Articles

The widespread adoption of smartphones, ridesharing and carsharing have disrupted the transport sector. In cities around the world, new mobility services are both welcomed and challenged by regulators and incumbent operators. Mobility as a Service (MaaS), an ecosystem designed to deliver collaborative and connected mobility services in a society increasingly embracing a sharing culture, is at the center of this disruption.

Understanding Mobility as a Service (MaaS): Past, Present and Future examines such topics as:

• How likely MaaS will be implemented in one digital platform app
• Whether MaaS will look the same in all countries
• The role multi-modal contract brokers play
• Mobility regulations and pricing models
• MaaS trials, their impacts and consequences

Written by the leading thinkers in the field for researchers, practitioners, and policy makers, Understanding Mobility as a Service (MaaS): Past, Present and Future serves as a single source on all the current and evolving developments, debates, and challenges. 

Mobility-as-a-Service (MaaS) is a service concept that integrates public transport with other mobility services, such as car sharing, ride sourcing, and bicycle sharing. The core idea is that intermediary digital services make it easier for users to plan, book, and pay for complementary mobility services, thereby facilitating less car-centric lifestyles. However, although MaaS has gained much interest in recent years, the concept has proven difficult to realize. Accordingly, there is a prevalent demand for knowledge on how to enable and push MaaS developments.

Conceptualizing MaaS developments as an innovation process that might contribute to a sustainability transition, this thesis sets out to improve the understanding of how public sector actors can facilitate action in the early phases and steer the innovation trajectory towards addressing long-term sustainability goals. The public transport authority in Västra Götaland (Sweden), and its attempts to facilitate MaaS developments, is used as a starting point. Three of its MaaS-related activities between 2016 and 2019 are analyzed based on participatory observation and stakeholder interviews. Additionally, the thesis draws on two qualitative studies of MaaS developments situated in Finland and Australia.

The thesis’ contribution to the research field of MaaS is threefold. Firstly, it explores expectations of MaaS. A majority of the actors involved in the studied MaaS developments reckoned that MaaS will support a modal shift away from private car use. Still, while some actors were confident that this will lower the negative externalities of personal mobility systems, others feared that it will reinforce social and environmental problems. Of note is that none of these views are yet backed by any extensive empirical evidence, the shortage of which is an ongoing challenge for MaaS developments. Secondly, the thesis identifies institutional factors that shape MaaS developments. The studied developments were enabled by novel information technologies and motivated by the need to lessen the negative impacts of private cars. Yet, the developments brought together actors that had not previously collaborated and challenged models of collaboration, business, and customer relations, which made them contingent on complex modifications within and beyond personal mobility systems. Thirdly, the thesis examines how the public sector governs MaaS developments. The governance approaches varied across Sweden, Finland, and Australia in terms of leading actors, methods of intervention, and underlying motivations, but were yet to deliver much tangible results for citizens in all three countries.

Based on these findings, the thesis proposes principles and pathways for MaaS governance. The principles advocate a broad set of activities to address all the institutional factors that impede MaaS developments. In contrast to the observed governance approaches, this includes activities aimed at strengthening mobility services and active mobility, and at weakening the private car regime. The pathways describe four roles public sector actors can take in MaaS developments – MaaS Promoter, MaaS Partner, MaaS Enabler, and Laissez-Faire – and illustrate how the method(s) of intervention can be adjusted between innovation phases. The principles and pathways thereby provide a comprehensive tool for understanding and enhancing public-private dynamics in MaaS developments.

Geographic forecasting of crime can be done by considering prior crime or by considering spatial risk factors, e.g., using risk terrain modeling (RTM). The present paper tests both methods, but primarily focuses on RTM and on increasing our understanding of forecasting by attempting to compare the spatial risk factors for where the number of crimes is high with the spatial risk factors for where the risk of victimization is high. This is performed by fitting negative binomial models on crime around bus stops and comparing them to the same models with the number of bus passengers as exposure variable. The models also take the surrounding environment into account by fitting multi-level models with neighborhood level predictors of concentrated disadvantage and collective efficacy. The results show that some types of facilities are risk factors for crime, but not for victimization. This results in new insights into how flows of people impact on forecasting, as for instance a school is a spatial risk factor for crime, while not being associated with an elevated risk per person. The results also show that the neighborhood level of collective efficacy is a stable and significant risk factor both for crime and for risk of victimization, highlighting a potential for better crime forecasting by combining different spatial and theoretical perspectives.

The aim of this paper is thus to add to the crime forecasting literature by considering differences between risk factors for crime and risk factors for crime per population at risk. The paper uses the methodological concept of risk terrain modeling (RTM), but for forecasting purposes the findings should be relevant more generally.

Reviewing previous studies on using computational models for analyzing the effect of transport policies on transportation systems shows that agentbased models have not been used much in spite of their great potential for simulating dynamic aspects of policy instruments and travel behavior. The main reason can be the need for a lot of input data which is hard to prepare for the modeler. This has led to limited use of agent-based models in previous studies and even in those studies the scope of simulation is limited to only particular scenarios. In this thesis, I proposed a general-purpose agent-based simulation model for urban transportation that supports simulation of a wide range of policy instruments. The proposed model is designed in a way that a large part of the input data can be generated automatically using online web-services. The thesis also reports an empirical study on using our proposed generalpurpose model together with on-line travel planners in agent-based simulation for predicting the effect of different policy instruments on travel behavior. The results from our empirical study showed that our generalpurpose agent-based model predicts 72% of the real travel decisions correctly. Furthermore, the results of the simulation for various scenarios and combination of them seem to be acceptable. Finally, we found out that the use of on-line services for data collection increases the speed and flexibility of the system for defining and running new scenarios. However, the scalability of using on-line services in simulation is constrained by limitations of online service providers. The main contributions of this thesis are a general-purpose agentbased simulation model for urban transportation and a novel approach to automatically generate input data to the simulation using online travel planners and other web-services. This novel approach mitigates the challenge of agent-based simulation as a data-intensive method. This can lead to more widespread use for agent-based simulation in solving complex and realistic transportation scenarios. Another contribution of this thesis is on visualization of simulation output. One of the main challenges of using simulation systems by transport planners and decision makers as end-users is to understand the complex output of the simulation. In this thesis, I empirically demonstrated how the usability of a freight transport simulation system is improved by adding a visualization module that illustrates the results of the simulation for the end-users.

The aim of this paper is to study how local governments in Sweden view the role of public transport in society, and to investigate how public transport is used in a strategic capacity. By studying general policy documents, the ambition is to gain a wider understanding of the role of public transport based on the societal context it is situated in. Documents from 15 regions and 27 municipalities have been analysed by a qualitative content analysis. Results show that public transport is regarded as an important factor towards achieving other goals and other public values, particularly those related to economic and environmental issues; and that the social dimension is not as prioritised. Rail-bound public transport is often advocated, as are collaboration between organizations and integrated land-use and transport planning. However, the studied documents showed large overall differences in how counties and municipalities address public transport issues. It should be a priority in Sweden’s main steering documents to treat public transport consistently and give it the same priority as other societal functions—not least because Sweden’s treatment of public transport is a reasonable reflection of its overall society and can influence prioritisations and considerations in counties and municipalities across the country.

This paper analyses regional public transport planning in Sweden. The aim is to provide an insight into how policy objectives are translated into action and to investigate how public transport measures are evaluated. The analysis is based on interviews with civil servants in five Swedish regions. Cost-benefit analysis is sparsely used (if ever) and the results further indicate that planning and evaluation of public transport is to a large extent centred around monitoring on-going trends, e.g. patronage and market share. Such information seems policy-relevant, i.e. is commonly asked for by the political level. The informants do ask for more knowledge regarding various effects (mainly social). However, it is less certain whether or not this knowledge would be used for economic evaluation. Regional and local public transport systems are complex, and intrinsically linked to land use and long-term regional ambitions. Instead of asking how public transport planning should be carried out, following CBA analyses, we should perhaps ask how the economic analysis could be tuned so that it becomes relevant for public transport planning. We foresee that the broader role of the public transport system will increase goal conflicts between, and within, authorities.

Interchange stations with their connections between modes and lines are
central for a high quality public transport system. Bus access at the station needs
to operate reliably and efficiently in order to prevent congestion and queues. Here,
a discrete event simulation model of vehicle movements and interactions at bus terminals is developed and implemented. The model has a modular approach, where
common spatial sections at terminals are represented by modules that can be combined into various terminal layouts. These modules describe the events a vehicle may
go through in a particular section of the terminal, such as arriving to a bus stop or
stopping at a traffic light at the exit. The model can be used in planning processes,
both for new terminals and redesign of existing ones, and is able to describe the detailed movements and interactions between vehicles that occur at larger terminals.
The model is tested in a numerical experiment representing Norrkoping interchange ¨
station in Sweden. The experiment shows that the model is able to evaluate and compare different scenarios and can thus be a useful tool in planning processes.

A high quality railway service requires that all parts of the complete journey, from door to door, are well-functioning. This includes any transfers taking place, as well as last mile transportation to and from the railway station. Since the last mile often consists of local public transport, the access to this mode at stops and terminals and how well these are functioning are of great importance. A critical aspect is the capacity of the stop or the terminal in relation to the number of departures, where a higher capacity generally means an increase in size. At the same time it is desirable to limit the use of valuable land and keeping the facility as small as possible. The trade-off between capacity and size needs to be evaluated when designing stops and terminals.

In this study we have developed a discrete event simulation model of a combined bus and tram stop, which is a part of a larger multi-modal station. The objective of the study is to evaluate the modelling approach for the situation at hand. Of special interest are the complexities due to the different driving patterns of buses and trams. The developed model is capable of evaluating design alternatives and is applied in a case study of a stop at Norrköping railway station in southern Sweden. The model was found to realistically capture the various events occurring at such a stop and the case study further showed that the model is a useful tool in design evaluation.

It has been shown in previous research that regression modeling can be used in order to predict the number of bicycles registered by a bicycle counter. To improve the prediction accuracy, it has also been suggested that a long-term trend curve estimate can be incorporated in a regression problem formulation. A long-term trend curve estimate aims to capture those factors that are difficult, or even impossible, to explicitly model as input variables in the regression model. In the current paper, we present a regression-based approach for evaluating long-term trend curve estimates regarding their possibility to improve the regression prediction accuracy of bicycle counter data. We illustrate our approach by applying it on a time series recorded by a bicycle counter in Malmö, Sweden. For the considered data set, our experimental results indicate that a polynomial of degree two, which has been fitted to the time series, gives the best prediction.