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Protecting rider privacy in micromobility data

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By: Tarani Duncan

In 2018, 84 million trips were taken on shared bikes and scooters. The success of micromobility is a boon for local governments who want to better understand how their citizens are moving around cities. The data generated by private mobility companies can help local governments understand how new mobility projects impact transit, how residents use different types of space, where gaps in transit exist, and more — and all of these insights can help governments build better, smarter cities for the future. This is a great thing!

However, it’s critical to ensure that end-user privacy is protected first and foremost in this treasure trove of mobility data. At Mapbox, location is the core of our business, and we’ve taken great care to protect user privacy while relying on location data to drive product improvements, and be a resource for others to understand considerations and best practices when building with sensitive user data.

Cities are beginning to take the necessary steps to create standardized reporting protocols, to share and use the data from private mobility operators. But in some cases, these protocols still need to be tweaked to protect user safety.

One example is the Mobility Data Specification, or MDS, released in September, 2018 by The Los Angeles Department of Transportation. MDS is a set of APIs that provides cities with de-identified data about dockless mobility (DM) projects (e.g. shared bikes and scooters.) Cities adopting MDS require private mobility operators to provide point-by-point routes coupled with start and end times of every trip taken.

Location data of this format poses a serious risk to rider privacy. Individual, unaggregated route records can be re-identified with ease, which can expose sensitive information about individuals.

Instead of a protocol that collects such specific user data, here are some thoughts on how cities can 1) surface key operational insights and 2) create transparency needed to track permit compliance, while preserving user privacy.

Use Aggregated Data to Prove Out Investment in Bike Lanes

Cities can surface actionable insights about new infrastructure investments by aggregating route data across road segments, vehicle types, days of the week, and hours of the day. Data points demonstrating the distribution of “total vehicle miles traveled” can be paired with compelling visualizations to help transportation planners make commonsense investments in local infrastructure.

Use Heatmaps to Site High-Impact Mobility Hubs

At their best, bike and scooter programs work to complement the current transportation network by filling in the difficult-to-reach gaps left by personal vehicles or fixed-route transit. Cities can use heatmaps to aggregate origin and destination data to identify desirable areas for mobility hubs. Origin and destination data can be a powerful aid in crafting service level agreements that ensure operators successfully service high-demand and transit-underserved parts of town.

Use Asset Tracking Dashboards to Monitor Compliance, Safety and Equity

Shared scooters and bikes need regular inspections

Scooters are notorious for their short lifespan and should receive aggressively-cadenced inspections by trained employees. Cities can use an asset tracking dashboard to show the number of broken bikes or scooters in the field in relationship to the number of available bikes or scooters. They can also ask operators to provide a timestamp of last inspection to surface infrequently maintained bikes or scooters currently in operation. This data helps cities ensure scooter and bike companies are offering safe and reliable services.

Cities can track fleet size compliance in real-time

Some cities cap number of scooters or bikes allowed in service. Cities can use a dashboard that surfaces historic and real-time numbers of available bikes or scooters in field by operator. This helps cities identify when scooter and bike companies are above or below permitted fleet size requirements.

Cities can monitor obvious parking violations in real-time

Some areas of town, like National Park Land, are off-limits to dockless vehicles. Using an operations dashboard, cities can flag out-of-bounds vehicles in real-time.

Cities can ensure equitable distribution of fleets

Being able to track available scooters and bikes in real-time allows cities and transportation authorities to monitor operator compliance with equity requirements. During JUMP’s pilot in San Francisco, the operator regularly exceeded equity requirements by ensuring over 20% of their fleet remained available in transit underserved communities.

There are many great ways that the data from micromobility companies can help improve infrastructure, mobility, and access in our cities, but it’s important that, as a group, we figure out the right way to facilitate this data transfer while maintaining users’ privacy.

Discussing the issues and challenges is an important first step. If you’re interested in learning more, we’re hosting a Micromobility Happy Hour in the Mapbox SF office on Wednesday, May 1st. We’ve got some of the top minds in the space joining us for a spirited conversation on how we can improve accessibility and adoption of micromobility technologies and use the data to improve our cities. RSVP here. (Space is limited.)

Tarani Duncan


Protecting rider privacy in micromobility data was originally published in Points of interest on Medium, where people are continuing the conversation by highlighting and responding to this story.


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