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1.
  • Almlöf, Erik, 1985- (author)
  • Beyond Technology : Understanding societal impacts of implementing self-driving vehicle systems on road transport
  • 2024
  • Doctoral thesis (other academic/artistic)abstract
    • During the last decade, self-driving vehicles have become a major topic of interest, promising to transform transport by making travel safer and more efficient. However, as we move closer to making these vehicles a reality, it has become clear that introducing them into society might not be as straightforward as once thought, and there are growing doubts about the benefits they are supposed to offer.In this thesis, I investigate the societal impacts of self-driving vehicles by exploring four aspects: reasons for researching self-driving vehicles, how these vehicles could be implemented, the societal impacts of fully implementing self-driving vehicles, and their relationship to sustainability goals.I find that the motivation for researching this topic is often opaque, and the existence of the technology itself is used as a justification for more research. Furthermore, most research into realising self-driving vehicles focuses on purely technical aspects such as designing better algorithms. However, I show that many challenges remain connected to the sociotechnical intertwinement of self-driving vehicles. For instance, I illustrate how they will interact with pedestrians and how services using self-driving vehicles would be practically organised.Additionally, self-driving vehicles are likely to impact many aspects of society, such as congestion, accessibility, and economic factors. However, I demonstrate that no single framework successfully captures all the identified societal impacts, which are likely to depend on diverse factors such as geographical variations.The impacts further affect sustainability, where new challenges are likely to emerge. I show that while current tools to govern the transport system are still relevant, a comprehensive approach is needed to ensure that policymakers make well-considered decisions. In conclusion, I call for a more balanced view of self-driving vehicles. Introducing this new technology requires careful planning and governance to ensure that self-driving vehicle systems genuinely enhance our quality of life and help build a sustainable future. 
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2.
  • Almlöf, Erik, 1985- (author)
  • Exploring societal impacts of self-driving public transport using four-step transport models
  • 2022
  • Licentiate thesis (other academic/artistic)abstract
    • During the last decade, self-driving technology has become increasingly visible in the news, with the vision that people would enter vehicles that drive themselves, and that people could instead rest, read the newspaper, or have a meeting. However, these visions have mainly focused on the potential for car usage, even though public transport could benefit greatly from self-driving technology. For bus traffic, the bus driver accounts for half of the cost of driving, and savings on personnel costs could, for example, be reinvested in expanded public transport service or used to lower taxes.At the same time, more research has shown potential problems linked to self-driving technology, for example that more comfortable driving would lead to more traffic, which in turn would lead to increased emissions, higher noise levels in cities or further focus on car-centric infrastructure. For public transport, the driver's role in creating safety and acting as problem solvers has also been emphasized - who should I ask for directions if there is no knowledgeable driver on board?Various methods have previously been used to explore the social effects of self-driving technology and in this dissertation I have used so-called "four-stage models", more specifically the Swedish transport model Sampers. Four-stage models have been used for 50 years to evaluate effects on the transport system from e.g. infrastructure changes, but these models face new challenges, handling vehicles that drive by themselves. In my research, I have adjusted the model to simulate self-driving technology and investigated what effects this has on, for example, traffic volumes and emissions.In the three articles that are part of the dissertation, I have four main conclusions:Self-driving technology can mean large savings in costs for public transport, primarily for bus traffic but also to some extent for rail traffic. In addition, a smoother driving behaviour would mean more comfortable travel, which would increase the attractiveness of public transport. In addition, public transport not limited by, for example, driver schedules or current commercial conditions, could develop new types of services, such as on-demand public transport.Four-stage models have previously been used to model the transport system and have been shown to have good results, at least at an overall level. Within my research, I have made some adaptations of these models to mimic self-driving technology, but the models in their current form cannot consider, for example, vehicle sharing.It is important to point out that bus and train drivers currently perform many tasks that are not directly related to the driving of the vehicle, such as answering questions, maintaining social order among passengers and taking care of faults that occur during the trip. Today, self-driving technology cannot fulfil these roles.Self-driving technology for public transport would affect people's accessibility, driving style for vehicles, safety on board, how we plan traffic and the people who currently work as drivers. In fact, a multitude of societal effects have been identified, affecting all areas of transport. In addition, the effects are generally not similar across geographies, time units or for different actors, which further emphasizes that the total effect is not easy to summarize.
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3.
  • Almlöf, Erik, 1985-, et al. (author)
  • Frameworks for assessing societal impacts of automated driving technology
  • 2022
  • In: Transportation planning and technology (Print). - : Taylor & Francis. - 0308-1060 .- 1029-0354. ; 45:7, s. 545-572
  • Journal article (peer-reviewed)abstract
    • Numerous studies have studied the impacts of automated driving (AD) technology on e.g. accident rates or CO2 emissions using various frameworks. In this paper we present an overview of previous frameworks used for societal impacts and review their advantages and limitations. Additionally, we introduce the Total Impact Assessment (TIA) framework developed by the Swedish Transport Administration and use this framework to evaluate three scenarios for AD bus services in Stockholm. We conclude that the reviewed frameworks cover different aspects of AD technology, and that e.g. cybersecurity and biodiversity are areas largely neglected. Furthermore, most frameworks assume effects to be homogenous, when there may be large variation in e.g. perceived security. The TIA framework does not manage to include all societal aspects of AD technology, but has great benefits and manages to provide important insights of the societal impacts of AD technology, especially how effects may wary for different actors.
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4.
  • Almlöf, Erik, 1985-, et al. (author)
  • Frameworks for assessing societal impacts of self-driving technology
  • Other publication (other academic/artistic)abstract
    • Numerous studies have studied the impacts of self-driving technology on e.g. accident rates or CO2 emissions using various frameworks. In this paper we present an overview of previous frameworks used for societal impacts, and review their advantages and limitations. Additionally, we introduce the Total Impact Assessment (TIA) framework developed by the Swedish Transport Administration and use this framework to evaluate three scenarios for self-driving bus services in Stockholm. We conclude that the reviewed frameworks cover different aspects of self-driving technology, and that e.g. cybersecurity and biodiversity are areas neglected by most frameworks. Furthermore, most frameworks assume effects to be homogenous, when there may be large variation in e.g. perceived security. The TIA framework does not manage to include all societal aspects of self-driving technology, but has great benefits and manages to provide important insights of the societal impacts of self-driving technology, especially how effects may wary for different actors.
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6.
  • Almlöf, Erik, 1985-, et al. (author)
  • Who continued travelling by public transport during COVID-19? : Socioeconomic factors explaining travel behaviour in Stockholm 2020 based on smart card data
  • 2021
  • In: European Transport Research Review. - : Springer Nature. - 1867-0717 .- 1866-8887. ; 13:1
  • Research review (peer-reviewed)abstract
    • Introduction The COVID-19 pandemic has changed travel behaviour and reduced the use of public transport throughout the world, but the reduction has not been uniform. In this study we analyse the propensity to stop travelling by public transport during COVID-19 for the holders of 1.8 million smart cards in Stockholm, Sweden, for the spring and autumn of 2020. We suggest two binomial logit models for explaining the change in travel pattern, linking socioeconomic data per area and travel data with the probability to stop travelling. Modelled variables The first model investigates the impact of the socioeconomic factors: age; income; education level; gender; housing type; population density; country of origin; and employment level. The results show that decreases in public transport use are linked to all these factors. The second model groups the investigated areas into five distinct clusters based on the socioeconomic data, showing the impacts for different socioeconomic groups. During the autumn the differences between the groups diminished, and especially Cluster 1 (with the lowest education levels, lowest income and highest share of immigrants) reduced their public transport use to a similar level as the more affluent clusters. Results The results show that socioeconomic status affect the change in behaviour during the pandemic and that exposure to the virus is determined by citizens' socioeconomic class. Furthermore, the results can guide policy into tailoring public transport supply to where the need is, instead of assuming that e.g. crowding is equally distributed within the public transport system in the event of a pandemic.
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7.
  • Almlöf, Erik, 1985-, et al. (author)
  • Who is still travelling by public transport during COVID-19? : Socioeconomic factors explaining travel behaviour in Stockholm based on smart card data
  • 2021
  • Conference paper (peer-reviewed)abstract
    • The COVID-19 pandemic has changed travel behaviour and reduced the use of public transport throughout the world, but the reduction has not been uniform. In this study we analyse the propensity to stop travelling by public transport during COVID-19 for the holders of 1.8 million smart cards in Stockholm, Sweden. We suggest two models for explaining the change in travel pattern, linking socioeconomic data with the probability to stop travelling. We find that education level, income and age are strong predictors, but that workplace type also substantially affect the propensity of public transport travel. Furthermore, we use clustering to divide the population into five separate social groups, serving as a more intuitive understanding of how the pandemic has affected different citizens’ propensity to use public transport. The results can guide policy makers on how to better tail e.g. bus supply to local demand, either through an increased understanding of differences based on the results or by further incorporating the results into a transport simulation models.
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8.
  • Almlöf, Erik, 1985-, et al. (author)
  • Will leisure trips be more affected than work trips by autonomous technology? : Modelling self-driving public transport and cars in Stockholm, Sweden
  • 2022
  • In: Transportation Research Part A. - : Elsevier BV. - 0965-8564 .- 1879-2375. ; 165, s. 1-19
  • Journal article (peer-reviewed)abstract
    • Self-driving technology may lead to a paradigm shift for the transport industry with shared cars available to every-one. However, this vision has increasingly been challenged as too optimistic and unsubstantiated. In this study we explore societal impacts of using this technology for both cars and public transport and investigate differences depending on geography and trip purpose. Four scenarios were designed through workshops with 130 transport experts, modelled using a conventional four-step model for Stockholm, Sweden and evaluated in terms of changes to mode choice, number of trips and person kilometres.We find larger increases for non-commuting trips, i.e. service and leisure trips, than for commuting trips, questioning the view of the 'productive work trip' as self-driving technology's main impact on society. As these trips are primarily made outside of rush hours, this may lead to a changed transport system. Geographic differences are substantial and heavily dependent on the cost model for car alternatives, even indicating a reduction in car travel in rural areas if private ownership would be replaced by shared cars. Furthermore, walking and cycling levels decreased in all scenarios while enhancing public transport using self-driving technology had a limited impact on ridership.These results show that the impacts of self-driving technology may have varied societal impacts even within a region and may lead to increased car travel, especially off-peak. These conclusions stress the need for policies that are sensitive to both geography and time.
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9.
  • Almlöf, Erik, 1985-, et al. (author)
  • Will leisure trips be more affected than work trips by autonomous technology? Modelling self-driving public transport and cars in Stockholm, Sweden
  • Other publication (other academic/artistic)abstract
    • Self-driving technology may lead to a paradigm shift for the transport industry with shared cars available to everyone. However, this vision has increasingly been challenged as too optimistic and unsubstantiated. In this study we explore societal impacts of using this technology for both cars and public transport and investigate differences depending on geography and trip purpose. Four scenarios were designed through workshops with 130 transport experts, modelled using a conventional four-step model for Stockholm, Sweden and evaluated in terms of changes to mode choice, number of trips and person kilometres. We find larger increases for non-commuting trips, i.e. service and leisure trips, than for commuting trips, questioning the view of the ‘productive work trip’ as self-driving technology’s main impact on society. As these trips are primarily made outside of rush hours, this may lead to a changed transport system. Geographic differences are substantial and heavily dependent on the cost model for car alternatives, even indicating a reduction in car travel in rural areas if private ownership would be replaced by shared cars. Furthermore, walking and cycling levels decreased in all scenarios while enhancing public transport using self-driving technology has a limited impact on ridership. These results show that the impacts of self-driving technology may have varied societal impacts even within a region and may lead to increased car travel, especially off-peak. These conclusions stress the need for policies that are sensitive to both geography and time. 
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10.
  • Jenelius, Erik, Docent, 1980-, et al. (author)
  • Dynamiska trängselindex
  • 2017
  • Reports (other academic/artistic)abstract
    • Under det senaste decenniet har nya datakällor, så som GPS‐data från taxibilar och storskaliga system av fasta detektorer, gett betydligt större möjligheter att kartlägga hur trängseln varierar i en stad, d.v.s. variation mellan gator och områden, olika tidpunkter på dagen och mellan olika månader eller år.På den teoretiska sidan har det, under ungefär samma tidsperiod, upptäckts ett samband mellan fordonstäthet och hastighet på områdesnivå, vilket kallas det makroskopiska fundamentaldiagrammet (MFD). Tidigare har detta samband uppmätts på länknivå och kallas då fundamentaldiagram (FD). MFD kopplar samman antalet fordon i ett område med den genomsnittliga hastigheten ellerflödet i området. Man har också visat att MFD under ideala förhållanden är enegenskap hos nätverket i sig (infrastruktur och trafikstyrning), d.v.s. det beror inte på efterfrågan.I denna rapport använder vi dessa nya trafikmätningsmetoder och teoretiska framsteg inom MFD för två syften. För det första beskriver vi hur trängseln varierar över dagen på Södermalm och i City‐området i Stockholm genom att titta på MFD från empiriska datakällor så som GPS‐data från taxi‐bilar, slangmätningar och restidskameror. För det andra jämför vi simulerat MFD för City‐området med empiriskt MFD för samma område. Detta för att validera hurväl City‐modellen framtagen med simuleringsverktyget Transmodeler kan återskapa trängselsituationen på områdesnivå.Rapporten visar att väldefinierade MFD existerar både för Södermalm och Cityområdet.MFD visar att hastigheten sjunker och fordonstätheten ökar undermorgonens och eftermiddagens rusningstimmar, men trängselnivåerna når inte den punkt där flödet börjar avta trots att fordonstätheten ökar (hyperträngsel). Det är således trångt i innerstaden under rusningstimmarna, men kapaciteten i nätverket räcker ändå till. De två stora lederna Stadsgårdsleden och Sveavägen visar dock tecken på hyperträngsel om fundamentaldiagram skapas separat för dessa leder.Vidare visar rapporten att MFD har stor potential som verktyg för att valideraen simuleringsmodell. I rapporten jämförs MFD från City‐området i Transmodeler med empirisk MFD för samma område. Simuleringsmodellen överskattar flöde och hastighet vid låg densitet. Vid hög densitet ändras dockbilden och simuleringsresultaten underskattar flöde och hastighet. Det verkarsom att kapaciteten i nätverket underskattas, vilket ger högre trängsel imodellen än i mätdata. MFD från Transmodeller visar lägre flöden underavvecklingen av rusningen än under uppbyggnaden, både under förmiddag och eftermiddag, vilket inte syns i de empiriska data. Detta tyder på att det finns stora kö‐problem i simuleringsmodellen, vilket man inte ser tecken på i empiriskt MFD.
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  • Jenelius, Erik, 1980-, et al. (author)
  • Validation of Traffic Simulation Models Based on the Macroscopic Fundamental Diagram
  • 2017
  • In: Transportation Research Procedia. - : Elsevier. - 2352-1465. ; , s. 561-568
  • Conference paper (peer-reviewed)abstract
    • Urban traffic simulation models could benefit significantly from new validation methods with potential to reduce the time-consuming calibration and validation work needed before application of the model to evaluate city infrastructure or policy implementations. Current practice is to validate simulation models locally through comparison with point flow measurements and travel times on some important routes. However, for many applications, the level of congestion in an entire area is important. During the last decade, several studies have found empirical evidence of a relation between flow and density on city district level, the existence of a so-called macroscopic fundamental diagram (MFD). This paper shows how the MFD can be used to validate results from a traffic simulation model for a city district. Furthermore, the paper shows empirical results for Stockholm, Sweden. © 2017 The Authors. Published by Elsevier B.V.
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13.
  • Andreolli, Raphael, et al. (author)
  • A review on real vehicle usage modelling of driverless multipurpose vehicles in vehicle routing problems
  • 2023
  • In: Proceedings of the International Conference on Engineering Design, ICED 2023. - : Cambridge University Press (CUP). ; , s. 385-394
  • Conference paper (peer-reviewed)abstract
    • Real vehicle usage rarely matches the predictions made during early phases of vehicle development and sales processes at commercial road vehicle manufacturers. The automotive industry needs multidisciplinary vehicle design methods to predict real-world vehicle operations by considering the vehicle level and the transport system level simultaneously, in a more holistic approach. The aim of this study was to analyse how realistic vehicle usage of driverless multipurpose vehicles can be modelled in Vehicle Routing Problems (VRPs) by conducting a systematic literature review. We found that real vehicle usage modelling of driverless multipurpose vehicles in VRPs mainly depended on the following elements: VRP variant, energy consumption model, energy consumption rate class, number of vehicle-specific design variables and transport system-level factors. Furthermore, we identified in the literature five classes of energy consumption rate edge behaviour in VRPs. These findings can support decision-making in the modelling process to select the most suitable combination of elements, and their level of detail for the overall modelling aim and purpose.
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14.
  • Andreolli, Raphael, et al. (author)
  • Energy Consumption Evaluation of Emerging and Current Vehicle Fleets in Urban Logistics
  • 2024
  • In: 10th Transportation Research Arena, Dublin, Ireland, 15-18 April 2024.
  • Conference paper (other academic/artistic)abstract
    • Driverless multipurpose vehicles (DMVs) are an emerging vehicle concept for urban heavy-duty transport. However, little is known about their effect on urban road transport systems. Thus, the aim of this study is to analyse the total fleet energy consumption of DMVs for specific transport operations in urban logistics compared to heavy- duty battery and combustion vehicles. A novel electric vehicle routing problem was used to simulate in total 96 case-studies of operations with varying network and vehicle fleet properties. We found that the combustion vehicle fleets consumed significantly more energy for the same operation compared to the electric vehicle fleets. Although the DMV fleet and battery electric vehicle fleet showcased similar energy consumption for most case-studies, there were several operations where the DMV fleet consumed less energy and required a smaller fleet size. This study highlights the potential benefits of DMV fleets in urban logistics operations in terms of reducing total fleet energy consumption and fleet size.
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15.
  • Badia, Hugo, et al. (author)
  • Design and operation of feeder systems in the era of automated and electric buses
  • 2021
  • In: Transportation Research Part A. - : Elsevier BV. - 0965-8564 .- 1879-2375. ; 152, s. 146-172
  • Journal article (peer-reviewed)abstract
    • This paper evaluates the impact of vehicle automation and electrification on the applicability of fixed routes and door-to-door services to supply a feeder transit solution in suburban areas. These technologies will modify the current cost structure of the bus system depending on how mature they are, reducing operating costs and increasing capital costs. By means of a continuum approximation model, we evaluate the performance for users and agency of the two feeder strategies in different scenarios of technological development. The results show that automation has the main impact on the applicability between the two feeder alternatives while the effects of electrification are considerably smaller. The future applicability of door-to-door trips reaches wider ranges, although this change is especially significant under some circumstances of technology, service area and users. The expansion of this range is relevant in case the automated bus is mature enough (high reduction of operating cost and low vehicle acquisition price), the areas are small, the trips are short and the value of time is high. However, the results reveal that fixed routes will remain a competitive feeder solution in a wide range of scenarios. We identify that the demand density threshold grows sharply in front of any reduction of agency costs once its value is around 200-300 pax/km2-h. Therefore, flexible services will gain applicability especially in environments that allow reaching this threshold.
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16.
  • Badia, Hugo, et al. (author)
  • Feeder Transit Services in Different Development Stages of Automated Buses : Comparing Fixed Routes versus Door-to-Door Trips
  • 2020
  • In: Transportation Research Procedia. - : Elsevier B.V.. - 2352-1465. ; , s. 521-528
  • Conference paper (peer-reviewed)abstract
    • The arrival of automated vehicles could significantly reduce the operating cost of mobility services. This fact has encouraged researchers to propose door-to-door services instead of the current fixed routes. However, a comparison between these two alternatives is required in order to identify when (depending on the development degree of the automated vehicles) and where (depending on the characteristics of the area of service) the implementation of each service is the most competitive solution. This research compares the two types of transit services to supply first/last-mile solutions in suburban areas. By means of an analytical approach, the results show that fixed routes remain the most efficient alternative unless the new technology reaches a certain degree of development that allows a high reduction of operating costs. In this case, the applicability of door-to-door services will significantly increase under certain circumstances: small areas of service, short distance trips and high values of time.
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  • Badia, Hugo, et al. (author)
  • Shared e-scooter micromobility : review of use patterns, perceptions and environmental impacts
  • 2023
  • In: Transport reviews. - : Taylor & Francis. - 0144-1647 .- 1464-5327. ; 43:5, s. 811-837
  • Journal article (peer-reviewed)abstract
    • Recently, a new shared micromobility service has become popular in cities. The service is supplied by a new vehicle, the e-scooter, which is equipped with a dockless security system and electric power assistance. The relatively unregulated proliferation of these systems driven by the private sector has resulted in numerous research questions about their repercussions. This paper reviews scientific publications as well as evaluation reports and other technical documents from around the world to provide insights about these issues. In particular, we focus on mobility, consumer perception and environment. Based on this review, we observe several knowledge needs in different directions: deeper comprehension of use patterns, their function in the whole transport system, and appropriate policies, designs and operations for competitive and sustainable shared e-scooter services.
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  • Berg Wincent, Boel, et al. (author)
  • Access distance to e-scooters : Analysis of app use and trip data in Stockholm
  • 2023
  • In: Journal of Cycling and Micromobility Research. - : Elsevier. - 2950-1059. ; , s. 100004-100004
  • Journal article (peer-reviewed)abstract
    • Users’ access distance to shared micromobility services is an important component of travel patterns, a determinant of travel choices, and input to determining service catchment areas. Users’ willingness to walk to shared micromobility vehicles is increasingly relevant as policymakers regulate shared free-floating e-scooters to designated parking zones. This paper proposes a novel approach to analyze access distances of e-scooters users based on e-scooter app use and trip data for Stockholm, Sweden. Euclidean access and map-based walking distances are derived from the distances between the location where the users opens the app to search for an e-scooter and the trip’s origin. Variations in access and walking distances are analyzed based on time of day, day of week, proximity to public transportation, and geographical distribution. Users walk on average 185 m and have an active walking time of 2.3 min with a median value of 95 m and 2.1 min. Shorter walking distances are observed for trips during the morning and lunch hours compared to the afternoon and at night. Furthermore, users walk slightly longer during the weekend compared to weekdays. Access distances are shortest within a 0–100 m radius to the nearest public transportation station. The suggested catchment area radius for shared e-scooters ranges from 128 m to 203 m, based on the 75th percentile of access distances. A policy implication is the importance of planning parking zones for e-scooters very close to public transportation to encourage multimodal trips.
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  • Berg Wincent, Boel, et al. (author)
  • Parkering av elsparkcyklar : Enkätundersökning av effekter och åsikter kring parkeringsförbudet i Stockholm, Göteborg och Malmö
  • 2023
  • Reports (other academic/artistic)abstract
    • Den 1 september 2022 infördes ett nationellt parkeringsförbud för elsparkcyklar i Sverige. Parkeringsförbudet innebar att delade elsparkcyklar enbart fick parkeras på särskilda platser för elsparkcyklar eller på cykelparkeringar. Stockholms stad och Malmö stad valde två olika utformningar av parkeringssystem för elsparkcyklar medan Göteborgs stad valde att skjuta upp införandet med hjälp av lokala trafikföreskrifter. Den här enkätstudien undersöker effekter och åsikter kring parkeringsförbudet hos delade elsparkcykelanvändare i Stockholm, Göteborg och Malmö. Syftet med enkätundersökningen är att förstå vad användarna har för önskemål och attityder relaterat till parkering av elsparkcyklar.Enkäten togs fram under hösten 2022 och skickades ut till elsparkcykeloperatören Vois användare i Stockholm, Malmö och Göteborg den 17 november 2022. Totalt inkom 1584 svar. 965 användare från Stockholm, 145 användare från Göteborg och 159 användare från Malmö ingick i det slutliga urvalet som låg till grund för resultatet. Majoriteten av användarna från alla tre städer var heltidsanställda, boende inom Vois driftzon, hade minst en eftergymnasial utbildning och var av manligt kön. Ålder och årsinkomst varierade något mellan städerna. Användare i Stockholm hade i genomsnitt använt 2,7 elsparkcykeloperatörer senaste sex månaderna medan användare i Göteborg hade använt 2,6 och i Malmö 2,2. I Stockholm och Göteborg var den vanligaste användarfrekvensen en eller flera gånger per vecka medan det i Malmö var en eller flera gånger per månad.Användarna i Stockholm och Malmö uppgav att deras användarfrekvens, gångtid och åktid för resor med elsparkcyklar hade påverkats efter 1 september. Användarna i Göteborg rapporterade i lägre utsträckning att deras användning hade påverkats efter 1 september 2022. Mest positiva till parkeringsförbudet var användarna i Stockholm medan användarna i Malmö var mest negativt inställda. Användarna upplevde att införandet av parkeringsförbudet inneburit mer ordning och reda i stadsmiljön men att tillgången till elsparkcyklar och möjligheten att parkera nära destination hade blivit sämre. Täthet och placering av parkeringszonerna för elsparkcyklar var de aspekterna som användarna i Stockholm och Malmö var mest missnöjda med samtidigt som det var de aspekterna som användarna i Göteborg ansåg som viktigast.Utöver täthet och placering frågades även användarna om storlek, tydlighet och enkelhet i parkeringssystemet samt hur operatörens app användes för att hitta parkering. Genomgående var användarna i Stockholm mindre missnöjda med utformningen av parkeringssystemet i jämförelse med användarna i Malmö. Det tolkas som att Stockholms stad har lyckats bättre med elsparkcykelparkering ur ett användarperspektiv. Fler än hälften av användarna i alla tre städer hade gjort en kombinerad resa med elsparkcykel och kollektivtrafik. Användarna i Malmö hade i högst utsträckning gjort multimodala resor med elsparkcykel och kollektivtrafik, men uppgav i lägst utsträckning att det var lätt att parkera vid en hållplats eller station. Möjligheten att parkera vid kollektivtrafik är viktigt att beakta om uppmuntran till multimodala resor med elsparkcyklar och kollektivtrafik är av prioritet.
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  • Berg Wincent, Boel (author)
  • Shared e-scooter usage patterns : Analysis of app and trip data
  • 2024
  • Licentiate thesis (other academic/artistic)abstract
    • There is an urgent need to shift the urban mode distribution towards public transportation, micromobility, and shared mobility as a critical step towards achieving sustainable cities. Micromobility, with shared e-scooters as the main driving force, has sprung up as a promising mode for cities since the late 2010s. The development has been rapid and concurrent, with many changes in policy and operations. Given the novelty of the mode, there is an evident need for planners, policymakers, e-scooter companies, and researchers to understand the usage patterns and potentials of shared e-scooters. This thesis studied shared e-scooter usage patterns by analyzing app and trip data. Paper I analyses the access and walking distance to shared e-scooters. The Euclidean access distance was calculated from app and trip data. A process was then developed to estimate map-based walking distance from the Euclidean distance by removing and replacing outliers with an approximated value. Finally, a catchment area for shared e-scooters was presented. The result show that the walking distance is short, the majority walking less than 95 m and 2.1 min.Paper II evaluated shared e-scooters as a last-minute mode, a mode used as a way to mitigate the risk of late arrival. The study was based on the assumption of a preferred arrival time, which was tested where there was an associated risk of arriving late and when the assumed preferred arrival time shifts. Trip characteristics(speeds, distances, ride times, and trip frequency) of last-minute trips were analyzed and identified. The result show a peak in the number of trips ending before the full hour of the morning. These trips are infrequent on the user level and have lower average ride duration and higher average speeds, indicating an larger share of last-minute trips.
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25.
  • Burghout, Wilco, et al. (author)
  • Multimodal Traffic Management : Project Report
  • 2024
  • Reports (other academic/artistic)abstract
    • Nya system för att kombinera transportsätt, till exempel Mobility as a Service (MaaS), ger nya möjligheter för trafikanter att växla mellan olika färdmedel. Samtidigt ger stora mängder data från såväl kollektivtrafiknätet som vägtrafiknätet samt multimodala data från mobilnäten i kombination med nya metoder för att uppskatta resmönster uppdelat på färdmedel möjligheter till en helt ny förståelse av multimodala resmönster i en stad. Att förstå hur multimodala resmönster utvecklas över tid ger nya möjligheter att utveckla effektiva verktyg för multimodal trafikledning.Det övergripande målet med projektet är att möjliggöra förbättrad tillgänglighet i transportsystemen genom effektivare trafikledning. Mer specifikt syftar projektet till att utveckla nya metoder för att uppskatta multimodal efterfrågan samt färdmedelsval och ruttval för multimodal trafikledning. Vidare har potentiella effekter av multimodal trafikledning analyserats.Projektet omfattar en litteraturstudie för analys av möjligheter och utmaningar med multimodal trafikledning. En explorativ analys baserad på oövervakat lärande har utförts för att identifiera typiska nätverksövergripande mobilitetsmönster. Val av rutt och färdmedel har predikterats med hjälp av statistiska modeller. Ett multimodalt dataset för fem veckor i Stockholm med storskalig mobilitetsdata för vägnätet och biljettdata för kollektivtrafiknätet har sammanställs för den explorativa analysen samt utvärderingen av rutt- och transportsättsmodellerna i samband med trafikledning.Baserat på litteraturstudien kan vi dra slutsatsen att koordinerad ledning av väg och kollektivtrafik har potential att minska trängseln och säkerställa effektiv förflyttning av resenärer i ett storstadsområde. Det finns flera motiv för multimodal trafikledning, där de viktigaste är potentiellt ökad efterfrågan för kollektivtrafik, förbättrad robusthet för transportsystemet och bättre prioritering av trafikledningsåtgärder. De största utmaningarna är samarbete mellan intressenter, informationsdelning och datafusion.Resultaten av den explorativa analysen baserad på oövervakad inlärning indikerar att klustring för att ta fram typdagar kan vara användbart vid scenarioutvärdering, men också fungera som input till korttidsprediktion, vilket ger en enkel och robust predikteringsmetod för länkflöden med ett MAPE-prediktionsfel på 10-15 %.Ruttvalsanalysen visar att en modell baserad på en ruttuppsättning med genererade rutter är mer responsiv för restidsförändringar än en modell baserad på endast observerade rutter, vilket är användbart för att förutspå effekten av olika trafikledningsåtgärder. En ruttvalsmodell med enbart restid är en vanlig förenkling att använda för att prediktera ruttval, men resultatet i denna studie visar att inkludering av fler attribut avsevärt förbättrar modellernas prestanda.Analysen av nätverksövergripande multimodala data för 5 veckor i Stockholm indikerar att det är möjligt att uppskatta hur transportsättsandelen mellan kollektivtrafik och andra transportslag varierar i tid och rum. En bättre förståelse för spatiotemporal variation av färdmedelsvalet är en viktig input till förbättrat beslutsstöd i multimodal trafikledning.
  •  
26.
  • Cats, Oded, 1983-, et al. (author)
  • How fair is the fare? Estimating travel patterns and the impacts of fare schemes for different user groups in Stockholm based on smartcard data : Final report for Trafik och Region 2018 SLL-KTH research project
  • 2019
  • Reports (other academic/artistic)abstract
    • There is a rapid increase in the deployment, acquisition and analysis of automated fare collection (AFC) systems, enabling a profound change in the ability to analyze high-volume data that relate to observed passenger travel behavior and recurrent patterns. The analysis of such passively collected data offers direct access to a continuous flow of observed passenger behavior at a large scale, saving expensive data collection efforts. For a review of the spectrum of applications – from strategic demand estimation to operational service performance measurements.The FairAccess project leverages on the availability of Access-kort data for the vast majority of trips performed in Stockholm County. The overarching goal of this project is to develop means to analyse empirically the impacts of policy/planning measures based on disaggregate passively collected smart card data. This involves a series of analysis and modelling challenges. We develop and apply a series algorithms to infer of tap-out locations, infer vehicles and travel times, and infer transfers to that journeys can be composed. Tap-in records have been matched with corresponding inferred tap-out locations and time stamps for about 80% of all records. Thereafter, we construct time-dependent origin-destination matrices for which segmentations can be performed with respect to geographical and user product features.We demonstrate the approach and algorithms developed by performing a before-after analysis of the fare scheme change from zone-based to flat fares. We analyse changes in travel patterns and derive price elasticities for distinctive market segments. The introduced fare policy delivered the desirable result of an increased ridership through improved convenience of the single-use products. Nevertheless, the significance of the service convenience component was underestimated, which resulted in the price adjustments being not in line with the mobility effects.The planning and development of the Stockholm public transport system must rely on the best empirical foundations available to support evidence-based decision-making and make the right priorities. To this end, the development and analysis performed in the FairAccess project lay a necessary foundation for further methodological developments and analyses such as on-board crowding evaluation, demand forecasting and identifying user groups.
  •  
27.
  • Cats, Oded, 1983-, et al. (author)
  • Unravelling Mobility Patterns using Longitudinal Smart Card Data : Final report for Trafik och Region 2019SLL-KTH research project
  • 2021
  • Reports (other academic/artistic)abstract
    • BackgroundThis project followed-up on a project called FairAccess which was granted in Trafik och Region 2018.In FairAccess, we processed Access card data and performed a sequence of inferences to derive timedependent origin-destination matrices for the entire Region Stockholm system. Tap-in records werematched with corresponding inferred tap-out locations and time stamps for about 80% of all records.Moreover, we implemented an algorithm to generate a journey database based on our transferinference method. We used the outputs of this process to evaluate the impacts of the fare schemechange (i.e. from zone-based to flat fare) on different user profiles. Access card products and zonalattributes were used for analysing policy impacts on different market segments.The “Unravelling Mobility Patterns using Longitudinal Smart Card Data” project was granted on May27, 2020 and the contract was signed on July 17, 2020. In this project, we capitalise on the capabilitiesof the inferences performed in previous work to conduct a series of market segmentation andadvanced data analytics to empirically analysis demand patterns for public transport in the StockholmCounty. The growing travel demand in Stockholm County is accompanied by an increased diversity ofsub-centres within the region as well as in individual travel patterns. It is thus increasingly importantto understand how demand patterns evolve over time, what the key market segments are and howdifferent users are affected by changes in service provision. The latter is studied in the contact of theopening of the Citybanan project.As stated in the SLL Research and Innovation Plan, the development of transport solutions for theStockholm region requires new knowledge regarding travellers’ needs and preferences, and theimpacts for different types of travellers. 
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28.
  • Cebecauer, Matej, et al. (author)
  • 3D Speed Maps and Mean Observations Vectors for Short-Term Urban Traffic Prediction
  • 2019
  • In: TRB Annual Meeting Online. - Washington DC, US. ; , s. 1-20, s. 1-20
  • Conference paper (peer-reviewed)abstract
    • City-wide travel time prediction in real-time is an important enabler for efficient use of the road network. It can be used in traveler information to enable more efficient routing of individual vehicles as well as decision support for traffic management applications such as directed information campaigns or incident management. 3D speed maps have been shown to be a promising methodology for revealing day-to-day regularities of city-level travel times and possibly also for short-term prediction. In this paper, we aim to further evaluate and benchmark the use of 3D speed maps for short-term travel time prediction and to enable scenario-based evaluation of traffic management actions we also evaluate the framework for traffic flow prediction. The 3D speed map methodology is adapted to short-term prediction and benchmarked against historical mean as well as against Probabilistic Principal Component Analysis (PPCA). The benchmarking and analysis are made using one year of travel time and traffic flow data for the city of Stockholm, Sweden. The result of the case study shows very promising results of the 3D speed map methodology for short-term prediction of both travel times and traffic flows. The modified version of the 3D speed map prediction outperforms the historical mean prediction as well as the PPCA method. Further work includes an extended evaluation of the method for different conditions in terms of underlying sensor infrastructure, preprocessing and spatio-temporal aggregation as well as benchmarking against other prediction methods.
  •  
29.
  • Cebecauer, Matej (author)
  • Enhancing Short-Term Traffic Prediction for Large-Scale Transport Networks by Spatio-Temporal Clustering
  • 2021
  • Doctoral thesis (other academic/artistic)abstract
    • Congestion in large cities is responsible for extra travel time, noise, air pollution, CO2 emissions, and more. Transport is one of the main recognized contributors to global warming and climate change, which is getting increasing attention from authorities and societies around the world. Better utilization of existing resources by Intelligent Transport Systems (ITS) and digital technologies are recognized by the European Commission as technologies with enormous potential to lower the negative impacts associated with high traffic volumes in urban areas.The main focus of this work is on short-term traffic prediction, which is an essential tool in ITS. In combination with providing information, it enables proactive decisions to decrease severity of congestion that occurs regularly or is caused by incidents. The main contribution of this work is to develop a methodological framework and prove its enhancing effects on short-term prediction in the context of large-scale transport networks. It is expected to contribute to more robust and accurate predictions of ITS in traffic management centers.Traffic patterns in large-scale networks, including urban streets, can be heterogeneous during the day and from day-to-day. This work investigates spatio-temporal clustering of heterogeneous data sets to smaller, more homogeneous data sub-sets. This is expected to produce more robust, accurate, scalable, and cost-effective prediction models. This thesis is the collection of five papers that contribute to enhancing short-term traffic prediction in this context. The clustering is recognized to boost prediction performance in Papers II, III, IV, and V. Paper II considers network partitioning and the last three papers study day clustering. The prediction models used across included papers are naive historical mean prediction models and more advanced prediction models such as probabilistic principal component analysis (PPCA) and exponential smoothing. Paper I considers and facilitates floating car data (FCD) as a cost-effective opportunistic source of speed and travel time data with extensive network coverage.Common practice in determining the number of clusters is to rely on internal evaluation indices, and these are very efficient but isolated from application. Paper IV tests this practice by also considering performance in short-term prediction application. Our results show that relying on these indices can lead to a loss of prediction accuracy of about 20% depending on the considered prediction model. Dimensionality reduction has a minimal effect on the resulting prediction performance, but clustering needs 20 times less computational time and only 0.1% of the original information.Finally, in Paper V, we look at similarities of representative day clusters recognized by speed and flows. Furthermore, the interchangeability of speed day-type centroids for flow when predicting speeds has proven to be robust, which is not a case for predicting flows by speed day-type centroids and observations.
  •  
30.
  • Cebecauer, Matej, et al. (author)
  • Generating Network-Wide Travel Diaries and OD Matrices Using Stockholm County Smartcard Data
  • 2020
  • Conference paper (other academic/artistic)abstract
    • Bakgrund: The public transport system in Stockholm extends across the greater Stockholm area, covering ca 6,500 km2 and 2.3 million inhabitants. The system includes 21 commuter train, metro, light rail and tram lines spanning ca 470 km, around 490 bus lines spanning ca 9,100 km, and a number of ferry lines (SLL 2016). The main ticketing system is the Access system, which uses electronic tickets that are loaded onto contactless cards. The system was introduced in limited scale in 2008 and the average number of ticket validations per day has since grown to 1.9 million in 2018. Trafikförvaltningen, Region Stockholm is collecting access smartcard data for several years. Just for year 2017 smartcard data consist of approximately 680 million tap-in records. The majority of tap-ins are recorded at metro gates (45%) and upon boarding buses (41%) while the remaining consists of commuter trains, trams, and ferries. Each card has a unique number, which allows it to be traced and construct the complete journeys and travel diaries. There is a big potential in using these data for different analysis, evaluation, and planning of public transport. We present the framework that enables processing of raw access data in fusion with AVL and network data to the network-wide travel diaries. Furthermore, the estimated OD matrices can be used for measuring the impacts of various interventions such as fare policy and service design changes. The inferred travel diaries also allow for extracting passenger loads for each vehicle trip segment across the network at the same resolution as the flow outputs of schedule-based transit assignment models.Metod: Tickets are validated upon access to stations or boarding of vehicles but not on egress or alighting. In other words, the Access system is “tap-in only”. We propose a method to estimate the alighting station in a multimodal public transport system, where tap-in transactions are observed in a complex network. Similar to previous literature it is assumed that the alighting occurs within a certain distance of the next transaction. Furthermore, vehicle and time inference using AVL data is performed. Trip elements are assessed individually resulting in individual travel diaries.Resultat och slutsats: The implemented inference algorithms and the derived travel diaries facilitate the construction of OD matrices that are essential input for services planning. The performance of the inferring algorithms is: for the alighting station: 87%; for travel time 70% using AVL data exclusively; considering all trips even without alighting station 86% of all journeys have inferred destination; from which 73% have travel time estimated.
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31.
  •  
32.
  • Cebecauer, Matej, et al. (author)
  • Integrating Demand Responsive Services into Public Transport Disruption Management
  • 2021
  • In: IEEE Open Journal of Intelligent Transportation Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 2687-7813 .- 2687-7813. ; 2, s. 24-36
  • Journal article (peer-reviewed)abstract
    • High-capacity public transport services such as metro and commuter trains are efficient during normal operations but are vulnerable to disruptions. To manage disruptions, bridging buses are commonly called in to replace the rail-based service along the disrupted lines. These often take significant time to arrive and are costly to keep stand-by. Demand-responsive transport such as taxi can respond to demand almost immediately but is costly and must usually be arranged by the individual travelers. This study examines the integration and potential role of demand-responsive transport in disruption management. The analysis considers the impacts of limiting the serving area, varying the number of available vehicles, pursuing ride-sharing, as well as a system-of-systems approach with collaboration between taxis and bridging buses. Results of computational experiments on the case study of Stockholm, Sweden reveal that integration of demand-responsive transport in the disruption management can bring large positive benefits in terms of average and maximum waiting times for travelers. This is especially the case for strategies including ridesharing. It is also shown that appropriate trade-offs between desired waiting times and costs can be achieved by collaboration of both bridging buses and demand-responsive transport. Additionally, more robust public transport with increased reliability during disruptions can increase sustainability as more people may choose public transport instead of private cars.
  •  
33.
  • Cebecauer, Matej, et al. (author)
  • Public transport disruption management by collaboration with demand responsive services
  • 2020
  • Conference paper (peer-reviewed)abstract
    • For large cities, public transport represents the backbone for commuters and thus plays a crucial role for society and for the economy. High-capacity public transport services such as metro and commuter trains are efficient during normal operations but are vulnerable to disruptions. Metro and commuter train disruptions can be handled in several ways. Very common are bridging buses that are called in to replace the rail-based service along the disrupted lines. These often take significant time to arrive and are costly to keep stand-by. Demand-responsive transport such as taxi can respond to demand almost immediately but is costly and must usually be arranged by the individual travelers. This study examines the integration and potential role of demand-responsive transport in disruption management. The analysis considers the impacts of limiting the serving area, varying the number of available vehicles, pursuing ridesharing, as well as a system-of-systems approach with collaboration between taxis and bridging buses. Results of computational experiments on the case study of Stockholm, Sweden reveal that integration of demand-responsive transport in the disruption management can bring large positive benefits in terms of average and maximum waiting times for travelers. This is especially the case for strategies including ridesharing. It is also shown that appropriate trade-offs between desired waiting times and costs can be achieved by collaboration of both bridging buses and demand-responsive transport. Additionally, it is expected that more robust public transport with increased reliability during disruptions can increase sustainability as more people may choose public transport instead of private cars.
  •  
34.
  • Cebecauer, Matej, et al. (author)
  • Real-time city-level traffic prediction in the context of Stockholm City
  • 2019
  • Conference paper (other academic/artistic)abstract
    • Background: The ongoing POST (Prediktions- och Scenariobaserad Trafikledning) project and the previous project Mobile Millennium Stockholm (MMS) provided tools and frameworks for real-time estimation and prediction of travel times on the city-level. City-level prediction of the traffic state as well as the traffic demand is important for both traveler information applications, such as online navigation, and traffic management applications, such as scenario evaluation of incident management strategies. However, city-level prediction is very challenging and requires efficient processing of large amounts of data. Here we present the recent research about effects of the clustering on the prediction performance and computational cost. Partitioning of the road network based on spatial and temporal attributes can potentially result in clusters that provide more robust and accurate prediction with reasonable bias-variance tradeoff. Methods: The effects of the clustering on the prediction performance are studied on the three case studies, representing different travel time sources in Stockholm city. First represent 15 MCS radars as the sources of travel times. Second 420 segments on the major roads around Stockholm with travel times estimated from the MCS radars. Third, travel times of 11,340 links processed from GPS data of 1,500 taxis operating in Stockholm. With the computational experiments, we studied different clustering approaches based on the day classification, functional classes, spatial locations and temporal attributes, and how they can effect the prediction performance and computational cost.Results: reveal that partitioning can significantly improve the prediction accuracy and rapidly decrease the computational cost and time.
  •  
35.
  • Cebecauer, Matej, et al. (author)
  • Revealing representative day-types in transport networks using traffic data clustering
  • Other publication (other academic/artistic)abstract
    • Recognition of spatio-temporal traffic patterns at the network-wide level plays an important role in data-driven intelligent transport systems (ITS) and is a basis for applications such as short-term prediction and scenario-based traffic management. Common practice in the transport literature is to rely on well-known general unsupervised machine-learning methods (e.g., k-means, hierarchical, spectral, DBSCAN) to select the most representative structure and number of day-types based solely on internal evaluation indices. These are easy to calculate but are limited since they only use information in the clustered dataset itself. In addition, the quality of clustering should ideally be demonstrated by external validation criteria, by expert assessment or the performance in its intended application. The main contribution of this paper is to test and compare the common practice of internal validation with external validation criteria represented by the application to short-term prediction, which also serves as a proxy for more general traffic management applications. When compared to external evaluation using short-term prediction, internal evaluation methods have a tendency to underestimate the number of representative day-types needed for the application. Additionally, the paper investigates the impact of using dimensionality reduction. By using just 0.1\% of the original dataset dimensions, very similar clustering and prediction performance can be achieved, with up to 20 times lower computational costs, depending on the clustering method. K-means and agglomerative clustering may be the most scalable methods, using up to 60 times fewer computational resources for very similar prediction performance to the p-median clustering.
  •  
36.
  • Cebecauer, Matej, et al. (author)
  • Revealing representative day-types in transport networks using traffic data clustering
  • 2023
  • In: Journal of Intelligent Transportation Systems / Taylor & Francis. - : Informa UK Limited. - 1547-2450 .- 1547-2442. ; , s. 1-24
  • Journal article (peer-reviewed)abstract
    • Recognition of spatio-temporal traffic patterns at the network-wide level plays an important role in data-driven intelligent transport systems (ITS) and is a basis for applications such as short-term prediction and scenario-based traffic management. Common practice in the transport literature is to rely on well-known general unsupervised machine-learning methods (e.g., k-means, hierarchical, spectral, DBSCAN) to select the most representative structure and number of day-types based solely on internal evaluation indices. These are easy to calculate but are limited since they only use information in the clustered dataset itself. In addition, the quality of clustering should ideally be demonstrated by external validation criteria, by expert assessment or the performance in its intended application. The main contribution of this paper is to test and compare the common practice of internal validation with external validation criteria represented by the application to short-term prediction, which also serves as a proxy for more general traffic management applications. When compared to external evaluation using short-term prediction, internal evaluation methods have a tendency to underestimate the number of representative day-types needed for the application. Additionally, the paper investigates the impact of using dimensionality reduction. By using just 0.1% of the original dataset dimensions, very similar clustering and prediction performance can be achieved, with up to 20 times lower computational costs, depending on the clustering method. K-means and agglomerative clustering may be the most scalable methods, using up to 60 times fewer computational resources for very similar prediction performance to the p-median clustering.
  •  
37.
  • Cebecauer, Matej, 1986- (author)
  • Short-Term Traffic Prediction in Large-Scale Urban Networks
  • 2019
  • Licentiate thesis (other academic/artistic)abstract
    • City-wide travel time prediction in real-time is an important enabler for efficient use of the road network. It can be used in traveler information to enable more efficient routing of individual vehicles as well as decision support for traffic management applications such as directed information campaigns or incident management. 3D speed maps have been shown to be a promising methodology for revealing day-to-day regularities of city-level travel times and possibly also for short-term prediction. In this paper, we aim to further evaluate and benchmark the use of 3D speed maps for short-term travel time prediction and to enable scenario-based evaluation of traffic management actions we also evaluate the framework for traffic flow prediction. The 3D speed map methodology is adapted to short-term prediction and benchmarked against historical mean as well as against Probabilistic Principal Component Analysis (PPCA). The benchmarking and analysis are made using one year of travel time and traffic flow data for the city of Stockholm, Sweden. The result of the case study shows very promising results of the 3D speed map methodology for short-term prediction of both travel times and traffic flows. The modified version of the 3D speed map prediction outperforms the historical mean prediction as well as the PPCA method. Further work includes an extended evaluation of the method for different conditions in terms of underlying sensor infrastructure, preprocessing and spatio-temporal aggregation as well as benchmarking against other prediction methods.
  •  
38.
  • Cebecauer, Matej, et al. (author)
  • Similarity and Interchangeability of Flow and Speed Data for Transport Network Day-Type Clustering and Prediction
  • Other publication (other academic/artistic)abstract
    • Prediction of future traffic states is an essential part of traffic management and intelligent transportation systems. Previous work has shown that spatio-temporal clustering of traffic data such as flows or speeds into network day-types improves both the performance and the robustness of traffic predictions. Since some data types may not be available at a network-wide level, or only for certain periods, this paper investigates how similar such representative day-types are if based on different data types. The similarity of day-type clusters is evaluated with qualitative calendar visualization and two quantitative metrics, the Adjusted Mutual Information (AMI) which considers day-to-cluster assignments, and a new proposed Centroids Similarity Score (CSS) which compares centroids. The paper also explores the impact on flow and speed prediction performance of substituting one data type for the other in the clustering or classification phases. Using microwave sensor data from the Stockholm motorway network, our findings show that clusterings based on flows and speeds and across a range of clustering methods have reasonably high similarity. CSS is found to be a more relevant similarity indicator than AMI in the prediction application context. By capturing more relevant traffic state information, flow-based clustering and classification are robust for both flow and speed predictions, while speed-based clustering significantly degrades flow prediction performance.
  •  
39.
  • Cebecauer, Matej, et al. (author)
  • Spatio-Temporal Partitioning of Large Urban Networks for Travel Time Prediction
  • 2018
  • In: 2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC). - : IEEE. - 9781728103235 ; , s. 1390-1395
  • Conference paper (peer-reviewed)abstract
    • The paper explores the potential of spatiotemporal network partitioning for travel time prediction accuracy and computational costs in the context of large-scale urban road networks (including motorways/freeways, arterials and urban streets). Forecasting in this context is challenging due to the complexity, heterogeneity, noisy data, unexpected events and the size of the traffic network. The proposed spatio-temporal network partitioning methodology is versatile, and can be applied for any source of travel time data and multivariate travel time prediction method. A case study of Stockholm, Sweden considers a network exceeding 11,000 links and uses taxi probe data as the source of travel times data. To predict the travel times the Probabilistic Principal Component Analysis (PPCA) is used. Results show that the spatio-temporal network partitioning provides a more appropriate bias-variance tradeoff, and that prediction accuracy and computational costs are improved by considering the proper number of clusters towards robust large-scale travel time prediction.
  •  
40.
  • Cebecauer, Matej, et al. (author)
  • Spatio-Temporal Public Transport Mode Share Estimation and Analysis Using Mobile Network and Smart Card Data
  • 2023
  • In: 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 2543-2548
  • Conference paper (peer-reviewed)abstract
    • Public transport plays a vital role in society and the urban environment. However, knowledge of its spatial and temporal shares is often limited to traditional travel surveys. Recently, there has been substantial progress in mobility data collection, including data from traffic, public transport, and mobile phones. Especially mobile network data is a large-scale and affordable source of high-level mobility records. Similarly, public transport smart cards or ticket validation data are being collected and made available in major cities. The contribution of this study is to unveil the potential of estimating public transport shares, by merging mobile and smart card data. Stockholm, Sweden, is used as a case study. We analyze and discuss spatio-temporal patterns of estimated public transport shares for Stockholm, using descriptive and cluster analysis. The typical representative day-types are revealed and analyzed. Finally, a regression analysis considering the weather and socioeconomic context is conducted. It provides a highly explanatory and predictive understanding of which factors impact the share of public transport in Stockholm. To conclude, combined mobile and smart card data offers a cost-efficient, large-scale, low spatio-temporal aggregation (capturing daily and hourly variations) alternative to traditional travel surveys for analyzing PT shares.
  •  
41.
  • Cebecauer, Matej, et al. (author)
  • Using flows or speeds in traffic pattern clustering and prediction : does the data type matter?
  • 2022
  • Conference paper (other academic/artistic)abstract
    • Data and knowledge of travel patterns play a key role in finding more cost-effective solutions and better utilization of existing resources to increase sustainability and decrease CO2 emissions, pollution, and noise. Understanding travel patterns and prediction of future traffic states is a central ingredient in Intelligent transport systems (ITS). Pre-clustering the data before applying the prediction models is a recommended practice. We consider in this work revealing day-to-day traffic regularities and grouping days into representative day-types based on their traffic similarities before training prediction models. Specifically for this presentation, we will present our recent work on day-type clusterings that concern the similarities and interchangeability of day-types recognized by flow and speed traffic measurements. We consider the speed and flow traffic measurements from the motorway control system in the highway system around Stockholm, Sweden. Different clustering methods are used and their performance is evaluated on short-term prediction models. The results reveal that day-types are similar across data types and clustering methods, and their similarity does not depend much on the number of clusters. As the baseline scenario, calendar-based day-types are used. The similarity is higher between flow and speed recognized day-types compare to calendar-based day-types. Considering short-term prediction performance, the data-driven day-types outperform calendar-based methods. However, for more sophisticated prediction models the difference becomes insignificant. The interchangeability of speeds and flows in traffic prediction is studied in a scenario where new days are classified into day-types based on speed observations. This could be particularly interesting for traffic management centers as speed observations may be collected in more affordable, sustainable, and scalable ways. However, results reveal that flow prediction is sensitive to whether the new day is classified to one of the clusters using speed instead of flow observations, and prediction performance is reduced by about 28%. This sensitivity can be overcome by using a more sophisticated prediction model. When classifying based on flow observations a more sophisticated model results in slight improvements in speed prediction.
  •  
42.
  • Chen, Haoye, et al. (author)
  • Mixed Integer Formulation with Linear Constraints forIntegrated Service Operations and Traveler Choices inMultimodal Mobility Systems
  • 2023
  • Conference paper (peer-reviewed)abstract
    • Multimodal mobility systems provide seamless travel by integrating different types of transportation modes. Most existing studies model service operations and travelers’ choices independently or limited in multimodal travel options. We propose a choice-based optimization model for optimal operations of multimodal mobility systems with embedded travelers’ choices using a multinomial logit (MNL) model. We derive a mixed-integer linear formulation for the problem by linearizing transformed MNL constraints with bounded errors. The preliminary experimental test for a small mobility on demand and public transport network shows the model provides a good solution quality.
  •  
43.
  • Chen, Haoye, et al. (author)
  • Pick-Up and Delivery Problem for Sequentially Consolidated Urban Transportation with Mixed and Multi-Pupropse Vehicle Fleet
  • 2022
  • In: Journal of Advanced Transportation. - : Hindawi Limited. - 0197-6729 .- 2042-3195. ; 2022
  • Journal article (peer-reviewed)abstract
    • Different urban transportation flows (e.g., passenger journeys, freight distribution, and waste management) are conventionally separately handled by corresponding single-purpose vehicles (SVs). The multi-purpose vehicle (MV) is a novel vehicle concept that can enable the sequential sharing of different transportation flows by changing the so-called modules, thus theoretically improving the efficiency of urban transportation through the utilization of higher vehicles. In this study, a variant of the pick-up and delivery problem with time windows is established to describe the sequential sharing problem considering both MVs and SVs with features of multiple depots, partial recharging strategies, and fleet sizing. MVs can change their load modules to carry all item types that can also be carried by SVs. To solve the routing problem, an adaptive large neighborhood search (ALNS) algorithm is developed with new problem-specific heuristics. The proposed ALNS is tested on 15 small-size cases and evaluated using a commercial MIP solver. Results show that the proposed algorithm is time-efficient and able to generate robust and high-quality solutions. We investigate the performance of the ALNS algorithm by analyzing convergence and selection probabilities of the heuristic solution that destroy and repair operators. On 15 large-size instances, we compare results for pure SV, pure MV, and mixed fleets, showing that the introduction of MVs can allow smaller fleet sizes while approximately keeping the same total travel distance as for pure SVs.
  •  
44.
  • de Almeida, Constanca Martins Leite, et al. (author)
  • Using the Sustainable Development Goals to Evaluate Possible Transport Policies for the City of Curitiba
  • 2021
  • In: Sustainability. - : MDPI AG. - 2071-1050. ; 13:21
  • Journal article (peer-reviewed)abstract
    • Cities across the world are becoming more engaged in tackling climate change and contributing to the achievement of international agreements. The city of Curitiba in Brazil is no exception. In December 2020, the city published PlanClima (Plano Municipal de Mitigacao e Adaptacao as Mudancas Climaticas), a climate plan developed with local and international organizations. PlanClima aims to guide policies and actions to mitigate and adapt to climate change. This study focuses on selecting and qualitatively evaluating transport policies that contribute to the city's 2030 climate and Sustainable Development Goals (SDGs). With PlanClima's analysis for the transport sector in mind, nine targets for 2030 are identified and connected to different transport policies. To evaluate the possible interactions between the policies and the different dimensions of the SDGs, four types of linkages were designed: essential, uncertain, limited, and opposite. These categories were developed to evaluate the several dimensions in which a policy can have a positive or negative impact. The results show that the implementation of zero emission zones/low emission zones, green public procurement, subsidy schemes for the uptake of clean vehicle technology, and the digitalization of the transport system through smarter public transport and digital platforms that couple bike sharing, taxis, and public transport are some of the measures that can contribute to the achievement of Curitiba's targets and ensure a positive impact on the sustainable development of the city. The study highlights how different policy instruments can contribute to achieve the city's targets, thus providing guidance to policymakers.
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45.
  • Ding-Mastera, Jing, et al. (author)
  • A latent-class adaptive routing choice model in stochastic time-dependent networks
  • 2019
  • In: Transportation Research Part B. - : Elsevier. - 0191-2615 .- 1879-2367. ; 124, s. 1-17
  • Journal article (peer-reviewed)abstract
    • Transportation networks are inherently uncertain due to random disruptions; meanwhile, real-time information potentially helps travelers adapt to realized traffic conditions and make better route choices under such disruptions. Modeling adaptive route choice behavior is essential in evaluating real-time traveler information systems and related policies. This research contributes to the state of the art by developing a latent-class routing policy choice model in a stochastic time-dependent network with revealed preference data. A routing policy is defined as a decision rule applied at each link that maps possible realized traffic conditions to decisions on the link to take next. It represents a traveler's ability to look ahead in order to incorporate real-time information not yet available at the time of decision. A case study is conducted in Stockholm, Sweden and data for the stochastic time-dependent network are generated from hired taxi Global Positioning System (GPS) readings. A latent-class Policy Size Logit model is specified, with routing policy users who follow routing policies and path users who follow fixed paths. Two additional layers of latency in the measurement equation are accounted for: 1) the choice of a routing policy is latent and only its realized path on a given day can be observed; and 2) when GPS readings have relatively long gaps, the realized path cannot be uniquely identified, and the likelihood of observing vehicle traces with non-consecutive links is instead maximized. Routing policy choice set generation is based on the generalization of path choice set generation methods. The generated choice sets achieve 95% coverage for 100% overlap threshold after correcting GPS mistakes and breaking up trips with intermediate stops, and further achieve 100% coverage for 90% overlap threshold. Estimation results show that the routing policy user class probability increases with trip length, and the latent-class routing policy choice model fits the data better than a single-class path choice or routing policy choice model. This suggests that travelers are heterogeneous in terms of their ability and/or willingness to plan ahead and utilize real-time information, and an appropriate route choice model for uncertain networks should take into account the underlying stochastic travel times and structured traveler heterogeneity in terms of real-time information utilization.
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46.
  •  
47.
  • Fu, Jiali, et al. (author)
  • Identification of workstations in earthwork operations from vehicle GPS data
  • 2017
  • In: Automation in Construction. - : ELSEVIER SCIENCE BV. - 0926-5805 .- 1872-7891. ; 83, s. 237-246
  • Journal article (peer-reviewed)abstract
    • The paper proposes a methodology for the identification of workstations in earthwork operations based on GPS traces from construction vehicles. The model incorporates relevant information extracted from the GPS data to infer locations of different workstations as probability distributions over the environment. Monitoring of workstation locations may support map inference for generating and continuously updating the layout and road network topology of the construction environment. A case study is conducted at a complex earthwork site in Sweden. The workstation identification methodology is used to infer the locations of loading stations based on vehicle speeds and interactions between vehicles, and the locations of dumping stations based on vehicle turning patterns. The results show that the proposed method is able to identify workstations in the earthwork environment efficiently and in sufficient detail.
  •  
48.
  • Fu, Jiali, et al. (author)
  • Optimizing fleet selection for earthmoving operations
  • 2013
  • In: ISEC 2013 - 7th International Structural Engineering and Construction Conference. - : Research Publishing Services. - 9810753551 - 9789810753559 ; , s. 1261-1266
  • Conference paper (peer-reviewed)abstract
    • Earthmoving operations often involve a large number of specially designed equipment with significant purchasing/leasing prices, high operating and maintenance costs. Hence, choosing the right fleet is a major concern from the construction planners' point of view. This paper presents a methodology that combines discrete-event simulation and optimization to solve the optimal fleet selection problem for earthmoving operations. Two optimization objectives are formulated and solved using the proposed framework and a genetic algorithm: minimization of Total Cost of Ownership (TCO) and maximization of productivity. Further, a two-stage rating scheme is introduced to arrange the fleet configurations so that the optimization algorithm converges to a fleet with better second-stage performance while the first-stage performance remains at the same level. The case study shows that the proposed mechanism can effectively allocate a local optimal equipment combination for earthmoving operations and hence serve as an efficient tool for construction management.
  •  
49.
  •  
50.
  • Harahap, Fumi, 1983-, et al. (author)
  • Policy Tools for Electric Vehicle Adoption in Curitiba City
  • 2023
  • In: Proceedings of the International Conference “Sustainable Built Environment and Urban Transition”.
  • Conference paper (peer-reviewed)abstract
    • The role of electric vehicles (EVs) in more sustainable cities is widely recognized, with their adoption increasing rapidly. Most governments have targets for continued EV adoption rate growth, and some plan to ban fossil-fuelled vehicles altogether. Yet, in most countries, including Brazil, the proportion of EVs among new vehicles sold remains low. EV adoption poses multiple technological, economic and social challenges that require targeted policy mechanisms. This study assesses policy measures to expedite EV adoption for road transport decarbonisation and sheds light on the critical role of EVs in sustainable urban development. We explore electric mobility challenges in urban areas, focusing on the case of Curitiba City in Brazil. We investigate existing challenges and barriers to policy implementation in Curitiba and successful interventions in cities worldwide to identify suitable policies for Curitiba. The study uses in-depth interviews with relevant stakeholders to examine policy tools, including financial, legal, knowledge-based, and societal instruments. The study recommends complementary instruments and measures to accelerate their adoption in Curitiba. Overall, the study's results, which identify criteria for policy design and implementation towards complete transport decarbonisation, should be valuable for decision-making in transport and mobility planning.
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