| 1. |
- Kinene, Alan, 1991-
(författare)
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Decision Models for the Procurement of Subsidised Air Services
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Small communities or remote regions are usually ignored by airlines because they have insufficient passenger demand and the air services to and from these regions are unprofitable. Free market conditions would lead to the lack of air connectivity to and from remote regions, hence transportation authorities intervene by procuring air services to guarantee improved accessibility for these regions. The procurement of air services is done through subsidy schemes where the transportation authorities pay subsidies to airlines that provide these air services along the routes to and from remote regions. These routes are commonly referred to as subsidised routes. The procurement of subsidised air services (subsidised routes) involves two major tasks—the selection of routes to subsidise and the selection of airlines to serve these routes. These are the focus of this thesis. The overall aim of this thesis is to design decision support models that can be used by transportation authorities to select the routes to subsidise and to select airlines to serve these routes. First, we develop an optimisation model that selects the routes to be subsidised, by maximising the number of people that can reach a given destination under different accessibility criteria subject to a budget. The model is capable of handling multiple accessibility criteria. As input to this model, we develop a novel method for estimating the subsidies required for non-existing subsidised routes. Second, we develop an auction framework to provide decision support to transportation authorities when designing auctions for the procurement of subsidised air services. The auction framework has three steps: auction definition by the transportation authority, bid preparation by the bidding airlines, and winner determination by the transportation authority. We develop two optimisation models as part of the auction framework, a winner-determination model for selecting the bids with the minimum subsidies, and a bid preparation model that replicates the airline’s behaviour when preparing bids for subsidised routes. The bid preparation model has an objective of minimising subsidies subject to a minimum profit threshold. We additionally propose models to estimate the appropriate demand and the route-operation cost for subsidised routes, which are needed as input to the bid preparation model. We demonstrate the usefulness of the two decision support models using the Public Service Obligation (PSO) network of subsidised routes in Sweden. The results suggest that the optimisation model can be used to select a new network of subsidised routes with improved accessibility to given destinations (e.g., the capital and an international airport) at a lower subsidy cost than the current network of subsidised routes. Having a requirement on the maximum airfare but not the minimum number of flights provides a good trade-off between the current restrictive setup with requirements on both the minimum number of flights and the maximum airfare, and a setup of the tendering process with no restrictions.
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| 2. |
- Kinene, Alan, 1991-
(författare)
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Models for the Procurement of Subsidized Air Services : Conventional Aircraft and the Adoption of Electric Aircraft
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In liberalized air transportation markets, governments often adopt subsidy schemes through which they ensure air services along routes that are deemed commercially non-viable but economically and socially essential. The objective of these subsidized air service routes is to ensure a minimum level of services to outlying communities or remote regions that are difficult to access—by other modes of transportation—from the capital, other main cities or a hub airport yet can not be served commercially due to thin demand. Through these subsidy schemes, transportation authorities offer compensation—usually in form of subsidies—to airlines in exchange for air services. Subsidized air services face two main criticisms: their misuse, for example selecting routes that may sufficiently be served by other modes of transportation; and the excessive subsidies spent by transportation authorities. Addressing these criticisms is key for the planning of socially and economically efficient subsidized air service networks. However, decision support models to address these criticisms are scant in both literature and current practice. Furthermore, past studies have naturally focused on models specific to the existing aircraft technology (i.e, conventional aircraft) with no attention towards electric aircraft yet, (1) their uptake appears faster today than predicted, and (2) they are expected to be more environmentally friendly with zero CO2 emissions during operation) and cheaper to operate than conventional aircraft.This thesis develops decision support models using the conventional aircraft as well as electric aircraft. Specifically, the thesis contributes with optimization models that can be used by transportation authorities to select the routes to subsidize, to set appropriate level of service requirements that should be met by the airlines (while either minimizing the subsidies or total social cost), and to strategically plan for the adoption of electric aircraft on subsidized routes. The usefulness of the models is demonstrated through applications to the subsidized air service network in Sweden, and this gives three main insights. First, transportation authorities can use an optimization model to improve accessibility of outlying regions to given destinations and at lower subsidy cost. Second, having a requirement on the maximum airfare but not the minimum number of flights provides an appropriate set of service requirements that should be met by the airlines. Third, leveraging the many currently under-utilized regional airports during the adoption of electric aircraft has accessibility and infrastructure-investment benefits; however, the isolated adoption of a homogeneous fleet of electric aircraft with limited seat capacity, slow speed and short range capabilities is not sufficient to serve remote regions. In the short run—at least until the the battery technology develops further—a hybrid network consisting of both these electric aircraft and the larger, faster and longer range conventional aircraft can be leveraged to provide a better services to the people.
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| 3. |
- Liu, Chengxi, 1987-, et al.
(författare)
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En transportmodell med fokus på cykeltrafik : modellutveckling och scenarioanalyser
- 2019
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Ökad andel resor med hållbara färdmedel är en förutsättning för att kombinera fortsatt tillväxt med minskad resursförbrukning och miljöpåverkan. I många europeiska städer har cykel blivit ett alltmer populärt färdmedel under de senaste decennierna. Dagens storskaliga transportmodeller, som utgör viktiga verktyg för utvärderingar och samhällsekonomiska analyser, är dock oftast fokuserade på modellering av resor med bil eller kollektivtrafik. Den här rapporten presenterar en tur-baserad transportmodell med syfte att bättre modellera cykelresor. Nyheterna i denna modell är bland annat ett detaljerat cykelnät som innehåller mer än 200 000 länkar och att modellen nyttjar en mer detaljerad zonindelning. Jämfört med nuvarande verktyget för samhällsekonomisk analys av cykelåtgärder, GCkalk, beskriver modellen ett fullständigt utbud och efterfrågan för cykel på detaljerad geografisk nivå. Modellen har skattats på data från den senaste resvaneundersökningen i Stockholms län från 2015 och representerar därmed observerat resebeteende. Modellen beaktar även cykel som anslutningsfärdmedel till resor med kollektivtrafik. Därigenom behandlar modellen cykel- och kollektivtrafik både som konkurrerande och som komplementära färdmedel och modellen kan utvärdera effekten av en förbättring av cykelinfrastrukturen på både enbart cykelresande och på cykel som anslutningsfärdmedel till kollektivtrafikstationer. Modellen är validerad mot cykelräkningar i Stockholm stad från september och oktober 2015. Modellen har testats på sex scenarier valda från Stockholms stads investeringsplan. Resultaten visar att investeringarna har en begränsad effekt på överflyttning mellan färdmedel och en måttlig effekt på befintliga cyklisters ruttval, restid och generaliserad kostnad.
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| 4. |
- Allström, Andreas, 1978-, et al.
(författare)
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A hybrid approach for short-term traffic state and travel time prediction on highways
- 2016
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Ingår i: TRB 95th annual meeting compendium of papers.
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Konferensbidrag (refereegranskat)abstract
- Traffic management and traffic information are essential in urban areas, and require a good knowledge about both the current and the future traffic state. Both parametric and non-parametric traffic state prediction techniques have previously been developed, with different advantages and shortcomings. While non-parametric prediction has shown good results for predicting the traffic state during recurrent traffic conditions, parametric traffic state prediction can be used during non-recurring traffic conditions such as incidents and events. Hybrid approaches, combining the two prediction paradigms have previously been proposed by using non-parametric methods for predicting boundary conditions used in a parametric method. In this paper we instead combine parametric and non-parametric traffic state prediction techniques through assimilation in an Ensemble Kalman filter. As non-parametric prediction method a neural network method is adopted, and the parametric prediction is carried out using a cell transmission model with velocity as state. The results show that our hybrid approach can improve travel time prediction of journeys planned to commence 15 to 30 minutes into the future, using a prediction horizon of up to 50 minutes ahead in time to allow the journey to be completed.
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| 5. |
- Allström, Andreas, et al.
(författare)
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Calibration Framework based on Bluetooth Sensors for Traffic State Estimation Using a Velocity based Cell Transmission Model
- 2014
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Ingår i: Transportation Research Procedia. - : Elsevier. - 2352-1465. ; 3, s. 972-981
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Tidskriftsartikel (refereegranskat)abstract
- The velocity based cell transmission model (CTM-v) is a discrete time dynamical model that mimics the evolution of the traffic velocity field on highways. In this paper the CTM-v model is used together with an ensemble Kalman filter (EnKF) for the purpose of velocity sensor data assimilation. We present a calibration framework for the CTM-v and EnKF. The framework consists of two separate phases. The first phase is the calibration of the parameters of the fundamental diagram and the second phase is the calibration of demand and filter parameters. Results from the calibrated model are presented for a highway stretch north of Stockholm, Sweden.
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| 6. |
- Allström, Andreas, 1978-, et al.
(författare)
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Hybrid Approach for Short-Term Traffic State and Travel Time Prediction on Highways
- 2016
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Ingår i: Transportation Research Record. - Washington, DC, USA : The National Academies of Sciences, Engineering, and Medicine. - 0361-1981 .- 2169-4052. ; 2554, s. 60-68
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Tidskriftsartikel (refereegranskat)abstract
- Traffic management and traffic information are essential in urban areas and require reliable knowledge about the current and future traffic state. Parametric and nonparametric traffic state prediction techniques have previously been developed with different advantages and shortcomings. While nonparametric prediction has shown good results for predicting the traffic state during recurrent traffic conditions, parametric traffic state prediction can be used during nonrecurring traffic conditions, such as incidents and events. Hybrid approaches have previously been proposed; these approaches combine the two prediction paradigms by using nonparametric methods for predicting boundary conditions used in a parametric method. In this paper, parametric and nonparametric traffic state prediction techniques are instead combined through assimilation in an ensemble Kalman filter. For nonparametric prediction, a neural network method is adopted; the parametric prediction is carried out with a cell transmission model with velocity as state. The results show that the hybrid approach can improve travel time prediction of journeys planned to commence 15 to 30 min into the future, with a prediction horizon of up to 50 min ahead in time to allow the journey to be completed
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| 7. |
- Andersson, Angelica
(författare)
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Mode choice modelling of long-distance passenger transport based on mobile phone network data
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Reliable forecasting models are needed to achieve the climate related goals in the face of increasing transport demand. Such models can predict the long-term behavioural response to policy interventions, including infrastructure investments, and thus provide valuable pre-dictions for decision makers. Contemporary forecasting models are mainly based on national travel surveys. Unfortunately, the response rates of such surveys have steadily declined, implying that the respondents become less representative of the whole population. A particular weakness is that it is likely that respondents with a high valuation of time are less willing to respond to surveys (because they have less time available for such), and therefore there is a high chance that they are underrepresented among the respondents. The valuation of time plays an important role for the cost benefit analyses of public policies including transport investments, and there is no reliable way of controlling for this uneven sampling of time preferences. Fortunately, there is simultaneously an increase in the number of signals sent between mobile phones and network antennae, and research has now reached the point where it is possible to determine not only the travel destination but also the travel mode based on mobile phone network antennae connections. The aim of this thesis is to investigate if and how mobile phone network data can be used to estimate transportation mode choice demand models that can be used for forecasting and planning. Key challenges with using this data source in the context of mode choice models are identified and met. The identified challenges include uncertainty in the choice variable, the difficulty to distinguish car and bus trips, and the lack of information about the trip purpose. In the first paper we propose three possible model formulations and analyse how the uncertainty in the choice outcome variable would play a role in the different model formulations. We also conclude that it is indeed possible to estimate mode choice demand models based on mobile phone network data, with good results in terms of behavioural interpretability and significance. In the second paper we estimate models using a nested logit structure to account for the difficulty in separating bus and car, and a latent class model specification to meet the challenge of having an unknown trip purpose.
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| 8. |
- Andersson, Angelica, 1990-
(författare)
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Modelling long-distance travel demand by combining mobile phone and survey data
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Forecasts of the demand for long-distance travel are a key component enabling the calculation of social costs and benefits of policy actions such as infrastructure investments. Traditionally, such forecasting models have been based on travel survey data. However, response rates to travel surveys have been in decline for decades, calling into question whether the sample of respondents is really representative of the full population. As such, there is a need to explore alternative data sources. One promising alternative is mobile phone network data, which is collected without the need of active participation from the traveller. However, mobile phone network data in this thesis lacks trip and traveller specific information such as trip purpose, socio-economic information, travel party size and mode. Furthermore, it is difficult to distinguish between bus and car trips even at a later stage of data processing, as the two modes share the same infrastructure. The objective of this thesis is to investigate the use of mobile phone network data for long-distance mode choice modelling. More specifically, we investigate the specific aspects of mobile phone network data as a source of mode choice travel information in the first research paper of this thesis, how uncertainties connected to the identification of the used mode matter, and how it can be handled in the model. In the second research paper of this thesis, a full-scale Multinomial Logit mode choice model is implemented and evaluated, including the development of how to handle mobile phone network data-specific challenges in the dataset of this thesis, such as the lack of distinction between bus and car trips and the lack of trip purpose information. Once this full-scale mode choice model based only on mobile phone network data has been evaluated, a method for combining mobile phone network data with survey data is proposed in the third research paper of this thesis, and the joint model is compared to the mobile phone network data model in terms of behavioural credibility. Finally, it is investigated whether machine learning can be useful in modelling mode choices using the two data sources in the fourth research paper of this thesis. From the results of the papers included in this thesis, it is clear that it is possible to model mode choice based only on mobile phone network data, but that it is preferable to combine mobile phone network data with survey data, rather than to use any one data source separately. Either Multinomial Logit (MNL) models or Artificial Neural Networks (ANNs) can be used to model mode choices based on the two data sources. However, if ANN is selected for mode choice modelling, it is advisable to formulate the network based on the transport mode choice specific principles developed in the last paper of this thesis.
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| 9. |
- Breyer, Nils, 1988-
(författare)
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Analysis of Travel Patterns from Cellular Network Data
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Traffic planners are facing a big challenge with an increasing demand for mobility and a need to drastically reduce the environmental impacts of the transportation system at the same time. The transportation system therefore needs to become more efficient, which requires a good understanding about the actual travel patterns. Data from travel surveys and traffic counts is expensive to collect and gives only limited insights on travel patterns. Cellular network data collected in the mobile operators infrastructure is a promising data source which can provide new ways of obtaining information relevant for traffic analysis. It can provide large-scale observations of travel patterns independent of the travel mode used and can be updated easier than other data sources. In order to use cellular network data for traffic analysis it needs to be filtered and processed in a way that preserves privacy of individuals and takes the low resolution of the data in space and time into account. The research of finding appropriate algorithms is ongoing and while substantial progress has been achieved, there is a still a large potential for better algorithms and ways to evaluate them.The aim of this thesis is to analyse the potential and limitations of using cellular network data for traffic analysis. In the three papers included in the thesis, contributions are made to the trip extraction, travel demand and route inference steps part of a data-driven traffic analysis processing chain. To analyse the performance of the proposed algorithms, a number of datasets from different cellular network operators are used. The results obtained using different algorithms are compared to each other as well as to other available data sources.A main finding presented in this thesis is that large-scale cellular network data can be used in particular to infer travel demand. In a study of data for the municipality of Norrköping, the results from cellular network data resemble the travel demand model currently used by the municipality, while adding more details such as time profiles which are currently not available to traffic planners. However, it is found that all later traffic analysis results from cellular network data can differ to a large extend based on the choice of algorithm used for the first steps of data filtering and trip extraction. Particular difficulties occur with the detection of short trips (less than 2km) with a possible under-representation of these trips affecting the subsequent traffic analysis.
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| 10. |
- Breyer, Nils, 1988-, et al.
(författare)
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Cellpath Routing and Route Traffic Flow Estimation Based on Cellular Network Data
- 2018
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Ingår i: The Journal of urban technology. - : Taylor & Francis. - 1063-0732 .- 1466-1853. ; :2, s. 85-104
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Tidskriftsartikel (refereegranskat)abstract
- The signaling data in cellular networks provide means for analyzing the use of transportation systems. We propose methods that aim to reconstruct the used route through a transportation network from call detail records (CDRs) which are spatially and temporally sparse. The route estimation methods are compared based on the individual routes estimated. We also investigate the effect of different route estimation methods when employed in a complete network assignment for a larger city. Using an available CDR dataset for Dakar, Senegal, we show that the choice of the route estimation method can have a significant impact on resulting link flows.
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