How to use mobility data to plan effective transit networks

Designing and operating successful mobility services starts with collecting the right data.  Measuring success, which can be defined by the efficiency, profitability and/or sustainability of a service, as well as its ability to serve all riders equitably, requires robust data about travel behaviors. With this data in hand, transit agencies can uncover operational inefficiencies and transportation gaps — areas in their service zone that lack adequate transit options — and begin to address these important issues.

Mobility data allows us to answer questions such as: where are people going? What kind of transportation are they using? What factors affect their choices? Where are the transportation gaps?

In this blog post, we break down what mobility data is, how to collect it and how it can be used to benefit riders, transit agencies and urban planners.

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What is mobility data?

For our purposes, mobility data is information about how people move from one point to another. It’s usually recorded as a series of geographical points with additional layers that contextualize the information. For instance, the data may include elements like time, date, mode or speed of travel and who is taking the trip. It may even include information that affect mobility patterns, such as weather, pollution and traffic congestion. In other words, mobility data goes beyond dots on a map: it creates a rich picture of how a community moves.

The benefits of mobility data for urban and transit planning

Thorough data collection plays a key role in overcoming diversity data gaps and bolstering transportation equity — the concept that transit systems should be designed to provide fair access to goods and services to all, according to their needs.

Mobility data helps transit providers:

• Engage in more effective transit planning;
• Boost potential economic growth by increasing interconnectivity;
• Identify potential new markets;
• Understand where mobility access is lacking;
• Provide enhanced options for commuter transit which helps cut the number of vehicles on the road, and therefore CO2 emissions;
• Build automated processes that reduce operational costs and enhance efficiency;
• And provide riders with real-time travel information, improving the passenger experience.

A key aim when collecting mobility data should be to ensure no one is excluded from the story.  Of particular importance is data that provides insights into the travel behaviors of populations that have traditionally been marginalized by transit, such as low-income, senior or disabled riders.

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How to acquire useful mobility data

So what kind of data should you collect? Consider the Five Ws of ridership:

1. Who are your riders?
2. What is their destination?
3. When are they traveling?
4. Where are they traveling from?
5. Why are riders picking this particular mode of transportation?

This type of information can be obtained from various transit and sociodemographic sources, such as census and jobs datasets, mapping APIs, travel surveys, General Transit Feed Specification feeds and national transit databases.

As you build out your mobility databases, keep the following tips in mind:

• If you’re designing a travel survey, make sure to ask respondents about their demographic information, if appropriate.
• Ensure data is sufficiently disaggregated so that you can dig deep into how different population groups might travel — for example, people of different genders, ethnicities or ages.
• Try to collect the most up-to-date datasets available to you. For instance, rather than using average ridership data that is only published every 3 months by American Public Transportation Association (APTA), use Transit App’s live ridership tracker!​
• Stay on top of data security and compliance frameworks in order to protect riders’ privacy.

Data gathering can be a time-intensive task, and many agencies struggle with resource and budgetary constraints. Another common challenge is determining how much data to collect — you don’t want to build up such a huge repository of information that you struggle to categorize, access and leverage your data to its full potential.

Luckily, there are a number of data solutions that allow agencies to leverage information and put data-driven decision-making at the heart of their operations. A good example is Spare Realize, which helps users visualize and simulate mobility patterns using advanced machine learning algorithms, making it easy for transit planners to derive meaningful insights from their mobility data.

Explore the data landscape

After you’ve developed a holistic understanding of who your riders are and what they need from transit services, it’s time to turn your data collection efforts to geography. Where exactly should your transit services operate to best meet those needs?

Most modern transit software platforms collect datasets that can provide insights on existing transit demand in an area, including the different types of trips taken by a variety of rider groups. If the data indicates high, steady demand, you may wish to implement fixed-route buses. Whereas areas with lower or fluctuating travel volumes are good candidates for demand-based transit.

In addition, consider the location of key facilities and services in the area, the kind of transit that is (or isn’t) currently available in connection with those places and how your services may help change things.

If you're planning to introduce demand-responsive services like microtransit and paratransit, you'll need to set up a “prototype zone” based on factors such as population, jobs coverage, existing transit services, and ridership potential.

In some cases, you might rely on detailed suggestions from transit consultants, who conduct workshops and surveys to establish metrics to track the success of your zone. If you don’t have such data, mobility management solutions can help guide you towards designing zones in areas that will likely benefit the most from new or additional services.

While in the early stages of transit planning, look for areas of unmet needs, such as transit deserts, underserved communities, or areas likely to be impacted by first mile-last mile challenges (for instance, suburban areas where the closest bus stop isn’t within walking distance). It’s helpful to display your data spatially, as transit systems exist in the real, three-dimensional world; missing the spatial angle often means missing a key part of the story.

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Stay on top of trends

Travel surveys are a great way to generate data and stay on the leading edge of mobility trends.

Conducting travel surveys has historically been a convoluted and cumbersome process as it’s typically done in-person or through emails with low conversion rates. Spare has shifted the playing field by offering in-app surveying tools that streamline the survey process, ultimately giving riders and drivers a more prominent voice.

Here are a few examples of surveys you may wish to conduct in order to better understand your users:

• Net promoter score surveys: to measure satisfaction among your riders and drivers.
• Demographic surveys: to better understand the Five Ws of your rider population.
• Pulse surveys: to get feedback about a specific issue or service change.

Whether you are looking to increase ridership, improve the social equity of public transit or delight your riders, the journey begins with meaningful data.

Collecting mobility data is a key component of running mobility services that are accessible and successful in meeting the needs of riders. If you want to learn more about travel surveys or how Spare can help your on-demand transit service make data-driven decisions, drop us a line at [email protected].

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