Universal Design and Transport Innovations: A Discussion of New Mobility Solutions Through a Universal Design Lens

Society is changing. In the broader sense, we are looking at a reorganisation of goods and services available following the fifth technological revolution (Perez 2003), of which digitalisation is a core component. This also affects mobility. In addition, there is an established understanding that the centrepiece of 20^th-century mobility – the private car – represents an unsustainable way of providing mobility (Sheller and Urry 2006; Geels et al. 2012). This combination of digitalisation, which increases the opportunity space for innovation, and the narrative placing the private car as the centrepiece of our day-to-day mobility is challenged, creating a window of opportunity for new mobility solutions. Many have emerged to fill this space.

Looking back, the private car powered by an internal combustion engine was one of the most important technological advances of the 20^th century, and the most important change within day-to-day mobility. The car solved the problem of horse manure in city streets, and the technology provided an enormous growth in individual mobility. On the flip side, it also brought new challenges related to traffic safety, noise, urban sprawl and consumption of fossil fuels – and conditions related to inclusion. For a variety of reasons, including age, health, ability, wealth and ideology – large segments of the population do not have access to their own car. The car-centred mobility system, is therefore not neutral.

How people relate to cars depends on a series of factors including life events (Uteng et al. 2019a) and wealth (Bastian et al. 2016). The position of the car as the centrepiece of the mobility system is thus being challenged along a series of dimensions, both of which are related to environmental concerns (Geels et al. 2012) and to the idea of what constitutes a good life (Schwanen et al. 2015). In this context, UD and public mobility solutions become more important.

This paper draws on the technology mapping conducted by the Norwegian Board of Technology in 2020 (Haarstad et al. 2020), and experience from empirical studies of how people with mobility impairments interact with new technology – in particular, (Øksenholt and Aarhaug 2018). The mapping exercise was conducted to chart which innovations were likely to influence mobility in the context of Norwegian cities. The technologies listed include physical solutions, such as e-scooters and autonomous vehicles, but also new ways of offering mobility, such as mobility as a service (MaaS) and cooperative intelligent transport systems (C-ITS). Although mapped and analysed in a specific context, the technologies are common in many parts of the world. A selection of these technologies is explored further in this paper. The empirical experience used to discuss these technologies is mainly drawn from research projects in which the author has had a role; these projects were centred on individual issues. This experience is supported by prior research, including (Bezyak et al. 2017, Deka et al. 2016, Fearnley et al. 2022.b, Nielsen 2021).

Innovation studies have given rise to several conceptual models of how new technology is diffused. One of the classic and most widely used and criticised is that developed by Rogers (2010/1962). Within this model, the uptake of the new technology follows an s-curve, where a technology moves from being a small niche phenomenon – with users often labelled as ‘trendsetters’, or members of the ‘urban elite’ – through a take-off and acceleration phase; the technology is then gradually adopted by the rest of the population. This model of adoption contrasts with the philosophy of UD: Rogers’ model is an attempt to theorise based on observations, while the concept of UD is inherently normative.

The idea that some forward-leaning, or ‘elite’, individuals use a mobility solution before it spreads to other parts of the population does not have to be a problem in terms of UD. But if the elite’s consumption cannot be replicated across the population, it becomes problematic in terms of UD because it reflects different access to mobility. As an example, a new mobility solution may require a specific type of smartphone (as some hailing services do), payment by credit card (as many private companies require), substantial income (to afford the service) and a driver’s license (in the case of car sharing). A new technology that is only useful for a few will thus not necessarily be universal, and may be at odds with UD as a policy objective.

Avoiding this bias can be difficult. Many of the new mobility technologies that have come on the market are initially aimed at typical ‘early adopters’. These are individuals who also tend to have demographic characteristics that overlap with those who initiate the new technologies. In addition, many new technologies are developed in and for a world market. Low replication cost is a key component of digitalisation. User participation may be limited to the question of how the technology should be introduced in the specific locality, rather than how the solution is designed. This may reduce the scope for adaption to address the needs of other user groups than those upon which the developers initially focused.

A common denominator for the technologies selected in this work is that they have been influenced by the development of digital technologies. In this way, and as mentioned earlier, they can be labelled as part of the fifth technological revolution, following Perez’ (2003) classification. Digitalisation can be understood as the way digital technologies are introduced into society. Here, an important component is how information is transferred from being a physical to a digital entity – transformed from atoms to bits (Negroponte et al. 1997). This means that replication costs associated with information drop dramatically, and the movement of information is decoupled from the movement of physical entities. This allows a series of new services, and new ways of offering pre-existing services. Information, including vehicle location and status, can be made available for existing and potential travellers at low cost, reducing the disutility of travelling (Flügel et al. 2020).

Digitisation thus provides an opportunity to establish new service offerings based on available information both commercially and non-commercially. This helps potential travellers make more informed choices about when, where and how they travel. At the same time, it can also help to increase the divide between those who have access to this information, for example through the use of smartphones, and those who do not. This points back at the concept of universality and main solutions. Does it mean that the mobility system should include mobility solutions for all, or that each element of the mobility system should be accessible for all?

Predicting the future is challenging. In relation to mobility, the practice has long been to make predictions based on modelling along established trends. This approach has been criticised for creating lock-ins in established technologies. To address how new technologies play-in in future mobility, several methods have been used, including modelling with (very) alternative assumptions, backcasting and scenario building. For the purpose of creating a coherent discussion, this chapter makes no independent effort to assess which technologies are relevant. Instead, as noted above, it uses a list identified by the Norwegian Board of Technology as a starting point (Table 1) and adds to this by using examples and assessing UD relevance. In Table 1, UD relevance is judged based on discussions between the author and other researchers with experience from UD and technology implementation.

In Table 1, small UD relevance means that the technology is judged to not directly impact UD, and thus is less relevant for UD policies. Some UD relevance means that the technology impacts mobility in a heterogeneous way (mainly by providing advantages to some users and possible disadvantages to others), and that this differentiation is linked to users’ characteristics. The differentiation may not be directly related to mobility impairments, but is changing the mobility market in a way that influences persons with disabilities. An example would be a reorganisation of the taxi/non-emergency vehicle-for-hire markets, by removing requirements for operators to provide wheelchair-accessible vehicles. Large impact is when the technology is judged to influence persons with mobility impairments directly.

The following text focuses on the technologies that are expected to be most relevant in a UD context.

Mobility as a service (MaaS) is a digital platform that connects various mobility offerings from different modes through a single user interface. In this innovation, the main issues are related to implementation, not the development of the technology. As pointed out by Smith and Hensher (2020), MaaS actors have had more success in developing the technology than in functioning as economic and organisational entities. Theoretically, MaaS should increase the possible user group for a particular mobility mode, through reducing the barrier created by lack of information and creating a possibility for nudging; it is possible to inform travellers of various characteristics of the service in question at lower cost. The drawback, in a UD context, is that MaaS requires digital skills and smartphone access. Other potential issues are related to a fragmentation of responsibility: this issue arises when the operator providing the service is not the same as the one interacting with the customer at the point of booking.

Micromobility is a common term for small vehicles, including e-bikes, e-scooters and skateboards (Fearnley 2021). Some are designed to be used in mixed traffic with pedestrians. To the extent that these vehicles replace cars and vans, they can contribute to make the street space more available to softer travellers. However, when introduced to pedestrian areas, they typically increase the weight and speed of vehicles in these areas.

E-bikes make biking more accessible, and enable a wider segment of the population to bike further (Fyhri and Sundfør 2020). E-scooters provide access to individual motorised mobility for persons who would otherwise have less access to motorised mobility, being cheaper than taxis and private cars and more available than public transport. For persons with disabilities, issues with e-scooters are largely related to parking. That these small vehicles are left on the pavement is a problem, as they may get in the way of wheelchair users and can be a danger to the visually impaired.

Shared micromobility consists of bicycles, e-bikes or e-scooters that can be rented via subscriptions or on a per-trip basis. This decouples ownership and use and is expected to improve access and reduce the threshold for using the technology. Still, user surveys indicate that the majority of the users are young, wealthy, without disabilities and using the services in city centres (Fearnley et al. 2022a).

Car sharing enables car access without having to own a car. In practical terms, car sharing reduces the barrier for each trip, compared to car renting, while still having a higher barrier than private car ownership. Car sharing can reduce car ownership, parking needs and emissions from car ownership in urban areas (Chen and Kockelman 2016). This can help free up space for other types of road users and have a positive effect on accessibility. At the same time, it is not clear how car sharing will affect city space and car ownership in the long run, since the usage patterns and motivations for participation are still under development (Julsrud and Farstad 2020). The implications of car sharing for UD are also uncertain. Car sharing is aimed at people who are able to drive cars with a standardised design and exclude people who cannot use such cars. In this way, it can be argued that car sharing may increase the differences between those who are ‘inside’ and ‘outside’ the norm. However, this line of argument seems a bit extreme.

Ridesourcing is one of many terms used to describe new, platform-organised, taxi-like services. Other terms include transport network companies (TNCs) and ridehailing. The main effect of these services has been to make taxi travel – traditionally the most accessible form of motorised mobility – available for more people. The services are also generally perceived as safer than pre-existing services, further reducing the barriers to use (Aarhaug and Olsen 2018). The potential downside is linked to reduced scope for local authorities to regulate the supply, which may (as is the case in Norway) reduce the number of wheelchair-accessible vehicles (Aarhaug et al. 2020). This raises the question concerning at what level a system should be accessible. Is it sufficient to have access to some vehicles, or does every vehicle in a fleet need to be accessible? The latter would be more expensive and likely require some form of economic transfer, as the market solutions seem to focus on a narrower user segment than what UD dictates.

Autonomous cars have the potential to radically change the mobility system (Docherty et al. 2018, Nenseth et al. 2019). An expectation is that autonomous cars will make car-based mobility accessible to a larger part of the population. In extension, this will lead to an increase in mobility, especially for those who currently do not have access to their own car. Here, downsides include increased traffic and energy use, unless strict policies are introduced. The outcome will be highly policy dependent. Autonomous vehicles may well blur the distinction between private and public transport (Enoch 2015, Seehus et al. 2018). Automation may reduce the cost associated with providing the service, allowing public transport with higher frequency and or more flexibility for similar cost. This should increase the attractiveness of public transport relative to other modes. However, many questions relating to how autonomous vehicles will be perceived and regulated is still unanswered.

Demand responsive transport can be seen as closely resembling MaaS, by making a public transport service available on demand, through a potentially multimodal platform. This should point towards increased accessibility and improved UD. The potential downside is linked to the difficulty associated with communicating such services to vulnerable groups (Skartland and Skollerud 2016). In parallel to other services that rely on the automated processing of bookings, issues may arise concerning a lack of the correct tools or knowledge to order the services.

Common across these new technologies is that the innovations are mainly about combining existing elements and services in a new way. Here, the possibility of a better user interface through connection to smartphones has been particularly important. Looking ahead, it seems that autonomous vehicles, in addition to emissions-reducing technology, will also become increasingly important. If autonomous vehicles are used to a greater extent, it will have major consequences – both for how people think about transport and accessibility to mobility services. This is a field that is being researched, but where there is still a great deal of uncertainty.

Lenz (2020) points out that in addition to the obvious gains involving better information flow and greater access to information about transport services, there are many factors related to new transport technology and smart mobility that are poorly elucidated. For example, data flow across systems presents new challenges in terms of risk, ownership and responsibility. Many aspects of new mobility technology influence different users in different ways, potentially creating new inequalities. This applies along several dimensions, and is often under-communicated. The typical user of new mobility services described by Lenz (2020) has many similarities with the typical early adapter in traditional technological transition frameworks: young, wealthy, technology-oriented and able-bodied. Depending on whether and how quickly uptake of the new technology spreads to the rest of the population, this may mean that the segment of the population that has access to mobility services becomes both larger and smaller. The optimistic expectation is that more mobility may be available to more people; the negative expectation is that the differences between people’s access to mobility increase, as a result of some gaining access to better services while others retain their current mobility – or lose some of this mobility as users who can select the new services. Still, there are a number of examples of user participation in the development and implementation of new technology in the transport sector, especially related to public transport. There are also a number of technological developments that support inclusion. Examples of such technologies include navigation solutions for the visually impaired on smartphones, and contactless payment using mobile phones, which makes it possible to avoid vending machines for tickets and various forms of driver assistance. It seems that the consequences of new technology are mainly determined by how the technology is used and what frameworks and regulations are established, and not just the technology in isolation. While the opportunity space is increasing, the benefits may not necessarily reach everyone.

For people with orientation impairments, digitisation of information has helped to make travel experiences easier. In practical terms, digitisation of travel information means that the available information – including digital notices and automatic calls – can be (and is) disseminated across platforms and on smartphones, through beacons. Together, this makes the travel experience less intimidating. Digitalisation in a broader sense also makes access to door-to-door transportation more available. While research has identified weaknesses in the implementation of the more advanced information systems (Øksenholt and Aarhaug 2018), this constitutes minor disadvantages of a development that is mainly positive.

A structural challenge in mobility is that increased prosperity generally leads to increased use, and in particular of private transport solutions, such as the private car. This has several effects that affect UD. Directly, this means that the revenue base for the shared solutions goes down, as fewer people pay for tickets. To some extent, this can be mitigated through transfers. Targeted taxes on cars, such as urban toll roads, can create transfers from motorists to public transport users. It can also contribute to providing incentives to not travel by car and to maintaining a better public transport system than ticketing supports. At the same time, this system functions only to a limited extent as a redistribution policy (Fearnley and Aarhaug 2019) and may also have limited effects on behaviour, as it does not mitigate the underlying disadvantage faced by public transport in terms of travel time (Lunke et al. 2021; Lunke et al. 2022).

The challenge with new mobility technologies is that many have significant user cost. This can negatively affect overall mobility in two ways: 1) those who cannot afford it do not have access to the increased mobility that new technology entails; and 2) when parts of the population switch to using new mobility solutions – which are often private and user-financed – it undermines the financing of the mobility solutions on which others depend.

Several aspects of new mobility technologies are challenging when compared with the policy objective of a universally designed society. How new technology affects the goal of UD is largely related to how new technology is introduced and implemented. On the one hand, new technology increases the opportunity space for actions. On the other, the ability to adopt new technology is unevenly distributed, which may leave many with reduced mobility.

The introduction of new mobility technologies can thus result in new barriers – physical, technological, economic and mental. How this turns out is not only a result of the properties with the relevant innovations, but also the policies surrounding their use. Many of the technological advances that have taken place, especially in public transport (e.g., real-time information, smartphone ticketing and stepless access) have helped to make public transport more accessible. The valuation studies also show that these are measures from which most users benefit, in support of the UD thinking (Veisten et al. 2020; Fearnley et al. 2009).

Looking at technologies that have been introduced under the label of UD in Norway from 2010 to 2020 – in particular, information systems and improved vehicle and travel chain design – these have contributed to creating a more universally designed mobility system (Aarhaug and Elvebakk 2015; Fearnley et al. 2022b). These studies focus on experience within public transport, where important components include real-time information on stops, the use of beacons and improved operator knowledge. This is a great advantage, in terms of a) providing more reliable information to those on board, with automatic stop calls and information screens; and b) through the possibility of creating smart and connected travel planners, and multimodal ticketing systems: measures that are highly valued by all passengers irrespective of impairments (Veisten et al. 2020). However, other components that have been introduced have resulted in new barriers to use. In particular, these are related to the digital skills needed when introducing smartphone or other forms of electronic ticketing (Øksenholt and Aarhaug 2018), but also a wider issue in new mobility (Uteng et al. 2019b).

As argued in this chapter, there are indications that the challenges to UD become more acute with some of the new mobility technologies being introduced. The outcome is increasingly policy dependent.