Introducing On-demand Planning, a new transit tool powered by data from 100M rides. See how it works.

How to make autonomous transportation useful

  •   4 min read

Learning from real-world examples, we’ll show you how to leapfrog to a new TransitTech paradigm while solving for real public transportation needs.

article featured image

If you pull up the citywide public transit app in Arlington, Texas, you’ll find yourself with two options: on-demand microtransit vehicle, or on-demand self-driving vehicle. 

Under the leadership of Mayor Jeff Williams, this city of 400,000 (located between Dallas and Fort Worth) is at the forefront of making technology a useful part of its public transportation. 

Arlington RAPID (Rideshare, Automation, and Payment Integration Demonstration) provides autonomous transportation across downtown Arlington with five autonomous vehicles, including one that is wheelchair accessible. Funded by a $1.7 million Federal Transit Administration grant, RAPID is an innovative partnership between Via, which provides the software and operations, May Mobility, which powers the autonomous fleet, the City of Arlington, and the University of Texas at Arlington (UTA). RAPID has already served 15,000 rides this year, and it’s only growing from there.

Transit agencies and cities interested in bringing AVs to their communities can use Arlington’s approach — integrating AVs into existing public transit — as a roadmap. 

Arlington offers a glimpse into the future of autonomous vehicles (AVs). Over time, AVs will be fully integrated into communities’ public transportation systems, as one mode among many. This is different from how AVs are often deployed today — as unique programs separate from broader mobility services. 

The reason for integrating AVs with transit is twofold:

  1. Due to the current state of AV technology (we are still years away from humanless driving in all locations and conditions), a pilot crafted independently from other transit modalities will only be able to offer limited usage (and value) to customers.
  2. The cost of running even a limited AV service is substantial. Most communities will likely require significant public funding to deploy AVs and to ensure that the service is affordable and accessible by all community members. 

So, what can other cities learn from Arlington to accelerate the deployment of autonomous technology to solve real transit needs?

Tip: Don’t silo your AV service.

By adopting Arlington’s approach, cities and transit agencies can unlock the benefits of AVs. Historically, the planning process for many AV deployments has been conducted independently from existing mobility services like fixed route buses and trains, demand-responsive transit (DRT), and light rail. These pilots were usually situated in localized environments — university and corporate campuses, residential communities, or a short route open to the public — without much thought given to how these one-off services could connect to and supplement broader transit services.

Evolution of autonomous vehicles and demand-responsive transport in Arlington, Texas

Of course, there are reasons for this siloed approach. Some organizations are looking merely to showcase the latest technology or learn from bite-sized public interactions with self-driving vehicles. Others find themselves limited by budgets that only allow for the use of a few vehicles for a limited period of time. In addition, the digital infrastructure required to integrate AVs into the broader transit network necessitates outside technical support, and coordinating a complex ecosystem of players (likw public transit agencies, AV providers, regulators, fleet managers, and more) can be difficult and time-consuming. 

Yet by deploying AVs within broader mobility services, public transportation providers and private operators can derive significant value:

  • More than a moonshot innovation, AVs have the potential to serve a real purpose in the present by filling existing transportation gaps, such as first-and-last mile connections or transit deserts. 
  • Mixing AV and non-AV fleets within a network can minimize costs while extending the service offering substantially. 
  • Integrating AVs into public transit democratizes cutting-edge autonomous technology to a broad range of riders. 
  • By tasking AVs with real-world transportation use cases, transit providers can gain more meaningful insights into AV utilization than those obtained in siloed pilots.

At Via, we come equipped with the simulation and planning tools to design and scope AV services to meet a range of goals. Whether the objective is to provide first-and-last mile transportation for commuters or test Level 4 autonomous technology on public roads, we can work to define a service zone and then select optimal roads, routes, and stops considering speed limits, topography, number of intersections and more. We’ll also model ridership demand and travel patterns to determine optimal AV type, capacity, and fleet size.

Learning to leapfrog.

This brings us back to Arlington RAPID. Taking a closer look into how the City of Arlington integrated an AV service with its broader public transit system can provide insights to accelerate the process in other communities. 

Arlington leveraged its existing tech-forward services to accelerate development of its AV deployment. Arlington On-Demand, the City’s microtransit service with Via, initially launched in 2017 to replace a limited fixed-route bus system. The service began with 16 vehicles across a 26 square mile service zone and gradually expanded to the entire city: from 28 vehicles across a 40 square mile service zone in 2020 to 70 vehicles across a 100 square mile service zone in 2021. Since launch, Arlington’s public transit ridership has increased over 10X.

Arlington adopted AVs in a similar phased approach. In 2017, the city launched a pilot with AV provider Easymile, in which one autonomous shuttle operated at low speeds on off-street trails to connect the city’s Entertainment District with remote parking areas. Next, in 2018, the city partnered with Drive.ai to deploy three robotaxis on limited public roads in the Entertainment District. These robotaxis operated alongside non-AVs as a separate on-demand ride-hailing service on a limited route, but were not part of the city’s public transportation network. 

Autonomous on-demand vehicle in Arlington, Texas

This all changed with RAPID, which, as of March 2021, offers on-demand autonomous transportation on public roads throughout downtown Arlington and UTA’s campus. RAPID is the first service in the US to integrate autonomous vehicles into existing public transit — let alone offer riders a choice between AVs or non-AVs within a single smartphone app interface. 

By following insights borne out of Arlington’s AV journey, cities and agencies can leapfrog the first few years of experimentation and start immediately assessing how autonomous vehicles fit into their broader transit networks to provide real benefits for riders. Now, transit providers can employ AVs to derive actionable insights on autonomous transit, solve their communities’ current transit needs, make use of local, state, and federal funding, and provide a diverse group of riders the opportunity to experience the unique benefits of autonomous technology, from day one.

Interested in learning more about how to deploy AVs within your public transportation system? Via works with communities every step of the way — from designing autonomous networks to managing autonomous fleets. Reach out to our team at partnerships@ridewithvia.com.  

World-changing ideas. Right in your inbox.

Be the first to know about the latest transportation news and innovations.

Mailbox illustration.

Congrats — you're in!

Please fill out the following details:

Interested in learning more about our unique services? Sign up!

Thank you!

We're grateful to have you in our community.

Thumbs up illustration