The Global Champions of Urban Mobility

Spend a few minutes at rush hour in many major cities, and you’ll see the stark realities of mobility: clogged roads, polluted air, and patchy mass transit. But while most cities are suffering, some are overcoming these challenges. In those cities, residents enjoy better mobility and live healthier lives, with shorter commutes and cleaner skies.

To identify which cities are performing well and what lessons they can offer, we conducted a comprehensive analysis of more than 150 cities around the world and ranked them by their urban mobility performance. We call this framework the BCG City Mobility Compass. Our approach involved assessing more than 20 KPIs per city, supplemented with an in-depth survey of more than 50 city leaders. From that analysis, we grouped cities into six archetypes, based on such factors as their population size and density, urban layout, and mobility preferences, to determine which cities are building future-ready mobility systems. (See the appendix for a detailed discussion of our methodology.)

Following that research, we developed a global benchmark designed to serve as a basis for gauging how cities perform on the factors that matter most to city leaders and residents alike: fast, sustainable, seamless, affordable, and accessible transport. Using this tool, cities can make plans to transform their mobility systems and move people more effectively—today and in the future. (See “A New, On-Demand Mobility Diagnostics Tool for 150 Cities.”)

Transportation Systems Pushed to the Brink

In our survey, 95% of cities have set 2035 targets to move people more effectively—out of private cars and into sustainable modes, including public transport or forms of active mobility (micromobility, bicycles, or walking). Ambition levels vary globally. Cities in Europe and Asia-Pacific have established goals of having residents make more than 60% of all trips via sustainable modes by 2035; cities in North America and the Middle East have set more modest targets of around 30% to 40%. Yet regardless of their ambition level, cities are currently 10 to 15 percentage points behind where they should be in order to meet their 2035 targets, and they are unlikely to close that gap. (See Exhibit 1.) And historically, most cities have been able to shift only about three to five points of modal share per decade.

In the future, achieving mobility targets will likely become more challenging, as most urban areas face mounting pressures from the effects of urbanization, an increased reliance on privately owned cars, and growing system complexity. Technology alone will not provide a silver bullet, because each innovation solves some problems while creating new ones. For instance, although electric vehicles (EVs) can significantly reduce pollution, they also require extensive new infrastructure, adding fiscal strain and introducing new planning challenges. Navigating this evolving landscape successfully calls for decisive actions from leaders.

Six Urban Mobility Archetypes

There is no universal blueprint for transforming urban mobility. In our survey, more than 90% of city leaders reported struggling to identify the most effective levers—underscoring the potential value of tailored peer comparisons in helping them advance mobility outcomes.

To identify comparable peers, we grouped the 150 global cities in our analysis into six archetypes, accounting for differences such as population density, geographic layout, economic conditions, mobility maturity, and infrastructure base:

• Prosperous Innovation Centers. The first archetype includes cities with a population of less than 3 million and above-average population density, where sustainable modes dominate—with active transport, such as walking or cycling, commonly accounting for more than 50% of trips. These cities combine dense infrastructure with advanced digital integration to create efficient, people-centered mobility ecosystems. Examples include Utrecht and Copenhagen.
• Traditional Middleweights. The second category comprises cities with populations of less than 3 million, where private cars remain the dominant mode of transport. Because of their lower population densities (in many cases less than 3,000 residents per square kilometer) and correspondingly reduced system complexity, these cities can still achieve solid mobility performance overall. Examples include Nashville and Tallinn.
• Mass-Transit Megacities. Next are densely populated urban areas with populations of more than 3 million (and often far more). Public transport is the dominant mode, typically accounting for roughly half of all trips. These cities operate large-scale networks, often relying on a strong track-based transit backbone. Moreover, they increasingly apply polycentric planning to manage people flows, demand peaks, and other factors. Examples include Singapore and Tokyo.
• Multimodal Metropolises. Cities in this category rely on a blend of public transport and active mobility as dominant modes. Overall, sustainable transport typically accounts for three-fourths of all trips. These cities, typically with populations slightly greater than 3 million and less concentrated downtown areas, aim for seamless integration across transport modes. Berlin and Barcelona are leading examples.
• Private Transport Powerhouses. The fifth archetype includes highly car-dependent cities with population sizes above 3 million, where, on average, approximately 80% to 90% of trips occur in private vehicles. This is a result of a differing urban planning approach: Widely spread cities with extensive suburbs—particularly in the US—and often rather monocentric urban layouts make commutes long and cars necessary. Chicago is an example of this archetype.
• Developing Urban Giants. These are significant urban agglomerations in developing countries, usually with populations exceeding 10 million. They are characterized by high density and rapid demographic expansion that is likely to continue (in some cases at rates of 40% to 60% by 2040). Despite these complexities, the scale and momentum of cities in this category offer significant transformation potential. Delhi and Dhaka are representative cities in this group.

Mobility system performance across these groups reveals striking disparities. More advanced archetypes significantly outperform less mature peers, even with the data controlled for size. For instance, Prosperous Innovation Centers experience roughly 50% less congestion than Traditional Middleweights of similar size. Private-Transport Powerhouses emit more than twice as much CO₂ per 10-minute commute as Mass-Transit Megacities. (See Exhibit 2.)

Overall, our analysis shows a strong correlation between city performance and car dependency. For example, in cities with populations above 3 million, residents of the five cities with the lowest car modal share each spend 30 to 40 fewer hours in congestion per year and emit about 800 grams less CO₂ per 10-minute commute than those living in the five cities with the highest car modal share. (See Exhibit 3.)

Global Champions

Clearly, there are differences not only between archetypes but also within each archetype, as some cities outperform their direct peers. To identify these leaders, we assessed the cities in our study according to six quantifiable dimensions, each with a range of potential KPIs:

• Overall System Outcomes and Effectiveness (for example, time lost in congestion per resident, or CO₂ emissions for a 10-minute trip)
• Private Transport Management (for example, parking fees as a percentage of income, or use of congestion pricing schemes)
• Public Transport Performance (for example, cost of a monthly public transport ticket as a percentage of income, or accessibility to public transport as a percentage of population living within 500 meters of a bus stop or track-based public transport station)
• Active Mobility Promotion (for example, bike lane coverage, or the cost of shared bikes or scooters)
• Demand Management (for example, polycentricity score, or the implementation of active demand management initiatives)¹ 1 Polycentricity refers to city layouts that have more than one downtown commercial area. These cities tend to have less traffic congestion, because they don’t require residents to commute to the same area for work.
• Future Readiness and Technology Adoption (for example, spending on digital tools such as digital twins, or the use of end-customer platforms)

By aggregating scores across these areas, we ranked all 150 cities in our analysis on a scale of 1 to 10, leading to six global mobility champions—one for each archetype. (See Exhibit 4.)

At the forefront of the global pack is Singapore, the top performer among Mass Transit Megacities. Singapore’s leading position reflects a carefully calibrated multidimensional mobility strategy that aims to reduce reliance on private cars through a robust public transport network, promotion of alternative transport modes, and schemes to cap the permissible number of registered vehicles. The city’s Electronic Road Pricing system manages congestion by using electronic gantries to automatically charge vehicles for road usage during peak periods, with fees varying by location, time, and traffic conditions. More than 80% of intersections in the city are controlled by AI.

On top of that strong foundation, Singapore is investing in areas such as active mobility. Initiatives underway include development of a 1,300-kilometer cycling path network (scheduled to be complete by 2030), construction of end-of-trip facilities with showers and changing spaces for cyclists, and investment of more than $700 million to enhance pedestrian infrastructure and safety.

Other top-performing cities build on a different foundation and purse other initiatives. For example, Berlin already has a strong cycling culture, with over 2,000 kilometers of bike lanes installed across the city. Now it is working to integrate that infrastructure physically and digitally with other modes—for example, by transforming public transport stations into multimodal hubs, along with introducing mobiles apps that let customers book, use, and pay for different types of transit in a single interface. This approach makes Berlin a leader in the Multimodal Metropolis archetype.

How the City Archetypes Stack Up

The six archetypes serve as a framework for comparing groups of cities, pinpointing group and individual shortcomings, and identifying ways to further advance their mobility systems. Consider, for example, the four archetypes with populations exceeding 3 million—Mass-Transit Megacities, Multimodal Metropolises, Private Transport Powerhouses, and Developing Urban Giants. (See Exhibit 5.) A comparison of relevant data for each archetype reveals a number of clear differences. For instance, Private Transport Powerhouses have 70% to 75% fewer buses than Mass-Transit Megacities. And Developing Urban Giants have 75% to 80% less track for rail, metro, and light-rail transit than Mass-Transit Megacities.

Particularly concerning are the shortcomings of Developing Urban Giants, as these weaknesses are likely to worsen sharply with accelerating urbanization. Our simulation projects that, in the absence of significant investment, the share of the population with convenient access to public transport (within 500 to 1,000 meters of a bus stop or track-based public transport station) will drop by around 15 percentage points by 2040, causing overall accessibility to fall significantly below 50%. At the same time, existing track-based public transport capacity will become an acute bottleneck: as population density rises, we expect relative system capacity per capita to decrease by an additional 25% to 30%, further amplifying congestion, emissions, and accessibility issues in mobility.

Cities with fewer than 3 million inhabitants face different challenges. In these places, active mobility—cycling, walking, and shared micromobility—consistently outperforms both private and public transport–dominated systems across nearly all performance dimensions. For example, cities where active mobility is the dominant mode experience 25% to 30% lower levels of congestion and up to 25% lower levels of CO₂ emission than peers that rely primarily on public transport—let alone cities where most people rely on privately owned cars.

Comparing KPIs highlights some potential priorities for Traditional Middleweights. In these cities, bike ownership rates among adults are more than 40% lower than in Prosperous Innovation Centers, roughly bike-lane infrastructure is less than one-third as large, and shared-mobility availability is 55% less. (See Exhibit 6.) Although the two groups show similar levels of green-space availability, the differences between these archetypes translate into meaningful differences in traffic congestion and emissions levels.

Five Structural Measures to Improve Urban Mobility

Besides suggesting mode-specific interventions, the city leaders in our survey identified broader structural measures that can lead to greater progress. These initiatives, which build on trends in our survey data and on insights shared by city leaders, spur change by increasing public buy-in, improving efficiency, and making cities more future-ready.

Enlist residents in the transformation. More than half of city leaders cite public resistance as a major barrier to mobility transformation, yet fewer than 50% involve residents in the process beyond participating in basic online surveys. In light of generational shifts in mobility preferences, along with changing technologies, cities can enlist residents to actively co-create mobility transformation throughout the planning and execution phases. Madrid’s “Madrid Central” low-emission zone is a strong example. While the project was in development, citizens could offer input through an open‑government, online participation tool. That engagement helped the city overcome initial resistance—and the overall project reduced congestion in the zone by more than 15%, improved air quality, and fueled stronger local business activity.

Establish ecosystems of service providers. In many cities, the number of mobility players approaches 100, including AV fleets, micromobility services, and sensor providers. That often leads to increased complexity, limited interoperability, and siloed data. To improve, cities can serve as active orchestrators, setting data-sharing standards, enforcing interoperability, and enabling digital coordination. Hamburg is a good example. The city created one of Europe’s most advanced mobility data lakes by connecting public and private data streams to power real-time traffic management pilots and pave the way for broader coordination across Hamburg’s entire mobility system.

Make smarter infrastructure investments. Fiscal constraints and growing demand for mobility call for smarter infrastructure investments, especially for Private Transport Powerhouses and Developing Urban Giants. For instance, our simulations for Delhi indicate that, as a result of population growth, the city will need an estimated $7 billion to $10 billion by 2040 just to maintain current public transit service levels. Yet the city already faces significant budget constraints—a reality shared by more than 75% of surveyed cities. Innovative financing mechanisms include public-private partnerships, adoption of modular designs to cut capex by up to 20%, and use of digital tools to make planning processes more efficient. In one case, City Flow by BCG X, an AI-powered simulation and analytics platform, helped a European capital cut its planned metro costs by $1.4 billion without sacrificing performance.

Scale AI across the system. AI already delivers measurable impact across leading urban mobility systems, helping to reduce emissions, speed traffic flows, and improve the passenger experience on public transit—all without requiring costly infrastructure overhauls. Leading cities are embracing AI not just for operations, but also as a strategic lever. Singapore, for instance, has embedded AI across its entire transport ecosystem, from dynamic fleet dispatch and predictive maintenance to real-time demand forecasting.

Rethink urban planning. In addition to transport measures, urban planning—and specifically human-centric design—can reduce mobility demand and make cities more resilient. In this regard, concepts such as the 15-minute city show strong promise. An urban planning approach piloted in Barcelona, Paris, and Tokyo, the 15-minute city gives residents access to essential services such as work, shopping, schools, and health care within a 15-minute walk or bike ride from home. When realized, this approach can reduce travel needs by 15% to 20% while promoting healthier, low-emission transport. To apply it, cities can modernize zoning for mixed-use, walkable areas and invest in seamless multimodal transit to connect decentralized hubs.

Cities have growing aspirations to improve urban mobility, but our research reveals that most are not currently on track to achieve their aspirations. Without coordinated action, cities risk worsening inequality, congestion, and emissions. As our research shows, cities can make a start toward developing solutions by understanding their specific context and circumstances. But the analysis also points to clear winners for different archetypes: Singapore, Utrecht, Berlin, and other top performers are designing urban areas with greater mobility options to reduce congestion and emissions and make life more livable for their residents.

These cities’ successes point to three overarching keys for improving urban mobility:

• Identify your weaknesses and map opportunities. Pinpoint the city’s most pressing mobility challenges and untapped opportunities by leveraging global benchmarks included in the BCG City Mobility Health Check Tool. Assess where the city stands today, understand what high-performing peers are doing differently, and determine which initiatives to prioritize. Ultimately, an efficient mobility system will not only enhance the lives of city residents but also trickle down into other strategic opportunities. For example, reducing congestion improves travel times and also boosts economic activity, as smoother traffic flows decrease productivity losses, lowering the cost of congestion.
• Move beyond isolated measures. Single interventions won’t move the needle. Develop a coordinated set of targeted initiatives under a holistic framework, incorporating input from officials, residents, and other stakeholders. In addition to launching mode-specific initiatives to reduce car dependency, add structural measures to help residents understand and accept the transformation. Invest in the underlying data and technology backbone, and embed mobility questions into broader urban planning to reduce the number and length of trips overall.
• Make every dollar count. Before committing resources, leverage AI-powered analytics and advanced digital planning tools to simulate the expected impact of high-profile, costly mobility initiatives (such as core infrastructure projects) and enable smarter, evidence-based decision making. By modeling outcomes upfront and continuously refining insights with real-time data, cities can maximize the effectiveness of each investment and secure the biggest payoff on mobility investments.

Appendix

Methodology

The 2025 BCG City Mobility Compass covers 150 cities across all world regions, income levels, and transport maturity—from megacities like Tokyo, New York, and London to smaller hubs like Tallinn, Utrecht, and Wellington. (See the slideshow.)

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Three Elements
To develop our rankings, we spoke directly to residents and officials and layered in perspectives from BCG’s Center for Mobility Innovation. The methodology centers on three elements from those inputs:

• City leaders focus on core system performance. More than 75% mention sustainability improvement as a top-three priority of their urban mobility plan, approximately 60% city congestion relief, with other goals such as economic development less frequently highlighted (less than 50% of respondents).
• Residents prioritize the on-the-ground, day-to-day experience. More than 80% reported convenient digital booking platforms as essential. Similarly, 70% pointed to affordable public transport prices and short walking distances (less than 500 meters) as key for their mode decisions, along with similar numbers citing access to micromobility and walking infrastructure.
• Five trends will impact these demands, making mobility systems more complex. First, urbanization will drive population density. Second, the shift to autonomous vehicles will require digitization and new regulatory policies. Third, electric vehicles will demand new charging infrastructure and regulation to increase adoption. Fourth, shared mobility will add new modes to already crowded streets. Fifth, continued growth in e-commerce will lead to increased volume of packages being delivered in cities.

Six Dimensions
To reflect leaders’ and residents’ inputs, as well as the underlying trends that are altering urban mobility, we evaluated cities on six dimensions:

• Overall system outcome and effectiveness is the primary dimension for measuring system performance. It covers tangible results, such as average congestion times that residents face and CO₂ emissions that residents’ vehicles emit. It also incorporates the share of trips made through sustainable modes such as walking, biking, and public transit.
• Private transport management evaluates how effectively cities are reducing and modernizing private car fleets. This dimension includes measuring electrification efforts, the use of push factors to decrease private transport attractiveness in city centers, and efforts to move beyond the car-centric culture that prevails in many developed countries.
• Public transport performance assesses the comfort, convenience, and sustainability of public transport, including metro, rail, light rail, bus, and bus rapid transit systems. We measure the availability, accessibility, affordability, and capacity of these modes, and we incorporate metrics on public transport electrification programs.
• Active mobility promotion measures a city’s support for and enablement of micromobility, walking, and other active mobility choices. This includes considerations related to safety measures, indicators of the availability and affordability of shared fleets, and promotion of private cycling and walking as transit options.
• Demand management evaluates cities’ efforts to reshape urban layouts (such as by implementing the 15-minute city) and actively manage demand patterns, aiming to reduce the overall number of trips, decrease required trip lengths, and flatten demand peaks.
• Future readiness and tech adoption covers a city’s level of readiness for pending innovations such as autonomous vehicles or mobility-as-a-service integration. Moreover, we measure the maturity of traffic management and the adoption of digital planning tools (including AI-based solutions) as proxies to cope with increased population density.

To measure these six dimensions, the 2025 BCG City Mobility Compass draws on more than 20 KPIs selected for relevance and diagnostic value, drawn from internal and proprietary data sources, as well as from publicly available global data. We score each KPI on a scale from 1 to 10 and weight the results based on their relevance. (See the exhibit.)