Fordonsdata kan i framtiden vara till stor nytta för myndigheter på olika sätt. Än så länge samlar myndigheter in fordonsdata i begränsad omfattning. Det kan t.ex. handla om att genom offentlig upphandling pröva nya sätt för att kontrollera kvaliteten på utförd snöröjning. Trots att det finns ett intresse från både privata och offentliga aktörer att genomföra affärer kring fordonsdata är det ändå svårt för marknaden att ta fart. 

Frågan om hur fordonsdata kan kommersialiseras med offentliga aktörer som köpare har därför undersökts inom Drive Sweden Policy Lab i samarbete med CeViss-projektet (Cloud enhanced cooperative traffic safety using vehicle sensor data). CeViss-projektet har undersökt smarta kameror och hur de bl.a. kan användas för att varna andra förare för vilda djur vid vägen eller informera SOS Alarm om hur det ser ut vid en olycksplats. 

Förutsättningarna för lyckad kommersialisering kan sammanfattas under tre rubriker - affären, tekniken och juridiken. Vi ser att affären ligger i förmåga att erbjuda aggregerade data där olika datamängder korsbefruktas och därmed skapar ett större värde än de ingående datamängderna besitter var för sig. Kommersiella aktörer pekar på att rollen att aggregera data, eller förädla den, är mest intressant, eftersom det innebär en möjlighet att utveckla tjänster. En sådan tjänst förutsätter tillgång till en säker uppkoppling och överföring. Det är också resurskrävande att förädla data och styra rätt överföring, liksom att se över, anpassa och ta fram avtal som gör korsbefruktning av data och överföring av rätt data juridiskt möjlig. Här spelar individens integritet kontra samhällets behov av data en stor roll. Det är inte heller klart vilket behov aktörer inom olika samhällssektorer har av fordonsdata, samt hur dessa kommer att få tag i fordonsdata. 

Utmaningen för industrin ligger i att våga lita på att det finns en hållbar affär med myndigheten i längden, dvs. att det finns en tillräckligt stor betalningsvilja från samhällets sida även när data anses samhällskritisk viktigt. För att främja kommersialisering är det bra att börja med ett specifikt utvalt område för att utarbeta processer, avtal, tekniklösningar, affärs-modeller och så vidare. 

Geofencing hade kunnat vara en möjlighet att skapa de avgränsningar som behövs för en första affär, samtidigt som det skulle skapa tydlighet om var och när data samlas in från fordon. En sådan avgränsning hade också kunnat tjäna som en regulatorisk sandlåda för att utvärdera möjligheten till avtal som är hållbara över tid, det vill säga där det är rimligt att inom vissa gränser använda data på nya sätt eller för nya syften. 

Rapporten avslutas med en sammanställning av geofencing och datadelning ur ett juridiskt perspektiv samt en beskrivning av Drive Sweden Policy Lab. 

In this report, we have compiled our learnings and experiences of working with Policy Lab. Policy Labs have come about as an answer to the question "Can you work with policy and regulatory development in a better way than today?". Our answer to the question is a yes. Our hope with the report is that others will become interested and start their own Policy Lab. Abroad, there are many Policy Labs, but in Sweden there are only a few, which is why we believe there is room for more. There is not a given way to work with Policy Labs once and for all, but each Policy Lab is unique based on its context. Sweden's innovation agency Vinnova defines Policy Labs as follows: "Policy Labs can be explained as a group of actors with different competencies who want to develop a regulatory framework. In the Policy Lab, they use a set of user-centric methods and competencies to test, experiment, and learn in policy development."1 In our Policy Lab, we have worked in various research projects to: 1. analyse challenges/problems that arise between innovations, technology, market, and regulations, 2. develop one or more workable solutions and 3. interact with relevant actors to determine the next steps. What distinguishes our Policy Lab is that we never “own” the issue or solution. We must therefore always work with other actors who can take the results further. Our goal is to enable and skill people. This means that for us it is important to work concretely with real problems and needs owners and preferably test different solutions. We focus on the here and now perspective and not on what the future will look like in 10 years. It is about taking the next step forward towards the future, not creating the best rule, but instead creating the next rule. We also work consistently agile and use design as a method for problem solving. This means that the way we organize our work in the Policy Lab is circular and not linear. When it comes to using design as a method for problem solving, we use the concepts of "design thinking" and "double diamond". For us, it is also important that the members of the Policy Lab have different backgrounds and skills depending on what is needed in the individual project....

It will still be a few years before we will have autonomous buses driving city streets and squares without drivers. On the other hand, it should be possible to have autonomous buses in a depot at an early stage in order to ensure more efficient maintenance of the vehicles when they are not in service, while at the same time learning how to be part of future operations. Such buses would be type-approved for manual traffic (SAE level 0-2), but not approved for autonomous road operation (SAE level 4-5). During the span of a single day, the bus will therefore alternate between the regulations for enclosed (fenced depot) and non-enclosed (road) areas, between being autonomous and not autonomous.

The bus, which was previously a legal “static whole”, will now instead be tested based on two regulations depending on the environment it is in at any given time and level of autonomy. This is a completely new situation: that a bus is “dynamically divisible” from a regulatory perspective, which has significance in terms of who shall decide whether the vehicle is safe to use in a certain environment.

After analysing the challenges based on existing regulations, interviewing relevant authorities, arranging workshops with various stakeholders and meetings with experts in certification, our conclusion is that, in order to be considered safe in autonomous mode within the depot, the bus should be self-certified by means of CE marking according to the Machinery Directive1. This is the authors’ conclusion and not necessarily representative of the other parties involved in the project.

We predict that we will see more self-certification of autonomous vehicles in the future. Partly because there are such large international markets working in this way, such as in North America, and partly because it enables faster market introduction of dynamic vehicle concepts. With “dynamic vehicle concept” we mean vehicles that gain new areas of application by replacing the chassis or changing software settings and are thus converted from a bus to a truck or from a car to quadricycle. Maybe even several times a day.

Self-certification, however, will also increase the need for standardisation, both for processes and products. Processes may involve how a vehicle can be certified, particularly how the risk analysis should be carried out. In terms of products, standardised descriptions of the technology’s function will facilitate proprietary self-certification since operators know how to describe their own products, including how their certification should be structured based on the constituent certified components. Current regulations will also need to be updated if more vehicles are to be self-certified, such as the Machinery Directive.

Lastly, we would like to communicate the method used to reach our conclusions. The project has been carried out as a Policy Lab where we have brought together various stakeholders around a common challenge. This has enabled us to concretise both the challenge of autonomous vehicles within the enclosed area and our conclusions. The  method selected has also given relevant authorities the opportunity to familiarise themselves with how they should relate to tomorrow’s technology without having to present a view on how they will relate to a specific test or vehicle. In this way, Swedish authorities will be ready to adopt technical innovations once they are introduced to the market.

This report is structured so that Section 2 describes the current regulatory framework, particularly in terms of the distinction between the Machinery Directive and vehicle type-approval. Section 3 uses specific examples to describe business operations pertaining to autonomous buses in a depot. Section 4 presents the authors’ conclusions based on how the regulations relate to the specific details obtained from the depot pilot. Section 5 presents the full picture by relating our conclusions to what is happening internationally and how the national ordinance on autonomous vehicle trials on roads corresponds to international trends. Lastly, in Section 6, we provide a summary of what we consider to be the most important issues for which further work should be carried out.

It will be a few years before we have autonomous buses that drive around the city´s streets and squares without drivers. On the other hand, it should be possible to have autonomous buses in a depot at an early stage in order to have more efficient maintenance of the vehicles when they are not in services, while at the same time learning how to be part of the future operation. Such buses would be type-approved for manual traffic (SAE level 0-2), but not approved for autonomous road operation (SAE level 4-5).During one and the same day, the bus will therefore transfer between the regulations forfenced (depot) and non-fenced (road) areas, between being autonomous and notautonomous.The bus, which was previously a legal “static whole”, will now instead be tested based ontwo regulations depending on its current environment and level of autonomy. This is acompletely new situation, that a bus is “dynamically divisible” from a regulatory perspective, which in turn has consequences for who is to decide that the vehicle is safe to use in a certain environment.

After analysing the challenges based on existing regulations, interviewing relevant authorities, arranging workshops with various stakeholders and meetings with experts in certification, our conclusion is that the bus should be self-certified through CE marking according to the Machine Directive to be considered safe in autonomous mode within the depot. This is the authors´ conclusion and not necessarily representative for the other parties involved in the project.

Our prediction is also that we will see more of self-certification of autonomous vehicles in the future. Partly because there are such large international markets working that  way, such as the North America one, and partly because it enables a faster market introduction of dynamic vehicle concepts. With dynamic vehicle concept, we mean vehicles that gain new capacity by replacing the chassis or changing software settings and thus go from being a bus to a truck or from a car to a moped car. Maybe even several times a day.

But with self-certification, the need for standardization will also increase, both forprocesses and products. When it comes to processes, it can be about how to certify a vehicle, especially how to do the risk analysis. For products, standardized descriptions of the technology´s function will facilitate your own self-certification as you know how to describe your product, but also how to build your certification based on the included certified components. The current regulations will also need to be updated if more vehicles are to be self-certified, such as the Machine Directive.

Finally, we want to highlight the method used behind the conclusions. The project has been carried out as a policy lab where we have gathered different actors around a common challenge. In this way, we have anchored both the challenge of autonomous vehicles within the fenced area and on our conclusions in concrete details. The choice of method has also given relevant authorities the opportunity to familiarize themselves withhow they should relate to tomorrow´s technology without having to present a view on how they will relate to a specific test or vehicle going forward. In this way, Swedish authorities are ready to take on technical innovations once they are introduced to the market.

In this project, the Swedish Transport Administration wanted to have two different tracks investigated from a legal perspective. We have chosen to call the first track a “matchmaking service for freight” to optimize the utilization of available cargo space. There is an assignment from the government to the Swedish Transport Administration to work with this issue based on horizontal collaborations and open data. The second track is about the development of new technology enabling new ways of collecting railway data based on RFID and the possibility of filming passing trains, which in turn raises legal questions about how the Swedish Transport Administration can use collected data.

After analysing the two tracks based on current regulations, interviewing different actors, arranging workshops with different stakeholders, and meetings with experts in the fields, our conclusions are as follows:

So far, it is unclear who will be appointed to be matchmaker and how the matchmaking service is intended to work as the Swedish Transport Administration´s assignment will last for another ten years. Our assessments at this early stage of the Swedish Transport Administration´s assignment aims more to provide advice on how the matchmaking service can be designed in the future. Above all, we foresee that competition law will be a challenge as it regulates horizontal collaborations. In the future, it needs to be investigated more what benefit consumers get from the matchmaking service and how such service can be designed without distorting competition on the market. The matchmaking service is aimed for product owners. The interviews show that they are prepared to share data provided that they get a benefit from this. The interviews also show that they are not used to sharing data in such a way that is required for a matchmaking service to function properly. We therefore believe that work will have to be put on making the product owners understand the benefit of data sharing to facilitate the introduction of a matchmaking service, e.g. by showing good examples to get product owners to think in new ways and dare to take the step. It is also unclear what is meant by open data and how it is compatible with copyright/trade secrets. That part of the assignment needs to be further elucidated.

In our opinion, the Swedish Transport Administration has the copyright to RFID data, and it is also from a copyright perspective that the Swedish Transport Administration has so far shared RFID data (through contracts) with others. One hope with RFID is that the technology will make an impact on the entire European railway network, which in turn raises the question of how RFID data can legally be shared. Our assessments are that it would be possible to turn RFID data into open data to enable data sharing within the EU, but this is something that needs to be discussed further with all the actors involved.

Data collection by filming passing trains is still at an early trial stage. Above all, we see that more work needs to be done to make data collection compatible with the GDPR and the Swedish Camera Surveillance Act. When trains are filmed, information is also collected about the load on the wagons. We see that this can lead to safety risk, which need to be addressed in the future work.

This paper explains the methodological approach of policy labs as used in applied research projects on autonomous vehicles in Sweden. While introducing new technologies we need to ensure that regulations and policies keep up with the fast-paced technological development.  Policy labs is one way of managing the perceived conflict between technological innovation and existing regulations. Within a policy lab, a wide range of stakeholders gather to solve the bottlenecks for innovations together. We show through three different R&D projects how the policy lab approach can be applied and which results, improvements and challenges it revealed for introducing autonomous vehicles.  

The rise of Artificial Intelligence has put data and data quality at the core of digitalisation. At the same time there seems to be a need to better understand what is meant by data quality and how to ensure it is at hand. Our first attempt to start the discussion was made at the Data Space Symposium in Darmstadt in March 2024. In terms of contribution this report is an increment to the slideshow by giving further examples of how data quality is defined and put into use at the same time as highlighting the contextual properties of data quality and the need for human judgement. We do this from a policy perspective, i.e. grounding our analysis in regulations and standards. Our analysis starts with the legal reasonings on data quality found in the AI Act and the European Health Data Space regulation. Our ambition is not to be exhaustive, there are more EU regulations and directives to consider in relation to data quality than the ones we cover here – such as the directive on Copyright in the Digital Single Market that introduces the concept of text and data mining; the Data and Data Governance Acts that enable standardised formats for making data interoperable across services; and the Digital Service and Market Acts that define responsibilities in terms of making data and information available. Among others. The same goes for standards on data quality which span across specific domains and disciplines. Coming back to our ambition, we believe it is important to raise the question to what extent data quality can be automatically assessed, as this is an ambition floated at various events and foras within the data community. While we think this can be achieved for specific and narrow contexts, we argue that data quality is a topic that still requires judgement and the competence to make assessments on a case-by-case basis.

The ambition of the European Union is to lead the way in digitalization. A cornerstone in fulfilling the ambition is the proposed AI Act. Our ambition with this contribution is to create awareness of how regulating Artificial Intelligence (AI) will affect mobility within the EU. The chosen definition of AI is broad enough to cover most software and the regulated topics will affect areas such as road traffic and public transport, safety components in machines but not vehicles. Such systems deemed to pose a high risk will need to be certified and CE-marked. It will also have an impact on the relationship between provider and user of AI systems, with a clear ambition to open the black box of business to enable compliancy with GDPR and handling of anomalies. At the same time, the AI Act opens up for using personal data for other purposes than originally stated during collection.

The initial proposal for an EU act regulating Artificial Intelligence, commonly referred to as the AI Act, has undergone substantial modifications under the Slovenian, French and Czech presidencies since it’s proposal by the Commission in spring 2021. As the content and details change over time it has become necessary to analyse to what extent the act will build trust towards AI as technology. In this position paper the ambition is to highlight one aspect of the act – the relation to trust – based on the version drafted for the general approach by the Council. Now, even reducing the analysis to one aspect is a complex task and the chosen points are the ones we have seen gaining most interest with the stakeholders we have interacted with. There are other points that could have been included but we have chosen to leave them out so as to not obscure the overall picture by all the details. The text does not follow a traditional structure of Introduction – Method – Results. Rather it represents nuggets we have dug out while exploring the proposed regulation, here analysed in relation to the notion of trust. We also assume that the reader has a basic understanding of the initial proposal. For those interested in a more detailed account of our method we recommend our contribution on agile principles for analysing upcoming regulations. Before we get going, we want to make it clear that while we are indebted to numerous representatives from commercial enterprises, public administrators spanning across EU departments to Swedish municipalities as well as researchers from different institutions, we are solely responsible for the claims and the analysis presented in this contribution.

The rapid pace of digitalization and the new opportunities for value creation has raised a concern that regulation is lagging behind and becoming an obstacle. A number of tools have been proposed in order to facilitate innovation that is aligned with existing or upcoming policies.

A specific case of both facilitating and regulating innovation is the EU’s proposed regulation of AI systems. The act not only poses legal requirements on providers and users of AI systems but also includes measures for facilitating innovation – the concept of regulatory sandboxes is defined with specific purposes together with legal exempts.

At the time of releasing our paper, the trilogue has reached a political agreement. This means the proposed AI Act will be, even though we do not yet have the final wording. By mapping the negotiation mandates of the European Commission, the European Parliament and the Council of the European Union against Swedish experiences of facilitating innovation and regulatory compliance in relation to AI, we still suggest launching pilots for regulatory sandboxes without delay.

Based on our own experiences from conducting policy labs and those reported on by others from their regulatory trials, we conclude that it takes time to grow confidence in defining a research agenda with other stakeholders and then strike the balance between facilitation and surveillance of innovation. Something that will require institutional learning and capacity building.

The mandate to foster and facilitate regulatory compliance as well as innovation, given to the public sector through the AI Act’s regulatory sandboxes, is disruptive. It changes the role and responsibilities for some national authorities, requiring the acquisition of new competences and resources, as well as for the private sector. When they team up with a competent authority the mandate to act becomes larger, as does the responsibility with regards to which kinds of innovation to drive.

Conducting trials in the current window of opportunity, between now and when the AI Act is in force, will create experiences that policy makers and stakeholders can draw on when creating the detailed guidelines for organising regulatory sandboxes. Adopting an incremental and iterative process enables a transition from learning the basics of selecting a case and finding relevant partners to detailing how to process data and sharing responsibilities and rewards.

In 2018 the Swedish Government released its strategy on AI, the national approach for artificial intelligence. The strategy focuses on three main areas – education, research and innovation – with the ambition that Sweden would be the best country in the world regarding applying AI. Two key areas were mentioned – the competitiveness of Swedish enterprises on a global market and the strengthening of the public sector.

Since then, the domestic discourse has changed, as Social-democratic lead governments have been replaced by a Conservative-Liberal government, the launch of ChatGPT, as well as the introduction of EUs Digital Decade with new targets for digitalisation and a proposed regulation of AI. We have therefore conducted a first evaluation of the strategy and the state of AI in Sweden. Based on official reports and interviews we recommend that the Swedish strategy on AI should …

… acknowledge the EU and accommodate for the upcoming regulations and resources within the Digital Decade,

… embrace the pluralism of Swedish governance and facilitate collaboration among authorities and different levels of administration,

... ensure the competence and the mandate of the public sector accordingly,

... be adaptable to changes in both the domestic and international discourse,

… investigate long-term funding solutions of strategic AI initiatives, and finally,

… define sustainable and ethical AI in order to facilitate responsible usage and development of AI as well as facilitate procurement.

This will require prioritisation of targets and initiatives as well as a way of assessing progress which is suitable for the Swedish context.

Swedish Shipping Policy Lab

Smart ships, or Maritime Autonomous Surface Ships as they are also known, have a great potential to advance shipping and sustainable development through optimisation of operations and maintenance. In situations that pose a risk to humans or where humans tend to lose their concentration, smart ships can also contribute to increased safety onboard and for the environment. In short, smart ships are suitable for operations that are dirty, dull and dangerous. The Swedish Shipping Policy Lab was an initiative to support on-going projects within smart shipping with policy-developing activities with the ambition to strengthen Swedish competitiveness. The project has actively strived for a systematic approach to how shipowners, technology developers and authorities among others can foster policy development and innovation in relation to smart ships. As an outcome the project has identified three policies related to the investigated cases (see Appendix G for more details): 1. Navigational assistance from land – A shared statement by the Swedish Maritime Administration and the Swedish Transport Agency on the role of navigational assistance from land and the need to further investigate the service before it can be regulated in more detail. 2. The Ljusterö Ferry – Certification of ferries is commonly done in relation to an established and consistent set of technical requirements. For smart ships such as the new road ferries procured for the Ljusterö-connection it is reasonable to complement traditional certification with a safety case to ensure that the ship is seaworthy. 3. Smart maritime drones – Ships less than five meters long that do not carry passengers are excluded from national rules regulating the supervision performed by the Swedish Transport Agency. As long as there is no explicit need to inspect a specific ship, the probability of a supervision is low. If an inspection were to incur, it is necessary to show how the smart ship and its operation complies to applicable regulation in terms of laws and collision avoidance. Despite the maritime sector having a long tradition of international governance there are still no international instruments explicitly for smart ships. A conclusion from the policy lab is that while such work is ongoing, there is room for the flag states and their authorities to develop and operate smart ships in accordance with national policies. Or, to paraphrase, smart ships seem suitable for operations that are dirty, dull, dangerous and domestic.

The Swedish policy lab for maritime autonomous surface ships, or smart ships, explored three use cases for developing policy in practice. The policies regard smart ships on national waters: one short-term written policy identifying the next shared step for two authorities to position remote navigational assistance as a new service, giving the maritime ecosystem one official position to relate to; one informal policy relying on a mutual trust, where information sharing between an operator of small, unmanned ships and the supervisory authority enables critical competence building; and one evolving policy on the process of certifying autonomous or remote operated functions using non-standardized technology. In conclusion, despite shipping being explicitly regulated internationally we found that there is substantial leeway for national policies regarding smart ships on national waters.

The Swedish policy lab for maritime autonomous surface ships, or smart ships, explored three use cases for developing policy in practice. The policies regard smart ships on national waters: one short-term written policy identifying the next shared step for two authorities to position remote navigational assistance as a new service, giving the maritime ecosystem one official position to relate to; one informal policy relying on a mutual trust, where information sharing between an operator of small, unmanned ships and the supervisory authority enables critical competence building; and one evolving policy on the process of certifying autonomous or remote operated functions using non-standardized technology. In conclusion, despite shipping being explicitly regulated internationally we found that there is substantial leeway for national policies regarding smart ships on national waters.

Our ambition is to give an overview of the mandatory involvement of notified bodies according to the AI Act and the Machinery Regulation. Specifically, we are interested in the cases when both acts are applicable for the same product.

That said, our analysis is not to be taken as legal advice but as policy research and we recommend the reader to cross-examine our conclusions by assessing the acts in relation to the products at hand. It is also worth remembering that the focus of the analysis is when a notified body is mandatory for CE-marking a product – we do not describe what is needed to meet requirements on technology and organisation, and it is always possible to opt to include a notified body in the conformity assessment even if it is not mandatory.

Another limitation is that we do not explore the full interaction between the AI Act and the Machinery Regulation, or how they interact with other policies relevant for CE-marking products intended for EU’s internal market.

Our main conclusions of the analysis are that:

• We should not focus on how the definition of Artificial Intelligence in the AI Act relates to the concept of ”fully or partially self-evolving behaviour using machine learning approaches” as introduced by the Machinery Regulation; but instead

• We should focus on when the Machinery Regulation mandates the involvement of a notified body and how that relates to the AI Act.

We also foresee an up-coming bottleneck in the availability of notified bodies capable of performing the duties in relation to both the AI Act and the Machinery Regulation, something that can have an effect on access to the internal market.

Motivation: In a broad sense data sharing onboard public transport vehicles is governed by two different business models – interoperable and free of charge access for some data versus data that is restricted to specific uses by commercial contracts and existing legislation. Under the Digital Decade the EU has proposed new legislation with the ambition to promote a single digital market. The question then arises – how will the upcoming regulations affect existing business models for data utilisation?

Method: We have investigated two different cases where existing technology meets upcoming EU legislation. The questions have been framed through dialogue with actors in the industry, to cover topics and questions that are both concrete and current. Using the policy lab methodology, we have investigated the possibility to re-use surveillance film from public transport vehicles for passenger counting. The analysis compares GDPR and the Swedish camera surveillance act with the proposed AI Act, to see what new possibilities or obstacles arise. We have also explored the changes that the Data Act may impose on different actors’ access to data derived from the batteries installed in an electric bus.

Results: The AI Act will not change the business models within the eco-system but facilitate access to more personal data (including personal data where GDPR otherwise would be a barrier), useful for training automated passenger counting. Those responsible for placing the system on the market will still need to ensure that they are compliant with GDPR in terms of processing personal data. In terms of the Data Act the outcome is more disruptive as the owner and user of a vehicle is entitled to all data representing their usage, free of charge, and this will impair existing business models for data access. It is also possible for multiple actors to be users, for instance if the vehicle is owned by a public transport authority and leased by an operator.

Discussion: Our analysis shows that while the impact of the Data Act can resonate with the ambitions behind the regulation in terms of making more data interoperable and available free of charge, it can also have the opposite effect. The latter is specifically the case where altruistic data sharing already is in place and the Data Act imposes standard contracts for and role-based restrictions towards utilisation. Both the AI Act and the Data Act are complex and often difficult to assess. In relation to the Data Act, the recitals were helpful for interpreting the application of articles and definitions. For understanding the relationship between the AI Act and GDPR we combined the legal analysis with prototyping the impacts and relied on sharing insights with other actors. This highlights the need for multiple ways of performing the data collection and analysis as well as the suitability of policy labs as a research method

Elsparkcyklar har potential att kunna bidra till positiva effekter i samhället. Men med friflytande elsparkcyklar följer också nya utmaningar. En del av dessa är relaterade till regelverk och policy.

Städer växer och förtätas, våra mobilitetsmönster förändras med teknologin som möjliggörare – men först och främst har personer ett behov av att ”lösa” mobilitet i vardagen utan att tänka för mycket på den. Det måste vara ”lätt att göra rätt” från början, och början och slutet av många resor är just fastigheter, antingen bostäder eller olika sorters verksamheter. Vilka mobilitetslösningar de erbjuder och möjliggör är därför avgörande för hur vi rör oss. Våra nuvarande planeringsnormer gynnar en bilburen mobilitet i och med att det finns regler om parkering per bostad resp. arbetsplats, så kallat parkeringstal (se plan- och bygglagen, förkortad PBL). På sistone har det dock varit ett flertal fastighetsaktörer och kommuner som har börjat experimentera med alternativ till parkeringen. Som så ofta inom begynnande innovationsområden saknas det kunskap och erfarenhet hos aktörerna, samt att nya samarbeten måste utvecklas och fördjupas. Under 2020 fick en grupp forskare på RISE möjlighet att undersöka a) hur en samarbetsprocess mellan två hittills oberoende aktörer eller branscher (”gränsland”) kan se ut och b) vilka som är de främsta utmaningar i det nya gränslandet mellan mobilitet och fastigheter, som exempel för ett gränsland som håller på att växa fram – bland flera andra som uppstår i omställningens spår. Till vår hjälp har vi haft flera experter som frikostigt delade med sig av kunskap och insikter, samt kollegor som har ett ben antingen i samhällsbyggnads- eller mobilitetsforskningen. I den här rapporten föreslår vi en process för samarbete mellan två branscher/ sektorer; och vi har sammanställt våra resultat och gör en bedömning av i vilken riktning mobilitet i fastigheter kommer ta vägen samt vilka förutsättningar som behöver förändras så för att bidra till att det blir just lätt att göra rätt, och därmed öka chanserna att lyckas med klimatomställningen i våra städer och samhällen.

The eSPARK project examines the sustainability profile of the popular shared e-scooters through policy analysis, usage data analysis, surveys, and life cycle assessment. Policies and attempts to regulate e-scooters in Swedish and European cities are studied and discussed with stakeholders. The LCA-results suggest that factors such as how e-scooters are collected and distributed, and the total ridden kilometers have significant impact on their environmental impact. The project also suggests different methods that can support cities to predict the geographical area of the e-scooters and offers insights about how e-scooters are used in the cities. Usage data and the surveys show that they are used by active people in areas with a lot of activities, especially restaurants and clubs. Users are likely to have a driving license, to frequently use a car but also to have a monthly pass for public transport. Thus, escooters have a potential to mitigate congestion on roads and public transport but may lead to more traffic on bike infrastructure instead.