May Mobility develops autonomous vehicles utilizing a Multi-Policy Decision Making (MPDM) system, a real-time reinforcement-learning AI that enables vehicles to learn and adapt to their environment every 200 milliseconds. This technology addresses the challenge of safely navigating unpredictable driving scenarios, allowing for efficient deployment of autonomous transportation solutions in diverse settings.
Funding
$105M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
+4Founders
Product
Problem
Existing autonomous vehicle (AV) systems struggle to adapt to unpredictable and novel driving scenarios due to limitations in pre-programmed training data. This can lead to unsafe or inefficient operation in dynamic real-world environments. Traditional AV solutions often require extensive and costly data collection and mapping.
Solution
May Mobility offers an autonomous driving solution powered by a Multi-Policy Decision Making (MPDM) system. This real-time, reinforcement-learning AI enables vehicles to continuously learn and adapt to their environment, making driving decisions every 200 milliseconds. The MPDM system allows the AV to generate training examples relevant to its current environment and learn while driving, improving its ability to react to new situations. This approach facilitates safer and more efficient AV deployment by enabling vehicles to handle unexpected events and unique driving scenarios.
Target Audience
The primary target audience includes transit agencies, cities, campuses, organizations, and businesses seeking to implement autonomous transportation solutions to address transportation gaps.
Features
- Multi-Policy Decision Making (MPDM) system: A real-time, reinforcement-learning AI algorithm.
- On-the-fly learning: Vehicles generate training examples and learn while driving.
- Continuous adaptation: System adapts to new situations and driving scenarios every 200 milliseconds.
- Combined sensor stack: Monitors the road and runs simulations on possible situations and hazards.
- ADA-compliant vehicles: Wheelchair-accessible Toyota Siennas can accommodate multiple riders.