Chapter 1
We are on the cusp of the next major evolution in urban transport. The Covid-19 pandemic has prompted significant disruption in transport patterns, with many reconsidering how and when they travel. Simultaneously, next-generation solutions are emerging that leverage the huge amount of data in our cities and include innovative modes of travel; take Advanced Air Mobility (AAM), with its flying passenger taxis and cargo drones.
These solutions are much needed: congestion as well as air and noise pollution impact not only productivity in many of our urban centres, but quality of life for residents too.
So, what will it take to transform urban transport? Mobility as a Service (MaaS), which integrates various types of transport service into a single one that is accessible on demand, has an important role to play. By combining data and ticketing, MaaS makes it easier for people to choose shared transport options. In cities with a physically robust transport system, including a strong public-transit network, as well as large quantities of open data and high smartphone penetration, MaaS can also help streamline journeys across different transport modes, opening up viable alternatives to private car use.
While it is not a silver bullet for congestion, MaaS offers a model of transpoFrt integration to urban and regional authorities everywhere that promises to make it easier for citizens to travel using both public and private providers and, ultimately, to unlock productivity growth. For policymakers, MaaS should be viewed as one important piece of the puzzle that must be solved to make our cities cleaner, greener and more habitable.
To make the most of MaaS, policymakers should:
Fully integrate mobility into urban life. The norm of individual car ownership – and the associated congestion, pollution and deadly accidents – is a holdover from the 20th century. Residents should be able to get anywhere in a city quickly, conveniently, safely, and at a fair and predictable price. To achieve this, MaaS should be available for a flat fee per month (like rent) and integrated with housing (like a utility). For example, an apartment for rent could post monthly mobility fees in addition to the rent required.
Consider mobility a region-wide service. MaaS is most effective when it not only links destinations within a city, but multiple cities within a region too. The advent of fully electric short-haul flights, AAM and electric vertical take-off and landings (eVTOLs) will increase the opportunities for and ease of regional connectivity; MaaS will be instrumental to leveraging these connectivity gains.
Mandate open data from public- and private-transport providers. Data are the lifeblood of MaaS. There are a number of open application-programming interfaces (APIs) for the sharing of mobility data with useful formats including General Transit Feed Specification (GTFS), GTFS-flex, Mobility Data Specification (MDS) and General Bikeshare Feed Specification. Governments should release all their mobility data in a pre-existing API and require private-transport operators to do the same. Additionally, cities should make software-development kits (SDKs) available to enable third parties and developers to create mobility-specific applications.
Partner with the private sector to create a MaaS platform. The private sector is already developing MaaS platforms, with startups worldwide experimenting with shared micromobility offerings, as are rideshare and mobility providers Uber and Lyft. Where they already exist, governments should leverage these developments rather than seek to replicate them.
Build a MaaS market. Success depends on broad-scale adoption, but government support is necessary for MaaS solutions so they can evolve from time-restricted pilots to long-term, continuous operations. This support can take the form of subsidies for MaaS bundles that prioritise socially beneficial modes of transport, for instance.
Use smart systems, AI and machine learning for better enforcement of traffic regulations. The efficacy of some congestion-reducing measures is hindered by lacklustre enforcement. High-occupancy vehicle lanes, for example, are reserved for vehicles with multiple passengers at peak times yet their enforcement is ad hoc. Smart systems could automatically discern the number of occupants in a vehicle and deduct the appropriate fine from a dashboard sensor or send an invoice to the registered owner.
Price street parking to reflect the true value of kerb space. All too often reserved for parked cars, kerbs are valuable urban real estate that would be better allocated as loading zones for shared vehicles or protected bike lanes. Thoughtful parking-pricing policies, including uniform-price auctions, variable-rate models and incremental pricing, should be considered to reduce private car use by more closely tying demand to pricing.
Implement congestion pricing. Congestion pricing can help reduce private car use by ensuring that drivers internalise some traffic costs. Policymakers should consider using variable-pricing models, such as Singapore’s real-time pricing that alters rates based on the time of the day, location of the road, vehicle type and local traffic levels.
Chapter 2
Traffic is not only annoying, it’s also costly and dangerous.
In 2019, Americans lost on average 99 hours a year due to congestion, costing them nearly $88 billion in wasted fuel and productivity. UK drivers meanwhile lost on average 115 hours a year, costing them £6.9 billion. While these figures decreased in 2020 due to the Covid-19 pandemic, they rebounded in 2021.
Private car use is extremely inefficient. Parked 95 per cent of the time, cars are underutilised and take up valuable space when stationary. In urban areas, a significant proportion of traffic comprises cars looking for parking spots. The inequity of access is also problematic. For low-income households without access to a private car, the lack of alternative transport modes presents barriers to quality jobs, housing and education. In Pittsburgh, for example, 20 per cent of residents without a car struggle to get to work while in Miami, car users access eight times more low-wage jobs on average than individuals on public transport. And finally, when on the road, congestion created by cars leads to greater air and noise pollution as well as traffic accidents.
Each of these factors contributes to cities being less productive than they should be. While agglomeration effects generally make cities more productive, this is not always the case: urban areas without good public transport (and with high levels of private car use) are generally less productive than cities of a similar size elsewhere.
With Covid-19 massively disrupting the travel patterns of people around the world and causing others to reflect on their transport choices, it is unlikely that workers will adopt the same pre-pandemic routines when and as physical workplaces reopen. In the longer term, we also need to account for growing urban populations: by 2050, about 70 per cent of the world’s population is expected to live in urban areas. This means the pressure on existing transport systems and the need for urban economies to become incrementally more productive will only intensify.
Given all these considerations, it is an opportune moment not only to reassess the commute, but also to reconsider urban transport as a whole. Our cities will soon be home to a new generation of transport, as Advanced Air Mobility (AAM) enters the consumer market. Quieter, smaller and potentially cheaper than previous generations of short-haul aviation, such vertical takeoff models will offer a viable alternative to taxis, helping customers travel across cities and regions in aircraft powered by batteries and green energy.
But by failing to invest in our urban transport systems and incorporate next-generation technologies, we will be in danger of perpetuating old habits and leaving economic value on the table, just when we need to strengthen our cities as powerhouses of the post-Covid recovery.
Chapter 3
Mobility as a Service (MaaS) can help reduce congestion and improve productivity by making multimodal trips easier. MaaS refers to a digital platform, generally an app, on which a user can plan, book and pay for a trip from end-to-end based on real-time data. Its framework can cover any combination of multimodal and transport-adjacent services (including parking), either public or private. For example, a MaaS app would enable a city dweller to determine that her or his most efficient route to work is to take a private-scooter share to catch a train, with both modes of transport immediately bookable and paid for. Transport is available either on a pay-as-you-go (PYGO) basis or as a subscription bundle.
The academic literature around MaaS has converged around a five-part scale:
Level 0 denotes no integration. Planning, booking and ticketing are separate. A transit-agency website on which one can only plan, book and pay for a single service is Level 0.
Level 1 denotes integration of information, such as multimodal-trip planners offered by Google Maps or the app Moovit that include route as well as price information.
Level 2 builds on Level 1 since booking and payment are integrated in addition to information. For example, in some cities, Uber and Lyft now offer shared scooters and bikes in addition to car trips, and they are partnering with transit agencies to update their apps so that users can plan multimodal routes and purchase multimodal tickets.
Level 3 offers all these integrated functions in a subscription bundle. Some examples of Level 3-MaaS include the Jelbi app in Berlin and the Whim app that first became available in Helsinki, but is now in several other cities. Jelbi is the product of a collaboration between Trafi, a Lithuanian startup, and Berlin’s primary transit agency.
Level 4 denotes a system integrated with public policy and governance, with key aims including sustainability, accessibility and equity.
MaaS is designed to facilitate efficient use of the varied mobility resources already on the ground and thus produce a shift away from private car use. While there is not enough data to prove that MaaS causes a reduction in congestion, pilot studies have shown it can alter consumer habits and preferences around car use. After a six-month study in the Swedish city of Gothenburg, which ran from November 2013 to April 2014, participants reported that they had chosen to travel by private car almost 50 per cent less than before using MaaS, and almost a quarter reported that their attitude towards private cars had become more negative. Meanwhile, a 2018 survey of Whim app users in Helsinki showed that they used public transport more than the control group as well as selecting bicycles or taxis to reach their stops; without this other mode of transport, these travellers may have opted out of public transport entirely because of the first- and last-mile problem (most people are only comfortable walking a quarter of a mile to a stop). Additionally, a study conducted in Sydney from November 2019 to April 2020 showed that MaaS can increase public-transport use and has the potential to decrease private car trips.
Besides addressing congestion, MaaS may also reduce the overall energy consumption of a transport system. Since it is relatively cheap and easy to implement, MaaS represents low-hanging fruit, especially if a city has the necessary array of transport options that residents may not be leveraging because it’s inconvenient to do so or they don’t know about them. MaaS is not, however, an alternative to a functional public-transit network or strong transport system, with investment in physical infrastructure still paramount and indeed a precondition to its successful implementation.
In light of the shift in mobility caused by the pandemic, planners are unlikely to be able to rely on predictable commuter and travel patterns as they have done historically. Workers might go into the office one or two days a week, for part of the day, or not at all. Most likely, their journey has multiple stops, with different mobility-sharing platforms for cars, bikes, scooters and other modes of transport further complicating this picture. A cohesive MaaS solution that offers tailored, real-time solutions for travellers will not only help residents to get around more efficiently, but will also facilitate reduced private car use and, in time, adoption of new integrated forms of mobility, such as urban aviation.
Chapter 4
In the urban context, MaaS can be most effective in cities with a strong transport infrastructure, including an expansive public-transit network, bike lanes and high-quality roads; a large quantity of open mobility data; relatively high levels of congestion; moderate- or high-population density; an active or emerging smart infrastructure; high smartphone penetration; high public- and private-sector investment; and a policymaking approach that fosters innovation. While perhaps counterintuitive, a transport system with a relatively complex regulatory regime can be more suited to MaaS than, say for example, a fully integrated system, as explained below.
The Necessary Mobility System
Physical-Transport Infrastructure and a Transit Network
To be a good candidate, a city should have robust public-transport infrastructure, including a transit network. MaaS platforms then help residents access transit more effectively, including by solving the first- and last-mile problem. Various online sources can help determine whether a city has public transportation that can support MaaS. The Oliver Wyman Forum has created an Urban Mobility Readiness Index, which scores cities on a variety of metrics to ascertain their future mobility capacity (not specifically for MaaS). One of these metrics is physical-transport infrastructure, including factors such as public-transit accessibility as well as road quality and connectivity. On a larger scale, the World Economic Forum Global Competitiveness Index ranks countries by the quality of their transport infrastructure.
Open Mobility Data
A MaaS platform will also require access to mobility data from private and public providers. Cities that gather and make public a high volume of mobility data from diverse transport modes are best situated to host MaaS. For example, the Jelbi app in Berlin relies on open data from the federal state, shared in accordance with the 2011 Berlin Open Data-Strategy. Similarly, Transport for London has an “open-data policy” under which it publishes a variety of mobility data on an open API. In Finland, public- and private-transport providers must share data on an open API pursuant to the Finnish Act on Transport Services (2018). Los Angeles has also developed an open API for micromobility called the Mobility Data Specification, with the city requiring private operators to share transport data. In contrast, at the other end of the spectrum, cities with low volumes of data collected and few data-sharing initiatives include Mukono in Uganda and Kathmandu in Nepal. High volumes of shared data anywhere necessitate rigorous data-privacy protections, such as anonymisation and encryption.
Congestion and Population Density
MaaS offers the greatest benefits in relatively dense urban areas where congestion hinders productivity. For example, Birmingham is the UK’s second largest city, but is substantially less productive than the similarly sized Lyon in France, largely because it has much greater rush-hour congestion. Publicly available tools, such as TomTom or INRIX, use real-time data from drivers worldwide to rank cities by congestion levels and give insights into traffic patterns.
The Necessary Regulatory Environment
Complexity
The complexity of the regulatory environment is an important consideration. Areas with just a few or even one transport agency will more easily implement a MaaS solution than those with many fragmented agencies, which would need to coordinate to deliver this service. MaaS can, however, have an outsized and positive impact in regions with complex and fragmented transit networks. For example, the San Francisco Bay Area’s rapid-transit system is overseen by 27 different agencies, complicating the user experience for passengers. While consolidation of these disparate agencies could well be the best long-term solution, to achieve this would be politically challenging and take years. In the interim, integration of transit options via MaaS could increase uptake.[_] So, while perhaps counterintuitive, a city with a fragmented transit landscape and regulatory regime is a good candidate for MaaS.
Innovation
Next, a city with a public sector that is willing to experiment and innovate is a good candidate for MaaS. For example, London and Los Angeles are undertaking micromobility pilots for scooters and car sharing, respectively, while Pittsburgh is piloting a MaaS programme called Move PGH. The Netherlands provides a good example of innovative policymaking: Amsterdam, Utrecht, Eindhoven, Rotterdam and The Hague are working together today to establish a new standard for the exchange of mobility data between cities as well as shared mobility operators. Once developed, this standard will most likely be disseminated across Europe.
To that end, a public sector willing to collaborate with the private sector is also a good candidate for MaaS, since the most effective platform will connect both private and publicly subsidised modes of transport. Furthermore, a platform is most efficient if private-sector actors become brokers that offer integrated transport solutions to passengers, particularly since this sector has already developed MaaS platforms that can be easily adopted by other regions.
Partnerships with academia or research institutions are also supportive in this context. For example, Transport for London has a well-established partnership with the Urban Mobility Lab.
Market Attractiveness
Cities with high levels of mobility investment from both public and private sources are well-suited to MaaS. For example, Los Angeles has $120 billion earmarked for transportation improvements, including smart mobility, over the next 40 years.
The Necessary Digital Maturity
Smart Systems
A city must have sufficient digital maturity to support any MaaS platform. Cities with advanced traffic-management systems that gather real-time data and include sensors, cameras and other devices connected via the Internet of Things (IoT) are best equipped. On this front, Singapore leads the way: its smart infrastructure allows it to implement variable congestion pricing based on the location of a vehicle and the time of the day. The Cities of the Future Index’s “Mobility Innovation” metrics, particularly Traffic Management, give some insight into whether a city has a smart-mobility system (although the index doesn’t include any African countries).
Smartphone Usage
Naturally, smartphone use must be high to enable MaaS. The leader is Singapore, where 88 per cent of the population used a smartphone in 2020, and the government spent $2.5 billion on communications infrastructure, such as upgrading lamp posts with connected sensors and cameras. Even where digitalisation is low, rising smartphone usage, in combination with decreasing data-storage costs, can help cities leapfrog legacy mobility issues. For instance, they can bypass the convoluted structure of multiple pay mechanisms and portals with a single, universal MaaS app.
Many African cities use semi-formal transport such as minibus taxis, which can be challenging for the public sector to manage due to their fragmented and decentralised nature. Nairobi’s Digital Matatus was the first group to develop open-data infrastructure for these informal transport systems. A partnership between the University of Nairobi’s C4DLab, MIT’s Civic Data Design Lab and Groupshot mapped the city’s minibus routes using transit-route data collected from GPS-enabled smartphones. The partnership then worked with Google to modify the GTFS open standard so that it could accommodate informal transit systems with variable data. DigitalTransport4Africa is a collaborative digital commons that applies this model across Africa. This means a public-private partnership could leverage this data to create a universal MaaS platform for regions in Africa.
Rating four major cities around the world on their suitability to introduce MaaS
Source: TBI
Evaluating the Existing MaaS Market
Global revenue generated by subscribers for MaaS platforms equalled $5.3 billion in 2021. Projections of the global MaaS market vary wildly, anything from $70.4 billion to $1 trillion by 2030. Investors and academics are still unsure whether MaaS is a long-term, revenue-generating proposition: no sustainable business model has been demonstrated and most revenue goes towards the transport providers themselves, rather than the platform. Regardless of the financial outlook, though, it is indisputable that both public- and private-sector funds are flowing to mobility solutions generally – and to MaaS in particular. Mobility solutions have continued to attract investment over the past two years despite the pandemic, with over 60,000 patents filed between 2012 and 2020; autonomous (AVs) and electric vehicles (EVs) took the largest share of the patent pool.
The interest in MaaS has also taken off among the public sector. The US, UK, China, EU and Israel are some of the leading innovation hotbeds for MaaS and the Scottish government specifically has committed £2 million to an investment fund to test the viability of MaaS over a period of three years. A new pilot by Move PGH in Pittsburgh is the first instance of Level 3-MaaS in the US.
The industries with exponential investment growth include e-hailing (combined taxi, car-rental and car-sharing services), AV components and EVs
Source: McKinsey & Company
Plotting where Level 3-MaaS apps are operating around the world today
Source: Whim App and Trafi
Chapter 5
Transport is a public good impacting a range of environmental, health and safety factors. Consequently, the public sector should develop and communicate a strong, cohesive vision for MaaS that incorporates sustainability, accessibility and equity in addition to congestion management. A private-sector company would not implement this same vision without public-sector involvement. As interest and investment in MaaS increases, these steps will allow policymakers to realise the benefits of digitally integrated transport solutions.
Fully Integrate Mobility Into Urban Life
The norm of individual car ownership – and the associated congestion, pollution and deadly accidents – is a holdover from the 20th century. Residents should be able to get anywhere in a city quickly, conveniently, safely, and at a fair and predictable price. To achieve this, MaaS should be available for a flat fee per month (like rent) and integrated with housing (like a utility). For example, an apartment for rent would post monthly mobility fees in addition to the rent required.
Consider Mobility a Region-Wide Service
MaaS is most effective when it not only links destinations within a city, but multiple cities within a region too. The advent of fully electric short-haul flights, AAM and electric vertical take-off and landings (eVTOLs) will increase the opportunities for and ease of regional connectivity; MaaS will be instrumental to leveraging these connectivity gains.
Mandate Open Data from Public- and Private-Transport Providers
Data are the lifeblood of MaaS. There are a number of open-application-programming interfaces (APIs) for the sharing of mobility data with useful formats including General Transit Feed Specification (GTFS), GTFS-flex, Mobility Data Specification (MDS) and General Bikeshare Feed Specification. Governments should release all their mobility data in a pre-existing API. Some examples of open-data initiatives include the UK’s Transport Systems Catapult and Belgium’s Intelligent Transport Systems, DigitalTransport4Africa and the EU’s Open Transport Net. Governments should require private-transport operators to release their data in the same way as well. The Finnish Act on Transport Services (2018) requires every transport group (public and private) to share its data in an open API. Similarly, Los Angeles requires shared-service and micromobility transport providers to share data using MDS. Simultaneously, governments should ensure that privacy is protected; the EU’s General Data Protection Regulation (GDPR) could serve as an example.
Additionally, cities should make software-development kits (SDKs) available to enable third parties and developers to create mobility-specific applications.
Partner With the Private Sector to Create a Regional MaaS Platform
The private sector is already developing MaaS platforms. For example, the Whim app (by a Finnish startup) is operating in a handful of cities and Trafi, a Lithuanian startup, works with public bodies in various cities to develop MaaS apps there (Figure 3). Startups worldwide are also experimenting with shared micromobility offerings, as are rideshare and mobility providers Uber and Lyft. Where they already exist, governments should leverage these developments rather than seek to replicate them.
Build a MaaS Market
Success depends on broad-scale adoption, but government support is necessary for MaaS solutions so they can evolve from time-restricted pilots to long-term, continuous operations. This support can take the form of subsidies for MaaS bundles that prioritise socially beneficial forms of transport.
Use Smart Systems, AI and Machine Learning for Better Enforcement of Traffic Regulations
The efficacy of some congestion-reducing measures is hindered by lacklustre enforcement. High-occupancy vehicle lanes, for example, are reserved for vehicles with multiple passengers at peak times yet their enforcement is ad hoc. Smart systems could automatically discern the number of occupants in a vehicle and deduct the appropriate fine from a dashboard sensor or send an invoice to the registered owner.
Price Street Parking to Reflect the True Value of Kerb Space
All too often reserved for parked cars, kerbs are valuable urban real estate that would be better allocated as either loading zones for shared vehicles or protected bike lanes. Thoughtful parking-pricing policies should be considered to reduce private car use by more closely tying demand to pricing. The types of parking-pricing methodologies that better capture the true price of kerb space are:
Uniform-price auctions, which can be used for street-parking permits in residential areas, with revenues going towards public services. These auctions set the price for parking at a level that car owners are willing to pay while simultaneously benefitting non-car owners.
Variable-rate models, such as the one piloted in San Francisco, which involve prices for metered spaces changing based on the time of the day to better represent demand. Granular, real-time data collected from smart systems would allow more minute adjustments in pricing, based on congestion levels in addition to the time of the day.
An incremental-pricing strategy with a fixed price for a certain amount of time, such as the first two hours, but much higher prices for each subsequent hour or even minute; this approach gives everyone an equal chance to park, but allows people who value parking highly to stay much longer, with additional revenues for the city.
The University of California’s Donald Shoup outlines a variety of innovative urban-parking reforms in addition: parking is cheaper for low-polluting cars and more expensive for high polluters in Madrid; Calgary gives a discount to small cars; in Santiago, drivers who pay via mobile phone only do so for the exact amount of time they were parked; and some cities, including Tokyo, Oslo, Amsterdam and parts of Los Angeles, even ban street parking entirely.
Implement Congestion Pricing
Congestion pricing can help reduce private car use by ensuring that drivers internalise some of the costs of traffic. Policymakers should consider using variable-pricing models that alter rates based on the time of the day, location of the road, vehicle type and local traffic levels. The considerations include:
Geographic bounds. Will the geographic area be a single corridor, a city centre or entire region? For example, a congestion-pricing plan recently approved in New York City covers Manhattan’s central business district.
Pricing model. Should this be a flat daily fee, as in London, or consider a number of factors, such as in Singapore where the model is enabled by connected sensors and cameras collecting real-time data on the time of the day, location of the road, vehicle type and traffic levels? Bangalore is experimenting with a similar variable-pricing strategy, fed by data collected from GPS-enabled smartphones.
Payment mechanisms. Payment can be per transaction, or the user can be sent a monthly invoice, such as in Stockholm. In Singapore, vehicles must have an in-car unit on the dashboard and a smart card with fare stored in advance so that electronic road pricing can automatically deduct the appropriate fees.
Some argue that congestion pricing is inequitable, but these concerns are overblown.
Chapter 6
While MaaS is not a panacea for all urban-transport issues, it can play an important role in reducing private car use, decreasing congestion and improving productivity in our major cities. The models of open data used in MaaS solutions can help solve the first- and last-mile problem – which sees people opting out of public transport because of the distance to their local transit – while equally helping users find, access and pay for convenient solutions across transportation modes.
Given the increased investment in these platforms and the volume of transport data being generated across our cities, urban policymakers are right to look at MaaS as part of an integrated-transport solution. But the real challenge is to understand the conditions under which MaaS can be most effective, supporting broader public-transport goals including the reduction of private car use. As we reboot our cities as engines of growth and adjust to new transport patterns in the wake of the pandemic, there has never been a better time to rethink urban mobility.
Chapter 7
We would like to thank all those who helped inform this paper, including:
Marcel Moran, PhD Candidate, University of California Berkeley (City Planning)
Liza Farr, Curbside Administrator, City of Providence, Rhode Island
Jonathan Kass, Transportation Policy Manager, SPUR
Andrew Flett, General Partner, Mobility Impact Partners LP
Sampo Hietanen, Founder, MaaS Global Ltd
Meir Dardashti, Principal, Maniv Mobility
Tom Forth, Head of Data, The Data City and Open Innovations
David Zipper, Visiting Fellow, Harvard Kennedy School
Lead image: Getty Images