederbörd och nederbördstyp från mätstationen Geocentrum i Uppsala för vintrarna 2020/2021, 2021/2022 samt november-december 2022 har använts som verifikation. Prognosen har utvärderats med hjälp av rank-histogram, CRPS, reliability diagram och Brier score. Det framgick att temperaturprognosen hade liten och otillräcklig spridning, speciellt för korta ledtider. Ensemblesystemet visade samtidigt ofta för låga temperaturer. Analysen indikerade att mängden fast nederbörd överskattades av prognosen speciellt för 24-timmar ackumulation. Prognosen visade sig vara mest pålitlig för att prognosticera snö över 1mm och 3mm för korta ledtider. Studien visade även på att modellen överskattade regn vilket innebär att ensemblen har svårt att uppskatta nederbörd i allmänhet och inte snö i synnerhet. Prognosen visade sig inte vara pålitlig för att förutsäga om temperaturen 12 och 24 timmar efter observerat snöfall var konsekvent under 0 °C. Analysen är mindre pålitlig på grund av få snöfall under perioden i Uppsala. För att dra säkra slutsatser behöver ytterligare data analyseras med fler snöfall. Det finns dock potential att använda ensemblen från MetCoOp för att formulera kriterier för snöröjning, speciellt om den kalibreras. Med dynamiska kriterier skulle start- och sluttider kunna justeras så att de var anpassade till större snömängder. Det krävs ytterligare undersökning om hur inställningen bland yrkesverksamma ser ut och hur kriterierna skulle se ut i praktiken.

Winter in Northern Sweden comes with very harsh and unpredictable condition associated with large amounts of snowfall covering roadways thereby affecting transportation by roads. When the road conditions i.e. the snow depth, road unevenness and friction of the road surface are accessed and found to exceed the threshold, a maintenance action must be carried out to retain the road to the required condition for the user. The aim of maintenance, in this case, is to make the road comfortable, safe and economical for the road user. Decision support system, therefore, comes in handy to facilitate on deciding what maintenance action to carry out and when the action should be carried out, where the action should be carried out and how to go about the action based on the various data and resources available. This thesis project concentrates on how to carry out a winter road maintenance after receiving an alert of an action to carry out, when to carry it out and the road network that needs to be maintained. The thesis work focusses only on two of the winter road maintenance actions namely snow ploughing of bus stops in Luleå and application of abrasives commonly referred to as sanding of bus stops. Carrying out winter road maintenance comes at a huge cost from both direct and indirect costs with the Swedish government spending about SEK 1.75 billion every year as indicated by Jana Sochor and Cecilia Yu (Sochor & Yu, 2004). This means that reduction in the maintenance cost of even 5% through optimisation of the maintenance cost would translate into a saving of about 87.5 million SEK per year and in 10 years could amount to close to 1 billion SEK. Optimization also leads to efficiency and effectiveness that could result in improved movement on the road and reduced environmental and social-economic impacts. Maintenance planning thus becomes essential for the effective and efficient execution of work and utilisation of the available scarce resource. This thesis project focusses on the use of Operations research methods to minimise the cost of carrying out a winter road maintenance action by finding the near optimal or if possible optimal solution and still deliver the required service level. The thesis delivers two main things: It first delivers a framework to support winter road maintenance decision making after an alert of an action is received and secondly an algorithm for the route that minimises the cost of maintenance by providing the route that minimises the travel distance of the ploughing/sanding vehicle from its source depot and back to the depot after completing a maintenance action assuming that the vehicle and material (fuel and sand) are in the same depot. The routes with minimum travel distance will, therefore, be that route that will reduce the labour time and in turn the labour cost, reduce the fuel consumption and the maintenance of the equipment due to reduced usage. The project uses a vehicle routing problem which is a generalised travelling Salesman as the optimisation technique to determine the optimal solution for the allocation of resources for carrying out a maintenance action to facilitate efficient utilisation of the available resources. This is with the help of a commercial optimisation software and support tools namely ArcGIS. To come up with the algorithm, the first step was a digital representation of the vehicle road network in Luleå for network analysis after which the bus stops were imported from google earth into the network. A two-stage optimisation was then carried out: first was a model for route optimisation based on the road network in ArcGIS with the objective function to minimise the travel distance and constraints based on the available resources. The results of ii the model were then exported into excel for the second optimisation for the optimal cost of maintenance done through a developed excel algorithm. The total cost of maintenance comprised direct and indirect cost. The direct cost consisted of the cost of fuel, the cost of personnel and the cost of hiring vehicles while the indirect cost results from the penalty fee charged for sanding and ploughing a bus stop after the threshold time given to a maintenance contractor by the municipality. Any bus stop that is ploughed after the threshold attracts a penalty per hour of the exceeded time. Six penalty threshold times were considered i.e. 30, 60, 90, 120, 150 and 180 minutes and a single parameter deterministic sensitivity analysis was carried out for each cost parameters to determine the sensitivity of the total maintenance cost. The more relaxed penalty thresholds were found to be less sensitive to the direct cost and the total maintenance cost compared to the more sensitive ones. When the penalty threshold is relaxed, the optimal maintenance cost reduces, and the required number of vehicles reduces. The cost of vehicle hire was found to be more sensitive than the other costs. The results of this project can help the maintenance contractor in developing a work schedule for the maintenance personnel and improve vehicle fleet management. By modelling the worst scenario, a contractor can plan for the maximum number of vehicles required and consequently the personnel required. With the optimal travel route for each vehicle and the total maintenance cost determined, maintenance contractors can determine the sustainability and profitability of their business and be able to negotiate for a better and more sustainable agreement (Contract) or for the relaxation of the penalty threshold time if it does not affect the service level required i.e. the quality and safety requirements. The approach used in this project can also be used for other winter road maintenance problems.

More than a million people die every year due to road traffic accidents globally where one in five serious or fatal accidents occurs during severe weather conditions. Sweden is in the lead of Vision Zero, with the aim of zero casualties due to road traffic, and every year new countries and organisations accept the challenge of saving lives. Early studies have shown that one way of decreasing casualties is to implement floating car data (FCD), which is data obtained from connected road vehicles. One example of such an implementation is to gather knowledge about the current state of the road network enabling targeted winter road maintenance. By implementing FCD for winter road maintenance, besides creating safer roads, savings will be made for the environment by reducing the use of fossil fuels and salt. Since the fleet of road vehicles is going towards being fully autonomous, the volumes of FCD will increase rapidly generating new possibilities for FCD usage. Recent research regarding FCD has mainly focused on traffic flow, speed and route optimisation, together with general methods for FCD mining creating intelligent transport systems. Studies have also been made to cover the gap between road weather information systems (RWIS) monitoring the road condition and thereby improving road weather forecasts. But there is a need for research regarding the implementation of FCD at a level of action, closer to the road users improving winter road maintenance. Presented in this thesis are results gathered in the project Digital Winter, a project initiated by the Swedish Traffic Administration, where FCD regarding tire-to-road friction has been procured for all public roads in Sweden. Results show promising numbers regarding coverage and reliability for implementation of FCD for winter road maintenance follow-up, managing that assigned levels of road friction are achieved. Examples are given for different areas in Sweden where harsh weather conditions are detected and statistics show coverage of FCD both at a daily and hourly level. Multiple suppliers of FCD have been participating in Digital Winter and the measurements presented, show a correlation between suppliers of FCD and methods that today are approved for winter road maintenance follow-up in Sweden. But also that the friction measured using FCD is closer to the true road friction experienced by road users.

Winter road maintenance is a necessity during the winter in Sweden, since the weather reduce traffic safety and accessibility, which have great impact on people and society in general. Unlike the degradation process of paved road surface and subgrade, that develops slowly over several years, the general state of the winter road can change significantly within a couple of hours, thus demanding more of road maintenance organisations when it comes to planning and initiating maintenance actions. Today there is a wide range of available sensor technology, that can be utilized to monitor the condition of the winter road and provide decision makers with the required information to initiate maintenance activities at the right time. However, it is necessary for the user, e.g. maintenance staff and decision makers, to know how this type of technology can be applied to make the winter road maintenance more efficient. The aim of this thesis is to define the winter road maintenance process, what obstacles and problems are present and the information requirements that are associated with planning, initiating and performing the winter road maintenance activities. The thesis focuses on the maintenance process for municipalities in northern Sweden using the city of Kiruna as a case study. An interview study was performed at Tekniska Verken in Kiruna to collect empirical data, which forms the basis for the process- and flow charts that are presented in the result. Common failure modes, connected to the failures that usually leads to the initiation of a maintenance activity, are identified, based on the interviews and the quality declaration for winter road maintenance. The failure modes were connected to the workflows, to show the phases of the workflow where the information is useful. Based on this, suitable sensor technology is proposed, which partly or fully meet the identified information requirements, and monitors the interesting failure modes of each maintenance activity. The results show that the greatest need for information is found in the stage of assessment and decision-making regarding initiation of maintenance actions, especially when it comes to initiation of snow plowing and de-icing activities. Using vehicle-based sensor technology, the condition of the road can be continuously monitored, and the initiation of maintenance activities can be triggered when reaching a threshold. Having road weather information stations, e.g. monitoring air and road temperature, wind speed, precipitation and road condition, is also an important source of information for municipal winter road maintenance. The use of sensor technology results in maintenance processes with fewer activities and decision steps, and it generates more reliable data that simplifies the decision-making. / Vinterväghållning är en nödvändighet under vinterhalvåret i Sverige, då väderlek har en stor påverkan på trafiksäkerhet och framkomlighet för trafikanter. Till skillnad från nedbrytningen av belagd väg under barmarkssäsongen, som sker stegvis under flera år, kan vintervägens tillstånd försämras avsevärt inom bara ett par timmar. Detta ställer högre krav på vägunderhållsorganisationer vad gäller planering och initiering av underhållsåtgärder. Idag finns ett brett utbud av sensorteknik som kan användas för att övervaka vintervägens tillstånd, och förse beslutsfattare med nödvändig information för att kunna initiera underhållsaktiviteter vid rätt tidpunkt. Det är dock nödvändigt att användaren, dvs. underhållspersonal och beslutsfattare, har kunskap om hur denna teknik kan användas för att effektivisera vinterväghållningen. Syftet med arbetet är att ta reda på hur underhållsprocessen för kommunal vinterväghållning är utformad, vilka hinder och problem som förekommer samt vilket informationsbehov som finns i samband med planering, initiering och utförande av vinterväghållningsaktiviteter. Arbetet är avgränsat till att analysera vinterväghållningen i Kiruna kommun. En intervjustudie utfördes vid Tekniska Verken i Kiruna för insamling av empiriskt material, vilket utgjorde underlaget för de process- och flödeskartor som presenteras i resultatet. Med utgångspunkt ur intervjumaterialet och kommunens kvalitetsdeklaration för vinterväghållning, identifierades vanliga felmoder kopplade till de funktionsfel som leder till initiering av underhållsaktivitet. Felmoderna kopplades sedan till arbetsflödena, genom att visa i vilket skede i arbetet som information om dessa är användbar. Utifrån detta gavs förslag på lämplig sensorteknik som helt eller delvis kan tillgodose informationsbehovet som identifierats, samt övervaka de felmoder som är intressanta för respektive underhållsaktivitet. Resultatet av undersökningen visar att det är vid bedömning och beslut om initiering av underhållsåtgärd som informationsbehovet är störst, framför allt när det handlar om initiering av snöröjning och halkbekämpning. Genom att använda sensorteknik för kontinuerlig övervakning av vägens tillstånd, kan underhållsaktiviteter initieras vid definierade gränsvärden. Egna vägväderstationer som övervakar och mäter exempelvis luft- och vägtemperatur, vindstyrka, nederbördsmängd och typ samt väglag, kan vara till nytta för den kommunala vinterväghållningen oavsett vilken underhållsaktivitet det handlar om. Användningen av denna typ av teknik leder till effektiviserade underhållsprocesser med färre aktiviteter och beslutssteg, samt förenklad beslutsfattning baserat på mer tillförlitliga mätdata.

In countries with harsh winter climates extensive winter road maintenance is necessary to achieve traffic accessibility and road safety. These measures have high economic and environmental costs as snow free roads and winter road maintenance in Sweden today is achieved by a combination of mechanical snow clearance and the spreading of salt to prevent ice formation. The salt ends up in the roadside environment and has negative effects on groundwater and vegetation. An alternative to traditional winter road maintenance to obtain non-skid winter roads is the use of hydronic pavement(HP) systems. Existing HP systems in Sweden are powered by district heating which limits the application to urban locations. The goal is to utilize renewable energy sources such as geoenergy which can be used in both rural and urban locations. This thesis suggests Hamnbacken in Visby as a pilot project for a full-scale application of the proposed HP system using surface water source heat.The weather related road surface conditions on Hamnbacken, and the potential of a renewable energysource have been examined in this study and the proposed location has been found favourable for a HP system. / Länder med övervägande kallt vinterklimat är halkbekämpning en nödvändighet för trafikens framkomlighet och säkerhet. Åtgärderna som vidtas för att få snö- och isfria vägar är kostsamma samt har en hög miljöpåverkan, ett vedertagligt exempel är plogning och saltning. Saltet hamnar i slutändan inom vägens omgivande områden och har en negativ påverkan på grundvatten och vegetation. En alternativ lösning till traditionell halkbekämpning är uppvärmda vägar för att uppnå ett halkfritt vinterväglag. Befintliga väguppvärmningssystem i Sverige försörjs av fjärrvärme vilket är en begräsning då tillgången till fjärrvärme finns i anslutning till tätorter. Målet är att utnyttja förnybara energikällor såsom geoenergi som är tillgänglig både i tätorter och på landsbygden. Det här examensarbetet undersöker Hamnbacken i Visby som ett pilotprojekt för en fullskalig implementering av väguppvärmningssystem där sjövärme används som energikälla. Denna studie har undersökt väderrelaterade vägförhållanden på Hamnbacken samt potentialen för användning av sjövärme. Den föreslagna platsens förutsättningar har visat sig vara gynnsamma i detta avseende.