Shanghai (Gasgoo)- On July 15, BMW Group China announced a new partnership with Chinese autonomous driving and ADAS technology firm Momenta to jointly develop an intelligent driving assistance system tailored specifically for the Chinese market.
Leveraging Momenta's cutting-edge large-model AI architecture, the two companies aim to create a locally optimized solution that delivers point-to-point assisted driving across a full range of scenarios, from highways to complex urban environments. The system will be rolled out across multiple BMW models, including the forthcoming China-made Neue Klasse lineup.
Mr. Sean Green, President & CEO, BMW Group Region China, emphasized the strategic alignment of the collaboration: "BMW's unique philosophy and intelligent driving approach are increasingly merging with China's world-class digital capabilities. Together with Momenta, we're building a new benchmark in co-creation and shared success, pushing forward our 'In China, For China, At China Speed' innovation strategy."
Momenta CEO Mr. Cao Xudong added, "We are honored to collaborate with BMW, a global leader synonymous with driving pleasure and technological advancement. By combining BMW's hallmark German engineering with our AI-driven intelligent driving expertise, we aim to deliver a solution that is safe, convenient, and truly future-ready."
China plays a pivotal role in BMW Group's global innovation roadmap. The company continues to pursue an open technology strategy in the country, maintaining its core strengths while embracing local innovation. Through deep collaborations with Chinese partners like Momenta, BMW is accelerating the development of intelligent mobility solutions that cater specifically to local customer expectations.
Momenta said it has led the industry in deploying end-to-end intelligent driving assistance systems. Its Flywheel Big Model architecture integrates perception and planning into a unified AI model and features a novel training mechanism combining long-term and short-term memory, mimicking human intuition and logic. This design significantly reduces training costs while improving system robustness and enabling the model to address complex, long-tail driving scenarios with enhanced reliability and stability.
