Classifying public transport service attributes based on their influence on overall traveler satisfaction can assist stakeholders and practitioners in introducing cost-efficient measures. To date most studies employed methods that were based on the assumption that the impact of service attributes on traveler satisfaction is entirely linear and symmetric. This study examines whether service attributes have a non-linear and asymmetric influence on the overall travel experience by employing the Three-factor theory (basic, performance and exciting factors). The analysis is conducted for different traveler segments depending on their level of captivity, travel frequency by public transport and travel mode used, and is based on a relatively large sample size collected for Stockholm County. Moreover, the estimated models control for important socio-demographic and travel characteristics that have been insofar overlooked. Results are presented in the form of a series of multi-level cubes that represent different essentiality of traveler needs which provide a useful methodological framework to further design quality service improvements that can be applied to various geographical contexts. Our findings highlight that a “one size fits all” approach is not adequate for identifying the needs of distinct traveler segments and of travelers using different travel modes. Furthermore, two-thirds of the attributes are consistently classified into the same factor category which entails important policy implications. This research deepens and expands the very limited knowledge of the application of the three-factor theory in the transport field.

Making Public Transport services more attractive and effective requires attractive and effective ticketing. This requires a clear understanding of user attitudes, needs and expectations. This study explored commuters' attitudes to fare collection and verification and the underlying factors, their acceptance of the policy of "No-ticket-purchase on-board" and their preferences for fare verification options. Commuters rated their agreement with 17 ticketing related statements in a cross-sectional questionnaire survey conducted along the corridor with the largest proportion of cross-county commuting in Sweden, Stockholm - Uppsala. Four sets of hypotheses were then tested. The average scores were normally distributed and hence analysed using a two-way ANOVA. A One-way chi-square test was conducted to determine the commuters' preference for fare verification approach. A t-test was used to analyse the perceived quality of ticketing and the commuters' reaction to the policy of "No-ticket-purchase on-board PT vehicle". Whilst the results showed that the commuters were relatively uniform in their attitudes, income, commuting route, ticket type and ticket purchase channel affected their attitudes. They were neutral to the policy of "No-ticket-purchase on-board". Their attitude to fare collection was more positive than that of fare verification and they showed a preference for automatic fare verification. The study highlights a number of policy implications and recommends further research on the feasibility of passive fare verification and on commuters' preferred options for fare verification.

The need for improved public transport (PT) ticketing in ever-growing deregulated PT markets has made well-designed integrated ticketing systems a priority area of intervention for PT service providers around the world. Yet, very little practical evidence of its impacts are reported in Sweden and in the world at large. The focus of this study was the impacts of the Movingo integrated ticketing scheme in terms of PT patronage, user satisfaction and the perceived quality of the ticketing set-up. Three travel surveys were conducted along the Stockholm-Uppsala route. Methods including logistic regression and correlated t-tests were used to analyse the samples. The findings suggest that the scheme made rail commuting more attractive resulting in an overall increase of about 24% in ticket sales with 3%–15% car commuters reporting that they patronised PT services after the project. The scheme also resulted in increased rail commuter satisfaction. The overall perceived quality of the ticketing set-up did not however improve due to interoperability challenges. Service providers’ uncertainty about equitable distribution of revenue among the participating service providers, interoperability challenges and the lack of interest among most of the participating service providers to sell Movingo tickets are some issues to be addressed.

Making Public Transport services more attractive and effective requires attractive and effective ticketing. This requires a clear understanding of user attitudes, needs and expectations. This study explored commuters’ attitudes to fare collection and verification and the underlying factors, their acceptance of the policy of “No-ticket-purchase on-board” and their preferences for fare verification options. Commuters rated their agreement with 17 ticketing related statements in a cross-sectional questionnaire survey conducted along the corridor with the largest proportion of cross-county commuting in Sweden, Stockholm – Uppsala. Four sets of hypotheses were then tested. The average scores were normally distributed and hence analysed using a two-way ANOVA. A One-way chi-square test was conducted to determine the commuters’ preference for fare verification approach. A t-test was used to analyse the perceived quality of ticketing and the commuters’ reaction to the policy of “No-ticket-purchase on-board PT vehicle”. Whilst the results showed that the commuters were relatively uniform in their attitudes, income, commuting route, ticket type and ticket purchase channel affected their attitudes. They were neutral to the policy of “No-ticket-purchase on-board”. Their attitude to fare collection was more positive than that of fare verification and they showed a preference for automatic fare verification. The study highlights a number of policy implications and recommends further research on the feasibility of passive fare verification and on commuters’ preferred options for fare verification.

Automated driving systems (ADS) have gained sizable attention over the last decade, promising safer, cheaper, and more accessible transportation. However, the discourse driving this research has not been thoroughly explored, with scant qualitative work detailing specific cases. To address this gap, this paper explores the motivations for the societal need for ADS research for the 500 most cited publications in the field, investigating explicit motivations (e.g., accident reduction), writing style, assumed likelihood of outcomes, and the text's tone. Qualitative and quantitative techniques are used, as well as the tool ChatGPT to investigate the large number of texts. The results show that the most common motivation is the emergence itself (‘ADS are coming, so they need to be studied’), followed by potential benefits such as accident reduction, congestion mitigation, increased comfort and productivity onboard, and environmental concerns. The tone of the publications is primarily neutral or slightly positive but with some deterministic descriptions like ‘ADS will lead to’ rather than more cautious language like ‘can’ or ‘may’. The results offer a glimpse rather than a comprehensive overview of the discourse on ADS within the research community. While the analysis might not capture the nuanced perspectives that readers encounter in publications focused on 'impacts', the reviewed publications remain the most cited works in the field, likely affecting the discourse to some extent.

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.

This project examined shared e-scooter trips provided by the operator Voi and used a trip planner to determine the potential alternatives if users had chosen to walk or utilise public transportation (PT) instead.

The analysis reveals that Voi trips are typically brief, with 71% lasting less than 10 minutes, usually covering 1-2 kilometres, and mostly occurring within central Gothenburg. The trip planner indicated that walking would be the best alternative for roughly half of the trips, while public transportation would be the main alternative for the other half. 

For the trips for which the trip planner suggested walking as the best alternative, 81% of them are less than 1 km long, meaning they could be alternatively covered by walking 15 minutes or less. Nonetheless, 89% of trips are faster with Voi, and 72% of them begin or end within 100 metres of a public transport stop, which strongly implies intermodal behaviour among e-scooter users and the use of e-scooters as a first/last mile solution; however, further research is necessary to support this statement.

Regarding the trips for which the trip planner suggested PT with no transfers, half of the users would have had to walk 500 m or more to access and egress PT and 80% of them started or ended within 100 m of a public transport stop, which can suggest users choosing Voi to replace a leg of their trips; or even the complete trip, considering that roughly half of these trips would have been theoretically cheaper with Voi instead of PT. Nonetheless, once again, more research is needed to support these hypotheses.

Generally, shared e-scooters hold the potential to complement public transportation services in densely populated urban areas, a notion supported by this study and prior academic and grey research. Even in the absence of parking regulations, users tend to initiate or conclude their trips near public transport stops, which can serve as a valuable guideline for developing parking policy.

In conclusion, shared e-scooters represent an important aspect of urban transportation that should not be overlooked. It is crucial to engage both existing and potential e-scooter operators in transportation planning to foster collaboration with municipalities, PT agencies and local communities. This collaborative effort should aim to promote multimodality, integrated ticketing solutions, and user-centric approaches that encourage a shift away from less sustainable transportation modes.

Föreliggande slutrapport är finansierad av Trafikverkets FoI portfölj, strategiska  initiativ,för projekt Självkörande eldriven stombuss på Tvärförbindelse Södertörn – En skalbarfallstudie (TRV 2019/118695). Partners i projektet är Trafikverket, Scania, Volvo, Keolis,KTH samt Sweco där även Trafikförvaltningen Region Stockholm, Nobina och projektTvärförbindelse Södertörn har bidragit till arbetet som pågått från maj 2020 till mars 2021.Ansvarig för projektet inom Trafikverket har varit Stora projekt.För att skapa en förståelse för konsekvenser av tekniska utveckling i relation tillnödvändiga fysiska och digitala åtgärder har tre scenarier tagits fram: Bus Driver Plus,Automation with Adaption och Automation Utopia. Dessa scenarier beskriver olika nivåerav automation och behov av kringliggande stödsystem. I det första scenario finns enförare ombord på bussen som tar över körningen vid farliga situationer. Det andrascenariot avser en självkörande buss utan förare där den fysiska infrastrukturen haranpassats genom ett införande av ett eget busskörfält. Det sista scenariot beskriver enframtid där bussen helt förlitar sig på digital teknik och en operatör kontrollerar körningenav flera fordon från ett avsides kontrolltorn.De tre scenarierna utvärderades genom en samlad effektbedömning, Trafikverkets metodför att utvärdera åtgärder. Resultaten visar att den största vinsten av automatisering kanhandla om resenärernas bekvämlighet och inte nödvändigtvis om att minimera kostnaderför förare. Antaganden om att resenärerna kan uppleva resan bekvämare är troligtvisöverskattade, men resultaten visar att även små förbättringar i bekvämlighet kan ge storasamhälleliga vinster.Scenariot där bussen har ett eget körfält innebär mycket stora kostnader och är troligtvisinte ekonomiskt försvarbart. Dessutom kommer enbart en busslinje att trafikeramotorleden som dessutom består av 3 tunnlar. Vidare är det inte säkert att den aktör somgör nödvändiga investeringar är den aktör som får ta del av de samhälleliga vinsterna. Iscenariot skulle Trafikverket stå för stora delar av investeringskostnaden, medan vinsten för personalbesparingar uppstår för Region Stockholm och kollektivtrafikresenärerna somåker längs sträckan.Projektet har även undersökt hur multimodala hubbar (nod som möjliggör smidigt bytemellan olika transportmedel) längs med förbindelsen kan stödja eldrivna och självkörandebussar. Det är viktigt att ny väginfrastruktur bidrar till en attraktiv kollektivtrafik därresenärer i första hand väljer buss istället för bil. För att eldrivna och självkörande bussarska införas behöver Region Stockholm ställa nya krav i upphandlingar för attåstadkomma en förändring i transportsystemet. Nya krav som skapar ekonomiskaincitament för operatörer som utför den operativa verksamheten över lång tid. Det är dockproblematiskt att ställa krav på eldrift eftersom det saknas tillgänglig infrastruktur iStockholm.Avseende självkörande fullängdsbussar är tekniken helt enkelt inte tillräckligt mogen idag.Dock tror många experter att självkörande bussar kommer att införas, både i stadsmiljöoch glesbygd, när tekniken och samhället är redo för det, gissningsvis kring år 2030.

Researchers struggle to create simple yet nuanced diagrams or short abstracts that are easily comprehendible by non-experts. Research articles may be our primary communication method, but they are generally difficult to understand, making them unsuitable for general communication. This paper investigates a rarely used method in transport research – vignettes – to convey research results and elicit implications for public planners. Historically, these vignettes have been designed using qualitative methods, e.g., the Delphi method or by researchers' review of trends. However, this paper uses two vignettes originating from quantitative results from a simulation model paper (Almlöf et al., 2022), investigating the impacts of self-driving technology. Rewriting the results into two short stories – vignettes – these stories then served as the starting point for semi-structured interviews and a workshop with six public officials in Stockholm, Sweden. The vignettes were used to understand what these results would mean to the participants and how they would combat potential problems connected to sustainability, given the vignettes. Finally, the interviews and the workshop were qualitatively analysed, and policy tools were identified that can steer the transport system towards societal goals. The vignettes were a powerful tool to help the participants envision a future with self-driving transport options and promote critical thinking regarding how each participant would be affected, given such a future. As such, vignettes should be further explored to help researchers investigate abstract subjects which participants may have difficulties understanding.

Self-driving vehicles have been hailed as a revolutionary force that will benefit society through increased accessibility and reduced accident rates. However, implementing such a new technological system will be complex, requiring immense societal adaptions and changes. In this paper, we analyse the challenges faced in implementing self-driving vehicles based on interviews with onboard operators and stakeholders responsible for the operations of self-driving buses in northwest Stockholm, Sweden. From these interviews, we suggest a framework for understanding which societal changes would be required to implement self-driving vehicles.

We highlight the complexities of self-driving and the sociotechnical perspective needed to understand the challenges of implementing self-driving vehicles, underscoring human drivers' complex and tacit knowledge. Further, we identify a crucial technological gap in the vehicles' understanding of context, suggesting that comprehensive self-driving operation requires a form of general intelligence beyond the current, specialised, driving-only intelligence. The findings presented in this paper pave the way for further research and efforts needed to enable broader adoption of self-driving vehicles and offer insights for policymakers to guide future legislation in self-driving transport. 

In conclusion, several adaptions are required to facilitate self-driving vehicles. However, policymakers are advised to uphold stringent transport requirements, regardless of human or machine drivers, and resist any pressures to unnecessarily relax regulations. Such a cautious approach will ensure the continued prioritisation of safety and efficacy without compromising the human norms and behaviours that are integral and necessary to transport systems. 

The public sector makes long-term investments in for example tram rail lines and highways based on forecasts of future travelling but generally do not consider the impacts of self-driving technology as a factor. Several papers have presented transport system wide simulations with self-driving cars, exploring changes in mode choice, energy demand or the potential for sharing. Demand traffic models have been used in several studies, looking at modal choice changes, but the general assumption is that the public transport service remains unchanged, despite a large potential for governments to enhance service or reduce costs. This paper examines the effects of self-driving technology on the transport system with Stockholm, Sweden as a case study, looking at four scenarios which were developed with input from 130 transport professionals from industry, academia and the public sector. Each of the scenarios include one "car" and one "public transport" mode, looking at changes in e.g. modal choice and person kilometers traveled. The national demand model Sampers is used for evaluation. The results indicate a decrease in walking and bicycling in all scenarios and a decrease in public transport travelling in scenarios with a taxi-like car service. Although this result would mean a shift from public transport to car travel, the majority of travel to and from central parts of Stockholm were still made by public transport.

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. 

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.

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.

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.

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. 

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.

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.

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.

The urban logistics transport system brings a significant burden to cities, as the transport-related externalities (e.g., CO2 emissions, noise, and congestion) affect the liveability of the environment and the health of the citizens. To contrast these externalities, urban logistics concepts (e.g., logistics strategies, different vehicle types and vehicle technologies) are being developed and implemented. However, in the literature, there is a lack of a comparative evaluation of different concepts. This evaluation provides useful knowledge for both public and private decision-makers in the system. The goal of this research is to close the knowledge gap by analysing the sustainability performance of urban logistics concepts. Using an existing framework of key performance indicators (KPIs), this study aims to evaluate four urban logistics concepts (i.e., consolidation, electrification, cargo bikes and automation) based on their sustainability performance. The inputs to the framework are findings from the literature, regarding the impact of the concepts on the indicators. These findings can be both qualitative and quantitative. To collect these findings, we performed a literature review on relevant case and simulation studies. The output of the framework is a sustainability performance assessment of the concepts, visualized graphically. The results of this work enable stakeholders to understand how urban logistics concepts can be effective in achieving sustainability. This knowledge can help the decision-making process, favouring choices that promote a sustainable system. 

Road freight transport systems are complex socio-technical systems where freight services are provided through various technological solutions, with the involvement of several stakeholders. Despite the benefits of road freight transport to the economy and society, it also has substantial drawbacks for our current and future society, such as greenhouse gas emissions, congestion, air pollution, noise and poor working conditions. Therefore, several transport concepts and policies, such as electric vehicles and carbon taxes, are being explored and implemented within the private and public sectors to mitigate the externalities of road freight transport systems and achieve more sustainable systems.

Understanding sustainability transitions requires a holistic approach that includes multiple dimensions of sustainability and the perspectives of various stakeholders. Therefore, this thesis uses a System Thinking lens to achieve a system-level understanding of sustainability. Moreover, the dynamics and feedback structures of sustainability transitions are considered in order to identify leverage points and avoid policy resistance.

This thesis aims to understand the impacts of transport concepts and policies on the sustainability of road freight transport systems. A mixed-method approach, including surveys, interviews, and System Dynamics modelling is used to study the impacts of COVID-19 regulations, electric trucks, city hubs, cargo bikes, automation and off-peak hour deliveries. Moreover, policies impacting the adoption of electric trucks and city hubs are explored.

This thesis's results indicate that collaboration is required to achieve sustainability. However, collaboration is complex since stakeholders often have conflicting goals. Applying System Dynamics as a modelling method allows for understanding the right place and time to implement various policies. In this thesis, the simulation of different policy scenarios enables the consideration of the consequences of these policies from both short- and long-term perspectives. This knowledge benefits decision-makers in the private and public sectors in making decisions that shift road freight transport systems towards sustainability.

Using 530 responses from an online questionnaire, this study aims to investigate the transition from physical to online shopping alternatives during the first wave of the COVID-19 pandemic at the individual level. The focus areas of the study are Sweden and Italy, two European countries that implemented contrasting prevention measures. This study analyses the impacts of the pandemic on the transition to online shopping activities, and identifies who among the respondents changed their shopping behaviour the most and how; and what the different shopping strategies are and who adopted them. Multivariate statistical analyses, including linear and binary logistic regressions and multinomial logit models, were used to analyse the dataset. In the analysis, the dataset was split between Italy and Sweden to take into account the contrasting prevention measures and the different social and economic backgrounds of the two countries; the results of this study confirm and highlight these differences. Moreover, the socio-demographic and household structures of the respondents were found to influence the amount and the direction of change in shopping behaviour during the first wave of the pandemic. The study also indicates some policies that can be implemented and/or further strengthened to increase the resilience of citizens in facing pandemics and to derive benefit from the behavioural changes that took place during the first wave of the pandemic.

Through consolidation, city hubs offer potential solutions to sustainability challenges in urbanfreight systems. However, the viability of such hubs has been questioned, as the willingness topay of businesses receiving goods has been an issue. This study employs a system dynamicsapproach to explore this willingness to pay in consolidation initiatives by quantifying thebenefits receivers can gain, thus bridging a gap in the literature. The system dynamics methodallows a holistic view of the system. Therefore, a quantitative model is built to explore thebehaviour of the businesses receiving goods and their interests in value-added services. Datafrom a case study in Stockholm is used as quantitative input. Moreover, sixteen businesses inthe area are interviewed to understand their needs and to create different scenarios. The analysisof the interviews reveals that the level of interest in value-added services varies depending onthe type of business. Four types of receivers are identified: large offices, small offices, largeshops, and small shops. The model results show that the main benefits for the receivers are timesavings in handling deliveries, leading to cost savings and the use of the city hub for storage.The results of this research can be used by decision-makers in the private and public sectors tounderstand the dynamics of city hubs and to formulate effective policies for the success of thesehubs. The originality of this study lies in the combination of the system dynamic approach andthe receivers’ perspective, which is relatively underexplored. The results can thus providevaluable insights in achieving viable consolidation solutions.

Because many systems are evolving into cyberphysical systems, it is essential to examine their impact on society. This article introduces a multidisciplinary course that provides an overview of how these systems contribute to sociotechnical change.

The transport-related externalities of the urban logistics system impact the urban environment and the health of the citizens: there is a need to improve the sustainability of the system. In this paper, we use a framework for sustainability performance abessment and a literature review to analyse the urban logistics concepts of electrification, consolidation, cargo bikes and automation. In the literature, there is a focus on pollution, while a holistic perspective on sustainability is lacking. A Sustainability Performance Abessment (SPA) matrix is the main result of this paper, as a tool for comparing the concepts and understanding how they can be combined to achieve integrated benefits. To make informed decisions, stakeholders need knowledge from a holistic perspective. The findings presented in this paper are a first step to achieving this required knowledge.

The urban logistics system greatly affects the liveability of the urban environment and the health of citizens through transport-related externalities. Urban logistics practices are being implemented to contribute to the sustainability of the urban environment. To make informed decisions, actors and stakeholders require knowledge about these practices and their impacts. This paper proposes a set of measurable indicators for sustainability assessment. For assessing sustainability, it is key to comprehensively consider sustainability dimensions. Therefore, the starting point of this paper is the Sustainable Development Goals (SDGs), to have a holistic view of sustainability, combined with existing indicators in the city logistics literature, to ensure relevance to the context. Moreover, it is important to consider the perspective of different actors and stakeholders. The novelty of this work is the definition of indicators from the perspectives of both the citizens as stakeholders and the logistics service providers as actors. The set of indicators is tested in two previous studies, showing that it is possible to evaluate the sustainability performance of urban logistics practices. Future work includes using the set of indicators in a real case study, to test the attainability and relevance of the indicators. This set of indicators should be used to evaluate urban logistics practices, with the aim of increasing the knowledge that actors in the urban freight transport system have regarding these practices. This knowledge can help decision-makers in the private and public sectors to make decisions that facilitate a more sustainable urban freight transport system. 

This paper explores the system-level impacts of electrification on road freight transport efficiency, as a complex concept with involvement of various stakeholders. Introducing electrification adds further complexity, bringing in new stakeholders, dynamics, and efficiencies. The paper utilises system dynamics modelling to understand the dynamics between different efficiencies and the impact of electrification. The results of the simulation model highlight that there are trade-offs between different kinds of efficiencies, and it is essential to achieve a balance. Moreover, worse-before-better behaviour should be expected, as electrification initially increases costs but has lower costs in the long term. The results point to two phases of E-truck adoption: during the first phase, the policy focus should be on expanding charging infrastructure; during the second phase, cost-focused policies become critical to boosting electrification. By understanding the impact of different policies, this paper offers valuable knowledge to decision-makers navigating the transition towards a more sustainable system. 

The urban logistics system causes negative externalities, such as pollution, noise and congestion. This study focuses on city hubs as a concept to reduce these externalities by improving consolidation and adopting zero-emission vehicles. Our research employs system dynamics as a method to uncover the dynamics and mechanisms related to the barriers and potentials of city hub implementation in Stockholm from the perspectives of the Logistic Service Providers (LSPs), the receivers and the public sector. Moreover, a mixed method approach is used for data collection, allowing us to extract the knowledge from the real implementation case, co-create a qualitative model as a Causal Loop Diagram (CLD) with the stakeholders involved in the system, and generalise the model. The mixed method approach includes a group model-building workshop, literature review, existing city hub analysis and stakeholder interviews. The main result is a CLD, visualising the dynamics of the introduction of city hubs. The CLD explores three potential incentives and policies: (i) the receivers change address; (ii) shippers oblige LSPs to use the hubs; (iii) the public sector gives monetary incentives to LSPs. The CLD presented in this paper establishes a validated system structure for the urban logistic system and facilitates the policymakers' understanding of the barriers to implementing city hubs and what policies could help their implementation.

Transport-related externalities have a negative impact on urban environments and public health. There- fore, urban logistic systems encounter significant challenges when it comes to sustainability. One urban transport strategy is city hubs, as these can achieve a more effective system with lower externalities. However, city hubs have yet to realise their full potential due to the challenges of their implementation, which are mainly economical. This paper investigates the dynamics of city hub implementation from the perspectives of the Logistic Service Providers (LSPs), the hub operator and the receivers of the goods. Drawing from qualitative and quantitative insights from a case study in Stockholm, a system dynamics model is built to understand these dynamics. The results of the model demonstrate that the city hub is economically sustainable only if collaboration is achieved between LSPs and receivers. However, even when this collaboration is achieved, the total system cost increases. When collaboration between actors cannot be achieved, the public sector’s involvement is crucial to achieving city hub adoption. The results also show that implementing an environmental zone where internal combustion engine vehicles are forbidden entry does not help the city hub adoption, as the share of the LSPs cost spent on vehicles is relatively low compared to salary cost and fuel cost. Therefore, policies favouring the actors involved in the scheme should be considered. The main contribution of this paper lies in identifying possible strategies and outcomes of city hub implementation within the studied area and providing guidance for policymakers on policies for city hub implementation. Moreover, the model can be adapted to other case studies by adjusting the input data, thereby serving as a tool for policymakers in different geographical contexts.

In mid-2023, we performed an experiment in autonomous buses in Stockholm, Sweden, to evaluate the role that social robots might have in such settings, and their effects on passengers' feeling of safety and security, given the absence of human drivers or clerks. To address the situations that may occur in autonomous public transit (APT), we compared an embodied agent to a disembodied agent. In this video publication, we showcase some of the things that worked with the interactions we created, and some problematic issues that we had not anticipated.

Truck drivers are required to stop and rest with a certain regularity according to the driving and rest time regulations, also called Hours-of-Service (HoS) regulations. This paper studies the problem of optimally forming platoons when considering realistic HoS regulations. In our problem, trucks have fixed routes in a transportation network and can wait at hubs along their routes to form platoons with others while fulfilling the driving and rest time constraints. We propose a distributed decision-making scheme where each truck controls its waiting times at hubs based on the predicted schedules of others. The decoupling of trucks' decision-makings contributes to an approximate dynamic programming approach for platoon coordination under HoS regulations. Finally, we perform a simulation over the Swedish road network with one thousand trucks to evaluate the achieved platooning benefits under the HoS regulations in the European Union (EU). The simulation results show that, on average, trucks drive in platoons for 37 % of their routes if each truck is allowed to be delayed for 5 % of its total travel time. If trucks are not allowed to be delayed, they drive in platoons for 12 % of their routes.

This paper considers the problem of hub-based platoon coordination for a large-scale transport system, where trucks have individual utility functions to optimize. An event-triggered distributed model predictive control method is proposed to solve the optimal scheduling of waiting times at hubs for individual trucks. In this distributed framework, trucks are allowed to decide their waiting times independently and only limited information is shared between trucks. Both the predicted reward gained from platooning and the predicted cost for waiting at hubs are included in each truck's utility function. The performance of the coordination method is demonstrated in a simulation with one hundred trucks over the Swedish road network.

Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefits of platooning, efficient dispatching strategies that facilitate the platoon formations across fleets are required. This paper presents a distributed framework for addressing multi-fleet platoon coordination in large transportation networks, where each truck has a fixed route and aims to maximize its own fleet's platooning profit by scheduling its waiting times at hubs. The waiting time scheduling problem of individual trucks is formulated as a distributed optimal control problem with continuous decision space and a reward function that takes non-zero values only at discrete points. By suitably discretizing the decision and state spaces, we show that the problem can be solved exactly by dynamic programming, without loss of optimality. Finally, a realistic simulation study is conducted over the Swedish road network with 5,000 trucks to evaluate the profit and efficiency of the approach. The simulation study shows that, compared to single-fleet platooning, multi-fleet platooning provided by our method achieves around 15 times higher monetary profit and increases the CO2 emission reductions from 0.4% to 5.5%. In addition, it shows that the developed approach can be carried out in real-time and thus is suitable for platoon coordination in large transportation systems.

We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

Electric trucks usually need to charge their batteries during long-range delivery missions, and the charging times are often nontrivial. As charging resources are limited, waiting times for some trucks can be prolonged at certain stations. To facilitate the efficient operation of electric trucks, we propose a distributed charging coordination framework. Within the scheme, the charging stations provide waiting estimates to incoming trucks upon request and assign charging ports according to the first-come, first-served rule. Based on the updated information, the individual trucks compute where and how long to charge whenever approaching a charging station in order to complete their delivery missions timely and cost-effectively. We perform empirical studies for trucks traveling over the Swedish road network and compare our scheme with the one where charging plans are computed offline, assuming unlimited charging facilities. It is shown that the proposed scheme outperforms the offline approach at the expense of little communication overhead.

Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and rest time regulations, known as hours-of-service (HoS) regulations. This letter studies the optimal charging problems of electric trucks with delivery deadlines under HoS constraints. We assume that a collection of charging and rest stations is given along a pre-planned route with known detours and that the problem data are deterministic. The goal is to minimize the total cost associated with the charging and rest decisions during the entire trip. This problem is formulated as a mixed integer program with bilinear constraints, resulting in a high computational load when applying exact solution approaches. To obtain real-time solutions, we develop a rollout-based approximate scheme, which scales linearly with the number of stations while offering solid performance guarantees. We perform simulation studies over the Swedish road network based on realistic truck data. The results show that our rollout-based approach provides near-optimal solutions to the problem in various conditions while cutting the computational time drastically.

As vehicles become electrified and more intelligent in terms of sensing, actuation and processing; a number of interesting possibilities arise in controlling vehicle dynamics and driving behavior. Over-actuation with inwheel motors, all wheel steering and active camber is one such possibility, and can facilitate control combinations that push boundaries in energy consumption and safety. Optimal control can be used to investigate the best combinations of control inputs to an over-actuated system. In Part 1, a literature study is performed on the state of art in the field of optimal control, highlighting the strengths and weaknesses of different methods and their applicability to a vehicular system. Out of these methods, Dynamic Programming and Model Predictive Control are of particular interest. Prior work in overactuation, as well as control for reducing tire energy dissipation is studied, and utilized to frame the dynamics, constraints and objective of an optimal control problem. In Part 2, an optimal control problem representing the lateral dynamics of an over-actuated vehicle is formulated, and solved for different objectives using Dynamic Programming. Simulations are performed for standard driving maneuvers, performance parameters are defined, and a system design study is conducted. Objectives include minimizing tire cornering resistance (saving energy) and maintaining the reference vehicle trajectory (ensuring safety), and optimal combinations of input steering and camber angles are derived as a performance benchmark. Following this, Model Predictive Control is used to design an online controller that follows the optimal vehicle state, and studies are performed to assess the suitability of MPC to over-actuation. Simulation models are also expanded to include non-linear tires. Finally, vehicle implementation is considered on the KTH Research Concept Vehicle (RCV) and four vehicle-implementable control cases are presented.

To conclude, this thesis project uses methods in optimal control to find candidate solutions to improve vehicle performance thanks to over-actuation. Extensive vehicle tests are needed for a clear indication of the energy saving achievable, but simulations show promising performance improvements for vehicles overactuated with all-wheel steering and active camber.

As vehicles become electrified and more intelligent in terms of sensing, actuation and processing; a number of interesting possibilities arise in controlling vehicle dynamics and driving behavior. Over-actuation with in- wheel motors, all wheel steering and active camber is one such possibility, which facilitate the control strategies that push boundaries in energy consumption and safety. Optimal control can be used to investigate the best combinations of control inputs to an over-actuated system. This paper shows how an optimal control problem can be formulated and solved for an over-actuated vehicle case, and highlights the translation of this optimal solution to a real-world scenario, enabling intelligent means to improve vehicle efficiency. This paper gives an insight into the Dynamic Programming (DP) as an offline optimal control method that guarantees the global optimum. Therefore the optimal control allocation to minimize an objective function and simultaneously fulfill the defined constraints can be achieved. As a case study the effect of over-actuation on the cornering resistance were investigated in two different maneuvers i.e. step steer and sine with dwell, where in both cases the vehicle assumes to be in steady state situation. In this work the cornering resistance is the main objective function and maintaining the reference trajectory is the constraint which should be fulfilled. A parameter study is conducted on the benefits of over-actuation, and depending on the type of over-actuation about 15% and 50% reduction in cornering resistance were observed during step steer and sine with dwell maneuver respectively. From a second parameter study that focused on COG position from a safety perspective, it is more beneficial for the vehicle to be designed to under-steer than over-steer. Finally, a method is described to translate the offline optimal results to vehicle implementable controllers in the form of both feed-through lookup-tables and rule-based feed-forward control.

While telecommuting (TC) research heavily discusses travel impacts of home-based TC, little is known about impacts of working from a neighborhood TC center on travel and non-travel activities and their energy requirements. We conduct a case study on the impacts of the work location (employer's office, TC center, home) on time use and travel using data collected in a neighborhood TC center in Stockholm. Our results show that telecommuters more frequently replaced working from the TC center for working from the more distant employer's office than for working from home. On TC center and home office days, diarists spent less time traveling, and on home office days more time on chores and leisure than on employer office days. When working from the TC center instead of the employer's office, telecommuters frequently used the same or more energy-efficient commute modes, e.g. biking instead of the car, which was feasible because the TC center is in the local neighborhood. However, when working from home, diarists mainly used the car for private travel. Thus, energy savings of TC can be increased by providing energy-efficient transport options or local access to non-work destinations to telecommuters. TC energy impacts depend also on changes to energy requirements for nontravel activities, for space heating/cooling/lighting at all work locations, and systemic TC effects (e.g. residential relocation), which can only be observed in the long term. Thus, future TC assessments should take an even broader perspective in terms of travel and non-travel activities, their energy requirements, and systemic effects.

IntroductionThe first wave of COVID-19 pandemic period has drastically changed people's lives all over the world. To cope with the disruption, digital solutions have become more popular. However, the ability to adopt digitalised alternatives is different across socio-economic and socio-demographic groups.ObjectiveThis study investigates how individuals have changed their activity-travel patterns and internet usage during the first wave of the COVID-19 pandemicperiod, and which of these changes may be kept.MethodsAn empirical data collection was deployed through online forms. 781 responses from different countries (Italy, Sweden, India and others) have beencollected, and a series of multivariate analyses was carried out. Two linear regression models are presented, related to the change of travel activities andinternet usage, before and during the pandemic period. Furthermore, a binary regression model is used to examine the likelihood of the respondents to adoptand keep their behaviours beyond the pandemic period.ResultsThe results show that the possibility to change the behaviour matter. External restrictions and personal characteristics are the driving factors of the reductionin ones' daily trips. However, the estimation results do not show a strong correlation between the countries' restriction policy and the respondents' likelihoodto adopt the new and online-based behaviours for any of the activities after the restriction period.ConclusionThe acceptance and long-term adoption of the online alternatives for activities are correlated with the respondents' personality and socio-demographicgroup, highlighting the importance of promoting alternatives as a part of longer-term behavioural and lifestyle changes.

Automated driving systems will be severely challenged under the unpredictable conditions of mixed traffic. Consequently, some form of human support remains essential in the foreseeable future. This challenge is particularly true for Shared Automated Vehicles, as these vehicles will likely not include any human driver onboard. When a Shared Automated Vehicle encounters a situation it cannot handle, a remote human operator will be needed to intervene. The remote operator can help the passengers to continue their journey by resuming vehicle operations. This thesis has investigated whether using a Head-MountedDisplay in comparison to a computer display improves Situation Knowledge for remote operators of Shared Automated Vehicles. This research adopted a user-centered design approach to develop a Head-Mounted Display and computer display prototype. In one of the first studies on a Shared Automated Vehicle remote control interface, this thesis considered implicit measurements of Situation Knowledge and did not focus on performance indicators. In a userstudy, twelve participants were given the task to determine the reason why theShared Automated Vehicle had stopped based on pre-recorded driving scenarios.Strong qualitative evidence indicates that a Head-Mounted Display canprovide remote operators with improved Situation Knowledge in comparisonto computer displays. To deepen the understanding of the performance andSituation Knowledge for remote operators of Shared Automated Vehicles undervarious conditions further research is necessary. Future studies can extendknowledge by assessing different scenarios and tasks in a live remote controlsituation, and develop and evaluate additional interface elements.

Automated driving systems will be severely challenged in the unpredictable conditions of mixed traffic. Consequently, some form of human support remains essential in the foreseeable future. This challenge is especially true for Shared Automated Vehicles (SAVs), as these vehicles will likely not include any human driver on-board. When an SAV will encounter a scenario it cannot handle, a remote human operator will need to intervene and help the vehicle and its passengers. In this study a user-centred design approach is used to study whether a Head-Mounted Display (HMD) interface can support such operators and provide them with additional spatial awareness. Two prototypes (an HMD and a computer display) are developed and evaluated using pre-recorded real-world scenarios. Twelve participants assessed three possible scenarios a remote operator may encounter. Among participants, the study found evidence of strong implicit spatial awareness when using an HMD interface.

To study future communication needs between pedestrians and shared automated vehicles (SAVs), an interface that communicates the intentions of SAVs to pedestrians was designed and implemented in a virtual reality (VR) environment. This enabled the exploration of behaviors and experiences of 34 pedestrians when encountering SAVs, both with and without the interface, in several street crossing situations. All pedestrians assessed the level of perceived safety and comfort directly after each encounter with the SAV. The results show that the pedestrians’ level of perceived safety and comfort is higher in encounters with the interface than in encounters without the interface. This may have a positive influence on the acceptance of SAVs, and implies that future SAVs may gain from this, or similar interface.

The successful adoption of a product or service by its target market or users relies on delivering a product or service in line with their needs and expectations. Failure to do so will likely result in a low rate of uptake or use of the product or service. This study sought to identify the criteria by which potential users of a first-/last-mile automated bus (AB) service would evaluate the service, and accordingly decide whether to use or disregard the service. This research investigated var-ious explanatory factors affecting users' perceptions of the service's quality and utility, and which enhanced or diminished their intentions to use it. The data analysed in this study was collected from a survey conducted in February and March of 2018 in Stockholm, Sweden, during a trial operation of a first-/last-mile AB service. Three-factor theory analysis, commonly used to analyse services, was applied to this data in order to identify users' core perceptions about the service, which in turn influence their intention-to-use the service. Structural equation modelling was used to identify the significant factors that influence the identified perceptions influencing the in-tention-to-use the service. This study found that different subgroups of users prioritised different attributes. Prospective users (with no prior experience with the service) were most concerned with the frequency of service. Their intention-to-use the service greatly increased when the service frequency is comparable to the service frequency of a regular public bus service. Experienced users' intentions to continue using the service greatly increased when the buses were made more comfortable. This study additionally found that users' perceptions of the service's quality were also influenced by numerous factors including the passenger's age, income level, preferred mode of travel for daily trips, preferred mode of travel for first-/last-mile trips, being tech-savvy or not, and their level of familiarity with automated driving technology.

Successful implementation of a first-/last-mile automated bus (AB) service depends on consumers' actual adoption of the service. Consumers, when decided to take an AB ride for the first time, shall rely on their expectation of the service and capabilities of the technology. After the first ride of the vehicle, their value assessments of the service are further refined based on their actual ride experiences. Whether the operators can retain the users highly depend on such assessment. Thus, it is immensely important, when investigating users' adoption behaviour of a first-/last-mile AB service, we take into account the longitudinal changes of the users' valuation of the service. This is the research gap that this study is contributing. During a first-/last-mile AB service trial in Stockholm, Sweden, a panel data involving 185 respondents was available for analysis. The first survey was shortly after the launch of the trialled AB service and the second one was four months later. Structural Equation Modelling was used to investigate the changes of users' judging criteria across different socio-demographic groups, due to initial usage and the subsequent usage. The results show that the concerns affecting the users to continue with the service change with an increase in the ride experience. Willingness-to-use of the experienced users was initially affected by their level of appreciation with the safety and travel time with the service. However, ride comfort became a dominant factor with increasing ride experiences.

Introduction Travel demand and travel satisfaction of a transport service are affected by user perceptions of the service quality attributes, and such perceptions should be included in studying user willingness-to-pay (WTP) for automated vehicle (AV) services. This study applied structural equation modelling with service quality attribute perceptions as latent variables affecting WTP. Objectives We investigated how WTP AV services are affected by socio-demographic characteristics, knowledge and experiences with AV, existing travel modes and particularly, perceptions of the associated service quality attributes. The AV services are: 1) on-demand personalised AV (PAV) service, 2) demand responsive shared AV (SAV) service, and 3) first-/last-mile automated bus (AB) service. Methods The data were collected from 584 potential users of a first-/last-mile AB service trial operated in Kista, Stockholm. Results Results show people hold different expectations towards each type of AV service. These expectations act as the minimum requirements for people to pay for the AV services. Respondents are found to be willing to pay more for PAV service if it is safe, provides good ride comfort, and is competitively priced relative to the price travelling by metro and train over a same distance. Other than service quality attribute perceptions, income level, existing travel modes for daily trips, familiarity with automated driving technology and AB ride experience are important factors affecting WTP for the AV services. Conclusion The developed model can be applied to understand expectations of potential users towards a new AV service, and to identify user groups who are willing to pay the service. New AV services can thus be designed sensibly according to users' actual needs.