"Yunqi Capital" Partners with Tsinghua University to Build More Energy-Efficient Autonomous Vehicles | Yunqi Capital Tech π

"Yunqi Tech π" shares updates from Yunqi Capital's portfolio companies, exploring how cutting-edge technology pushes the boundaries of real-world applications and tracking the present and future of tech commercialization. In this edition of "Yunqi Tech π," we bring you the latest from DeepRoute.ai.

➤➤➤ Under China's national "dual carbon" policy, how can autonomous vehicles become energy-saving champions? How can we improve the efficiency and safety of self-driving cars at intersections? Recently, DeepRoute.ai — an L4 autonomous driving company and Yunqi Capital angel-round investment — partnered with Tsinghua University's School of Vehicle and Mobility to conduct targeted research on the energy consumption and perception capabilities of autonomous vehicles. The findings will help DeepRoute.ai upgrade its mass-production strategy for self-driving cars, delivering more fuel-efficient and intelligently driven vehicles to consumers.

Autonomous vehicles that can avoid red lights across multiple intersections

Tsinghua University's research shows that urban intersections present complex traffic environments where vehicles engage in frequent interactive decision-making with numerous road users, constantly cycling through "decelerate, stop, accelerate" maneuvers. This pattern not only undermines economical driving and wastes energy, but also triggers traffic congestion and accidents. Statistics indicate that nearly 25% of traffic accidents in China occur at intersections, while in the U.S. that figure exceeds 36%.

Against this backdrop, DeepRoute.ai and Tsinghua University are jointly enhancing autonomous vehicles' perception and decision-planning capabilities through a vehicle-road-cloud integrated control architecture. This allows vehicles to pre-plan speed and route, avoiding red lights and traffic jams across multiple intersections while rapidly perceiving surrounding vehicles and pedestrians to navigate complex intersection scenarios with greater ease. Under the premise of safe, comfortable driving, the optimized autonomous vehicles achieved a 6.9% reduction in driving energy consumption compared to human-driven cars.

Autonomous vehicle driving through downtown streets

This research is one of several industry-academia integration projects between DeepRoute.ai and Tsinghua University. Their collaboration began in February 2021.

Li Keqiang, academician of the Chinese Academy of Engineering, Tsinghua University professor, and director of the State Key Laboratory of Automotive Safety and Energy, stated: "The automotive industry is a strategically important and pioneering pillar industry for the nation, currently undergoing disruptive technological innovation and industrial transformation. Autonomous vehicle research must be grounded in big data and large-scale scenarios, requiring us to actively explore integration with industry."

Zhou Guang, CEO of DeepRoute.ai, said: "DeepRoute.ai is honored to collaborate with Tsinghua University on industry-academia integration. Autonomous driving technology integrates expertise across vehicles, transportation, information, electronics, software, and other fields. Tsinghua University not only possesses deep professional foundations but also strong cross-disciplinary collaborative innovation capabilities, approaching real industrial needs to conduct cross-domain academic research and technical cooperation. These qualities provide ideal conditions for industry-academia collaboration and maximize progress for the sector."

By 2024, vehicles equipped with DeepRoute.ai's L4 autonomous driving system are expected to hit the market. DeepRoute.ai's R&D team will continue combining forces with Tsinghua University's strongest "vehicle brain + cloud brain" to jointly optimize the L4 mass-production strategy, building more energy-efficient, efficient, and intelligent autonomous driving products that move from laboratory to road as quickly as possible, improving traffic efficiency and safety.

Intelligent driving is one of Yunqi Capital's continued focus areas. Yunqi hopes to advance intelligent driving development alongside its portfolio companies, creating possibilities for more efficient, safe, and convenient urban transportation. Yunqi invested in DeepRoute.ai's angel round in 2019 and has supported the company ever since. Beyond DeepRoute.ai, Yunqi has also invested in multiple upstream and downstream startups including Neolix, JueFX Technology, and ZhuiShi Technology.