About
May Mobility is a cutting-edge autonomous vehicle company on a mission to make transit more sustainable, safe, accessible, and equitable. At the heart of its technology is Multi-Policy Decision Making (MPDM), a real-time reinforcement-learning AI algorithm that sets it apart from traditional AV systems. Unlike competitors limited by pre-collected training data, May Mobility's vehicles continuously generate and learn from training examples relevant to their current environment—updating every 200 milliseconds. This enables vehicles to simulate countless scenarios on-board and select the safest course of action in any situation, no matter how unexpected. May Mobility's autonomous services are live and expanding, with deployments spanning suburban Atlanta (via Lyft), rural Minnesota, and Tokyo Bay. The company has forged major strategic partnerships with Lyft, Uber, and Grab, positioning its AV fleet for large-scale commercial rollout. Its solutions address both ride-hail and fixed-route transit use cases, serving cities, commercial campuses, and transit agencies. By enabling AVs to be deployed at a fraction of traditional cost and time, May Mobility is accelerating access to safer, more efficient transportation for a broader range of communities. Its technology is designed for the real world—handling edge cases, dynamic environments, and novel driving scenarios that stump conventional systems. May Mobility is ideal for municipalities, transit agencies, ride-hail platforms, and enterprise campuses seeking scalable autonomous mobility solutions.
Key Features
- Multi-Policy Decision Making (MPDM): A proprietary real-time reinforcement-learning AI that allows vehicles to simulate and evaluate multiple driving policies every 200ms, enabling safe reactions to unexpected scenarios.
- Continuous On-Board Learning: Vehicles generate and learn from training examples relevant to their current environment while driving, rather than relying solely on pre-collected datasets.
- Ride-Hail & Transit Integration: Autonomous vehicles are deployable via major ride-hail platforms including Lyft and Uber, as well as fixed-route transit and commercial campus services.
- Scalable AV Deployment: MPDM enables AVs to be deployed at a fraction of the cost and time compared to traditional autonomous driving approaches, making broader rollout feasible.
- Global Operations: Active deployments across diverse environments—from suburban Atlanta and rural Minnesota to Tokyo Bay—demonstrating adaptability across geographies and use cases.
Use Cases
- Cities and municipalities deploying autonomous shuttles to provide affordable, equitable last-mile transit solutions in underserved or low-density areas.
- Ride-hail platforms (Lyft, Uber) integrating May Mobility's AV fleet to offer self-driving ride options to their existing customers.
- Corporate and university campuses using May Mobility vehicles to provide on-demand autonomous circulator services for employees and students.
- Transit agencies augmenting fixed-route bus networks with autonomous vehicles to reduce operating costs and extend service hours.
- International mobility operators and investors (e.g., Grab in Southeast Asia) licensing May Mobility's MPDM technology to build regional autonomous ride-hail networks.
Pros
- Real-Time Adaptive AI: MPDM technology continuously updates vehicle decision-making every 200ms, giving the system a human-like ability to adapt to novel and unpredictable driving situations.
- Strong Industry Partnerships: Collaborations with Lyft, Uber, and Grab provide immediate scale, distribution, and commercial viability for autonomous ride-hail services.
- Proven Real-World Deployments: Operating in multiple geographically and culturally diverse locations demonstrates practical reliability beyond controlled test environments.
Cons
- Limited Geographic Availability: Autonomous ride services are currently available only in select cities, limiting access for most potential users.
- Enterprise/B2B Focus: The technology platform is primarily targeted at transit agencies, cities, and ride-hail platforms rather than individual consumers or developers.
- Opaque Pricing: Pricing for deploying May Mobility's AV technology is not publicly listed, requiring direct engagement with the sales team.
Frequently Asked Questions
What is MPDM and how does it differ from other AV technologies?
Multi-Policy Decision Making (MPDM) is May Mobility's proprietary real-time AI algorithm. Unlike traditional AV systems that rely on static pre-collected training data, MPDM generates training examples from the vehicle's current environment and learns on the fly every 200 milliseconds, enabling safer responses to unexpected situations.
Where can I take a ride in a May Mobility autonomous vehicle?
May Mobility's autonomous ride-hail service is currently available in the Atlanta suburbs via the Lyft app, with additional deployments in locations such as rural Minnesota and Tokyo Bay, Japan.
Who are May Mobility's key partners?
May Mobility has strategic partnerships with major ride-hail and mobility platforms including Lyft, Uber, and Grab, enabling broad commercial deployment of its autonomous vehicle fleet.
What types of services does May Mobility offer?
May Mobility provides autonomous vehicle solutions for ride-hail services (via platforms like Lyft and Uber), fixed-route transit for cities and municipalities, and commercial campus mobility programs.
Is May Mobility available internationally?
Yes. In addition to US deployments, May Mobility operates in Tokyo Bay, Japan, and is expanding into Southeast Asia following an investment from Grab announced in October 2025.
