Transforming urban transportation challenges with simulation

May Mobility (May) is unlocking a better life through self-driving transportation. May delivers solutions that work in today’s communities to accelerate the path toward a future where people can drive less and live more. The company’s goal is to realize a world where self-driving systems increase the reliability of transportation, make the roads much safer, and encourage better land use in order to foster more green, vibrant, and livable spaces.

Ann Arbor, MI

Headquarters

2017

Founded

230

Employees
(in 2022)

“By focusing on our real-world deployments, we’re able to learn what makes our riders happy while also building out our operational capabilities. Applied’s team has equipped us with tools to enable this development approach that is economically viable at the same time.”

Edwin Olson
Co-Founder and CEO, May Mobility

Goals

May Mobility operates autonomous shuttle services in several U.S. cities to complement public transportation and provide a safe, sustainable, and shared mobility solution. While its self-driving shuttles are attended by Fleet Attendants (safety drivers) today, May aims to deploy fully-autonomous vehicles in expanded geographic coverage in the future.

The safety and comfort of riders are the utmost priorities for May’s vehicles in operation. To achieve its vision for autonomous system development, May is focusing on the following areas of development:

Agile development: Resolve operational issues immediately on production vehicles.

Catching regressions before deployment: Prevent regressions from entering the production vehicles before weekly and monthly software updates are shipped.

Active fleet learning: Continue to improve autonomous driving capabilities by turning anomalies seen in the field into test cases for development and validation.

May Mobility operates in Grand Rapids, MI

“The Applied team has been a good partner in adding features we ask for, which in turn set off the Simulation Flywheel internally. In the future, we are planning to use simulation to better classify disengagements.”

Kamil Litman
VP of Software, May Mobility

Approach

May has partnered with Applied Intuition to bring more agility and efficiency to testing the safety, comfort, and performance of their autonomous shuttle technology.

Riders in a May Mobility autonomous shuttle outfitted with Clean Shuttle enhancements for a safe, clean rider experience.

Simulation Flywheel: Applied’s collaboration to deliver on May’s feature requests set off a ‘Simulation Flywheel’ - a test-driven approach in which development becomes faster and regressions happen less frequently as the development team runs more scenarios, test cases, and continuous integration (CI) tests.

Custom observers to test comfort: Custom observers developed for May’s development team test the comfort experience of riders.

Soak testing before software update: A simulation-based approach replaces traditional long soak tests done on fixed routes in the real world. Different scenarios can be created quickly to verify safety before a software update is pushed.

Automated assessment of drive data: Applied’s solution programmatically finds anomalies and other events of interest from hours of drive logs collected by the fleet of vehicles and turns them into test cases for re-simulation.

Continuous development: Applied’s CI system is used to identify regressions in the autonomous driving software and root causes before the new software is deployed.

Faster development for new capabilities: Applied’s simulation tool supports faster algorithm development, allowing for testing new functionality such as an obstructed unprotected right-hand turn or training system parameters over a database of scenarios.

“We leverage Applied’s simulation tools to accelerate the pace of engineering, to catch regressions early in the dev/test/deploy cycle, and to analyze the real-world performance of the system.

We save time otherwise spent manually root causing and debugging software in the field, while also gaining detailed insights into system performance.”

Sean Messenger
Senior Robotics Engineer, May Mobility

Impact

Time and resource savings

May Mobility has saved hours of engineering time by automatically catching regressions in simulations before the software is deployed to the fleet.

High-quality rider experience

Catching regressions in simulation instead of encountering them in the real world ensures a high-quality rider experience.

Expansion into new ODDs

May is able to expand to new ODDs faster as a result of incorporating simulations into May’s development cycle.

Transforming urban transportation challenges with simulation

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