COVID-19 & Transit: Technological Innovations in Social Distancing

Transit. 2020. Enough said?

Do you take transit? Work in transit? If you answer yes to either, your experience is jarring: Transit has been turned upside down. News headlines have covered everything from decreased ridership and services, to budget cuts, and federal stimulus relief for transit systems.

Riders are adjusting to a dynamic environment in which service is often reduced and social distancing is precarious. In response, transit providers are combining practical solutions with innovative thinking to make the most of reduced services and offer riders peace of mind.

But pressure on agency budgets makes it hard to roll out new solutions, much less fulfill plans for major projected annual investments – investments that, if avoided, could balloon long term maintenance and capital budgets and negatively impact the level of service provided long after the COVID-19 Pandemic.

So, how are agencies delivering innovations that demonstrably help riders? By overcoming these obstacles through strategic thinking backed by appropriate technology and software. The following examples spotlight real agencies’ successes in making transit safer and more sustainable, with relevant lessons for peer operators.

Take these examples:

Real-Time Occupancy

In the age of social distancing, small enclosed spaces like buses and trains have unsettled some riders. Yet, many cautious travelers continue to take transit, as transit-provided mobility is indeed essential to daily life for many of our neighbors.

This is where the arrangement becomes tricky: How can operators promote social distancing opportunities when budget cuts have reduced service frequency and the number of vehicles in operation?

One response is through better real-time information. The first step is vehicle arrival predictions, but alone, this may not be enough - on-time information says nothing about a transit vehicle’s capacity and whether it is standing room only or twenty percent occupied. Adding accurate information about a vehicle’s current occupancy lets riders choose to skip a more crowded bus arriving in 5 minutes in favor of one arriving in 15 minutes, depending on crowding. This information can positively affect riders’ everyday transit experience.

How agencies can deliver this crowding information depends largely on technology infrastructure and the methods available to leverage those resources:

  • Data Collection: The USDOT describes Automated Passenger Counters (APCs) as “electronic machines near the doors of a transit vehicle that count the number of passengers that enter and exit at every transit stop”. APCs can employ different methods for detecting and counting passengers and some transit agencies have long utilized these systems to inform operational and service planning decisions based on the ridership data they collect. However, not all agencies have installed APCs, and for agencies that have done so, fleet coverage may be incomplete.

  • Data Availability: For vehicles outfitted with APCs, the timeliness of data is crucial. Is data simply stored within the units to be downloaded at a later date, whether manually or automatically? Or is information instead transmitted in near real-time to the agency’s relevant technology applications?

  • Data Distribution: With accurate and timely data in hand, transit providers must have practical means to disseminate that information to riders. Agency websites, trip planners and mobile apps are the most common platforms used to convey crowding data. However, technical staff must be able to translate the APC data into a data standard / specification that trip planners and mobile apps can consume and then display in meaningful ways.

The New York Metropolitan Transportation Authority was one of the first transit operators in the U.S. to publish crowding data in its mobile app. In response to rider concerns stemming from the COVID-19 pandemic, this new feature was added to the MYmta mobile app, using near real time APC information transmitted from MTA buses. While not all buses in the MTA’s large fleet are equipped with APCs, the number is growing.

To facilitate the process, MTA automated the gathering, aggregation, and transformation of its APC data into GTFS-RT (Real Time) format. In other words, the data is automatically gathered and translated into a format that makes it possible to display occupancy information in the MYmta app for every bus with an APC installed. In fact, the MTA’s work also makes their occupancy data available to all third-party apps through the same GTFS-RT feed.

Projected Occupancy

Agencies with similar technology stacks can accomplish the same goal. And for some transit operators where real-time occupancy information is unavailable, historical passenger count data has initially shown to have value in estimating and projecting occupancy.

The Washington Metropolitan Area Transit Authority (WMATA) recently launched a similar approach. Since WMATA’s MetroRail service is not equipped with APCs, crowding predictions are transmitted to riders on both its website and busETA app based on projections derived in part from recent crowding data.

However, WMATA’s bus fleet is fully equipped with APC units, enabling the agency to display near real-time crowding data for those vehicles. And like New York MTA, WMATA makes this data feed open and available to third-party transit and mapping applications.

Predicting the Future

How many transit operators will provide real-time crowding information? To what degree will occupancy data increase peace of mind and ridership? Time will tell, but transit agencies and riders alike have a vested interest in safety and efficiency.

Beyond the age of the COVID-19 pandemic, public transit occupancy data may be here to stay. The advances in real-time occupancy information once catalyzed by necessity could establish a new normal which includes increased convenience for riders.

The same could be true for other adaptions and innovations, but that would call for a different blog post…

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Contact Reagan Lynn, Client Engagement Manager at rlynn@camsys.com