Minus Zero, a Bengaluru-based startup, has unveiled what it claims to be India’s first end-to-end AI-based autopilot system designed to navigate dense urban traffic. The startup focuses on an AI-first approach to autonomous driving and end-to-end driving models that replace traditional modular AV architecture with a single foundational model. 

Developed and tested in Bengaluru, the system operates without reliance on traditional rule-based models or high-definition maps. It uses foundational AI models to self-learn from raw, unlabelled data.

The autopilot handles typical Indian traffic challenges, including narrow roads, unpredictable obstacles and the absence of lane markings. “Our vision-based system can gracefully handle unique obstacles like animals, push-carts, small two-wheelers, etc., and their unpredictable behaviours,” the company announced. 

The system is categorised under the ‘Hands Off & Eyes On’ model, requiring a safety driver at all times. Minus Zero’s approach marks a shift from traditional Advanced Driver Assistance Systems (ADAS) technologies. Unlike systems in developed markets such as Tesla’s FSD or GM’s Super Cruise, this solution is built to manage the unstructured conditions typical of Indian roads. 

The company stated that it understood this unique pain point and the technology shift required for building advanced autopilot systems for all the major emerging countries, starting with India.

Key innovations include the use of self-supervised foundational AI models, a vision-first hardware stack, and the ability to operate without HD maps. The system’s adaptability allows it to generalise to unseen scenarios and geographies, potentially making it scalable across other emerging markets.

The company is currently collaborating with large original equipment manufacturers (OEMs) and aims to achieve production readiness within two years. It previously showcased India’s first fully driverless in-campus vehicle and now advances its mission with this full-stack platform.

Minus Zero highlighted its full-stack AI capabilities, including generative AI and vision-language models (VLMs) for simulation and data processing. The system continues to learn and evolve with daily input, enhancing its real-world performance.

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