Beijing (Gasgoo)- On April 23, L4 autonomous driving company Pony.ai unveiled its seventh-generation autonomous driving hardware and software system at the AUTO SHANGHAI 2025. Alongside the system, three new mass-production models of the seventh-generation Robotaxi family were introduced, marking the beginning of their production journey.
Pony.ai’s seventh-generation Robotaxi models come equipped with fully automotive-grade components, with the overall cost of the autonomous driving kit reduced by 70% compared to previous generations, said the company. Key features include a platform-based design and the world’s first all-scenario L4 autonomous driving system based on automotive-grade chips, capable of handling full-scenario, driverless operations.
Pony.ai's L4 Robotaxi fleet, built on its PonyWorld model technology, has already completed 500,000 hours of full-scenario, all-weather, driverless operation, with a safety rate 10 times higher than human drivers, the company disclosed. Co-founder and CEO, Peng Jun, emphasized that 2025 marks the year of mass production for Robotaxis and the realization of the "Kunlun Plan" for Pony.ai. The three new Robotaxi models are developed in collaboration with Toyota, BAIC Group, and GAC Group, respectively.
The seventh-generation Robotaxi models from Pony.ai are equipped with six types of mass-produced sensors, including 9 LiDAR sensors, 14 cameras, 4 millimeter-wave radars, 4 microphones, 2 water sensors, and 1 collision sensor. This configuration enables 360° blind-spot-free detection around the vehicle and environmental monitoring within a 650-meter range. The sensor system is paired with Pony.ai's self-developed sensor cleaning solution, which enhances the vehicle's ability to detect and handle long-tail scenarios.
This setup ensures that the Robotaxi can navigate complex road conditions in real-time, meeting the full-scenario driverless operation and safety requirements for urban areas, highways, ring roads, and extreme weather conditions such as rain, snow, and fog, as well as handling complex situations and giving way to emergency vehicles.
