Introduction The 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. Objective This 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. Methods An 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. Results The 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. Conclusion The 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.

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Mobility as a Service (MaaS), where different shared modes of transportation are bundled into one easily accessible service, plays an important role in the shift towards more sustainable transport systems. In this article, we present empirical research with the aim to understand how the barriers to increased shared travel with MaaS can be lowered. The concept of corporate MaaS (CMaaS) is introduced, and empirical results are presented from a study of CMaaS at a workplace of 14,000 employees in Sweden. The findings are based on 77 interviews with CMaaS users, performed in four iterative rounds using service design methods. Social practice theories are used as analytical lens to attempt to understand travel practices in the context of CMaaS. As CMaaS (and MaaS) are socio-technical systems, several perspectives need to be integrated in order to reach this understanding; all system components, including materials (e.g. the user application, the transport modes), competences (knowledge of how to use the materials), and meanings (understandings of travel habits, lifestyle choices, and employer relations) need to be analysed. Through this analytical lens, three barriers to adoption of CMaaS and sustainable transport were identified: inadequate integration of the internal transport system with external transport systems; corporate policy, culture and norms that conflict with using the services; and system limitations due to laws and regulations. All these barriers are also relevant for understanding MaaS services in general.

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.

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Road freight transport is believed by many to be the first transport domain in which driverless (DL) vehicles will have a significant impact. However, in current literature almost no attention has been given to how the diffusion of DL trucks might occur and how it might affect the transport system. To make predictions on the market uptake and to model impacts of DL truck deployment, valid cost estimates of DL truck operations are crucial. In this paper, an analysis of costs and cost structures for DL truck operations, including indicative numerical cost estimates, is presented. The total cost of ownership for DL trucks compared with that for manually driven (MD) trucks has been analyzed for four different truck types (16-, 24-, 40-, and 64-ton trucks), for three scenarios reflecting pessimistic, intermediate, and optimistic assumptions on economic impacts of driving automation based on current literature. The results indicate that DL trucks may enable substantial cost savings compared with the MD truck baseline. In the base (intermediate) scenario, costs per 1,000 ton-kilometer decrease by 45%, 37%, 33%, and 29% for 16-, 24-, 40-, and 60-ton trucks, respectively. The findings confirm the established view in the literature that freight transport is a highly attractive area for DL vehicles because of the potential economic benefits.

Road freight transport is a key function of modern societies. At the same time, road freight transport accounts for significant emissions. Digitalization, including automation, digitized information, and artificial intelligence, provide opportunities to improve efficiency, reduce costs, and increase service levels in road freight transport. Digitalization may also radically change the business ecosystem in the sector. In this paper, the question, “How will digitalization change the road freight transport landscape?” is addressed by developing four exploratory future scenarios, using Sweden as a case study. The results are based on input from 52 experts. For each of the four scenarios, the impacts on the road freight transport sector are investigated, and opportunities and barriers to achieving a sustainable transportation system in each of the scenarios are discussed. In all scenarios, an increase in vehicle kilometers traveled is predicted, and in three of the four scenarios, significant increases in recycling and urban freight flows are predicted. The scenario development process highlighted how there are important uncertainties in the development of the society that will be highly important for the development of the digitized freight transport landscape. One example is the sustainability paradigm, which was identified as a strategic uncertainty.