REDWOOD CITY, Calif. — Helm.ai has announced the development of DNN (Deep Neural Network) foundation models designed to predict the behaviors of vehicles and pedestrians in complex urban scenarios. They have also trained these models to predict the path an autonomous vehicle would take in those situations. These capabilities are critical ingredients of the decision-making process for self-driving cars. Helm.ai leveraged its industry-validated surround view full scene semantic segmentation and 3D detection system as the core representation. This enabled training intent prediction and path planning capabilities. Additionally, the foundation models are trained using the company’s proprietary Deep Teaching technology. This helps achieve broad predictive capability in a scalable way.
Helm.ai’s technology learns directly from real driving data. It uses the company’s highly accurate and temporally stable perception system. The system captures information about complex behaviors of vehicles and pedestrians. This leads to DNNs that automatically learn subtle yet important aspects of urban driving. The foundation models powering Helm.ai’s intent and path prediction gather input from a series of observed images. They generate predicted video sequences that represent the most likely possible outcomes of what happens next. The models also provide a predicted path for the autonomous vehicle that is consistent with the intent prediction. Both the intent prediction and path prediction capabilities are essential for planning the safest optimal action by the autonomous vehicle.
Importantly, the Helm DNN foundation models for intent prediction and path planning are trained in the highly scalable Deep Teaching paradigm. This enables unsupervised learning about complex urban driving scenarios directly from real driving data. This approach circumvents cumbersome physics-based simulators and hand-coded rules. These are insufficient to capture the full complexity of driving in the real world. Helm.ai optimizes the development and validation pipeline specifically for high-end ADAS L2/L3 mass production software. It can also be directly applied to L4 fully autonomous applications. Moreover, the Helm.ai scalable AI approach readily generalizes to robotics domains beyond self-driving vehicles.
Helm.ai is building an AI-first approach to autonomous driving. Design it to seamlessly scale from high-end ADAS L2/L3 mass production programs all the way to large-scale L4 deployments. The company’s software-only platform is hardware-agnostic and vision-first, addressing the critical perception problem for vision. It also incorporates sensor fusion between vision and radar/lidar as needed. Today’s announced technology advancements accelerate the value of Helm.ai’s software offering. They pave the way for scalable development and validation of AI-based intent prediction and path planning software for autonomous vehicles.
“At Helm.ai we are pioneering a highly scalable AI approach that addresses high end ADAS L2/L3 mass production and large scale L4 deployments simultaneously in the same framework,” said Helm.ai CEO Vladislav Voroninski.
“Perception is the critical first component of any self-driving stack. The more comprehensive and temporally stable a perception system is, the easier it is to build the downstream prediction capabilities, which is especially critical for complex urban environments. Leveraging our industry-validated surround-view urban perception system and Deep Teaching training technology, we trained DNN foundation models for intent prediction and path planning to learn directly from real driving data, allowing them to understand a wide variety of urban driving scenarios and the subtleties of human behavior without the need for traditional physics based simulators or hand-coded rules.”
Helm.ai closed a $55 million Series C funding round in August 2023. The round was led by Freeman Group and includes investments from venture capital firms ACVC Partners and Amplo as well as strategic investments from Honda Motor, Goodyear Ventures, and Sungwoo Hitech. This financing brings the total amount raised by Helm.ai to $102M.
