Intro

The urban mobility landscape is rapidly transforming in cities across the globe. Advances in technology have created new opportunities to innovate and potentially help tackle important societal issues.

At the heart of all this, is data. It enables novel business models and technologies. And it helps us understand where opportunities lie and what impact solutions have. But it also brings its own unique challenges. In this article we’ll explore urban mobility and data from our perspective as a data design and technology company.

The future of mobility

Driven by technological progress and pressing issues in society, companies and city governments are exploring new ideas and technologies. Often these are combined with new financial structures. Well known examples of this are ride-sharing companies like Lyft and Uber. But there are also sensor networks, dynamic road pricing, micro mobility, real-time route planning and flexible curb usage.

Behind this evolution there are multiple interconnected drivers.

Driver 1. Crowded cities

The first driver is that cities are getting busier. Across the world more people are moving to the city. It is expected that in 2050 almost 70% of the world’s population will be living in urban areas, with the highest percentages in North and Central America and Europe. This will result in increased urban congestion and usage of public transport. Already the average American commuter spends 42 hours per year stuck in rush-hour traffic. At the same time the growing popularity of ride shares and deliveries is competing for already scarce road and curb space.

City governments are looking for smart ways to increase capacity, efficiency as well as safety. One of the approaches is bringing more data-driven flexibility in how infrastructure is used.

Examples:

Clockwise from top left: CurbLR, Chicago’s Mobility, New York Times, Roboat

• CurbLR by Shared Streets — CurbLR is a proposed data standard for curb regulation data to aid in dynamic curb management.
• Chicago’s Mobility by CLEVER°FRANKE— Using data to share CMAP’s perspective on the mobility challenges and strategies for the region.
• New York Times — How Manhattan could look different when cars are not given priority on the streets.
• Roboat by AMS Institute —Autonomous boats instead of cars to transport goods and people, and monitor the environment on Amsterdam’s canals.

Driver 2. Push for sustainability

As the increased urban populations and congestion result in additional air pollution, a second driver is the push for sustainability. Not only for the local environment, but also to meet global emissions targets. This means, reducing miles driven by cars, introduction of congestion zones, vehicle restrictions and promoting alternative modes of transportation like biking or e-scooters, and electric vehicles.

All these require data-driven tools to define strategies, monitor and manage outcomes.

Examples:

Clockwise from top left: Transparent Charging, Flow, Air Quality Smart Watch, The Verge

• Transparent charging by Incredible Machine —Charging system that adapts to fluctuating energy sources in a fair, transparent and smart way.
• Flow by Plumelabs — Flow is a handheld air pollution sensor that provides personalized recommendations for your commutes across the city.
• Air quality smart watch by CLEVER°FRANKE — An experimental smart watch interface to experience environmental data in a more intuitive way.
• The Verge —How cities are transforming as electric bike sales rise.

Driver 3. Technological progress

The third enabling driver is technology. The combination of ubiquitous mobile internet access, cheaper sensors, algorithm improvements and increased processing power is driving a broad set of technological leaps. From mobile apps, to dockless scooters and autonomous vehicles.

Some of these technologies, like autonomous vehicles, have a long way to go until they are ready to go mainstream. Still they have the potential to completely change the city, mobility and vehicle ownership as we know it today. And these vehicles will be both consumers and producers of large amounts of data.

Examples:

Clockwise from top left: City Scanner, Bluecyber, Picterra, Viscando

• City Scanner by MIT Senseable City — Regular city and public transport vehicles with added sensors gather detailed data on local air and road quality.
• Bluecyber by CLEVER°FRANKE — Sensor-driven real-time traffic flow insights aid cities in managing busier streets.
• Picterra — Combining drones and AI to quickly assess the condition of roads.
• Viscando — Detailed analysis of traffic patterns and behavior through sensors and machine learning.

Driver 4. Resilient cities

The current COVID-19 pandemic has demonstrated that we will need to invest in making cities and mobility more resilient.

Much is yet unclear about the impact in the long term. Likely more people will work from home as well. Also increased demand for more personalized and individual transport is expected. Some governments are now fast tracking rollouts of micro-mobility options like e-scooters. Cities are turning previously car-dominated streets into shared spaces and pedestrian zones, to allow for physical distancing.

Over time a more fundamental rethinking of how we build and structure cities is needed. Not only for potential future pandemics, but also to deal with the impact of climate change and changing mobility needs.

Examples:

Clockwise from top left: BirdsEye, CNN, Mobility during COVID-19, Amsterdam Heat Map

• The BirdsEye data platform by CLEVER°FRANKE — For the Abu Dhabi D.M.T. BirdsEye enables exploration of mobility data and future scenarios.
• CNN — Examples of how the design of cities could change to make them more resilient in a future pandemic.
• Mobility data to track risk in re-opening — Examples of how mobility data is used to track pandemic impact and spread.
• Amsterdam Heat Map by CLEVER°FRANKE — Helping people find cooler, less crowded parts of the city. With the AMS institute and Witteveen+Bos.

Driver 5. Equitable access and social impact

A risk with this promise of progress, is that it only benefits the fortunate few. We must ensure equitable access to mobility and the enabling technology. Not only in terms of affordability, but also in having the skills to use it. Touchless tickets for public transport might be great, but not if they require an expensive smartphone or using a complex app. Regretfully, this is still often the case.

With the increased reliance on data, privacy is a key topic. We need better options and regulations to have control over how data that represents us is collected, stored and used.

This requires design from the human perspective. Based on robust research, input from communities and data-driven insights, combined with sensible regulatory frameworks.

Examples:

Clockwise from top left: Urban Mobility Index, Shared Mobility Principles, District Mobility, Remix Transit

• Urban Mobility Index by HERE Technologies — The Urban Mobility Index compares livability of cities across a wide variety of mobility metrics.
• Shared Mobility principles — Principles aimed at providing a framework for equitable, safe and sustainable shared mobility.
• District Mobility by CLEVER°FRANKE — Data and visualizations to share solutions to the growing mobility challenges of Washington DC.
• Remix Transit Planning tool — Sketch out transit routes while directly seeing impact on metrics such as access to jobs.

Data and Urban Mobility opportunities

Based on our experience working with partners in this domain we see a number of opportunities to better apply data design in small and large ways.

Spread insights further

• Often data and insights remain with a small group of experts within an organization. Creating simple internal tools to explore data allows analysts to share their insights and others to explore the data collaboratively. The further the data goes, the more insights and value it brings.
• Start with simple prototypes and a clear focus. Proof value before starting larger projects, discover new opportunities and audiences along the way. Otherwise, it is easy to get stuck adding ideas and features without getting results.
• Combine your own data with publicly available sources, to explore correlations and discover underlying stories and opportunities. Weather and car crash data are great examples.
• Think beyond the map. Although it is a logical starting point for mobility data, applying, or combining with, other visualization techniques can lead to new insights. For example, graph trends of specific locations over time or use network diagrams to highlight routes and connections.

Bring it to the community

• Innovation in mobility relies on support from the community. Use data for storytelling to drive engagement and thought leadership. For example to share strategies and plans for infrastructural changes.
• Many cities and organizations have created open data portals, but most of these remain complex to use and navigate, while data are often outdated. Creating easy to use platforms allows the public to explore open data sets. A proven way to improve transparency and support public initiatives. This applies in particular to long term commitments like Vision Zero. Again focus on keeping it small and simple at first.
• Combine data before and after mobility and infrastructure projects to show the impact on mobility, traffic and other metrics. For example, when new street designs get implemented or the impact of the ride share services on traffic.
• Improve multi-modal journeys and seamless transfers across modes by connecting platforms together. Better journey planning improves transit accessibility. And data from actual journeys enable optimization of both routing and planning.

In closing

These are exciting times for urban mobility filled with great opportunities to reshape cities and mobility to create more livable, sustainable and equitable cities. If we start small, iterate based on insights and keep a focus on the human perspective there is a bright future ahead.