Recently, Pony.ai in the Beijing Economic and Technological Development Area (BDA) held a press conference to announce the brand name of its self-driving transport truck – PonyTron. 

Pony.ai holds a press conference to announce the name of its new self-driving truck on March 31, 2021.

PonyTron is expected to achieve mass production in 2025.

Pony.ai began to make preparations in the field of autonomous trucks in 2018 and PonyTron Technology Co Ltd was registered in BDA two years later.

As a high-level autonomous driving demonstration zone, BDA has opened 322 kilometers of autonomous vehicle test roads, becoming the country's first fully open autonomous driving test zone.

PonyTron, the self-driving truck developed by Pony.ai. 

According to Zhang Ning, vice president of Pony.ai, BDA is a friendly zone for the entire driving industry. It is the first area to launch autonomous driving test roads in the entire district, and it gives preferential treatment to autonomous driving companies.

Meanwhile, BDA possesses a complete industrial chain, as well as upstream and downstream partners, including firms in the chip industry, which can contribute to the mass production of autonomous vehicles.

PonyTron is about 17 meters long. Based on Pony.ai's self-developed multi-sensor fusion technology and deep vision algorithm, it can achieve a long-distance and wide-angle sensing range.

The vehicle uses two lidars to realize object ranging and detection, and its two GNSS antennas can achieve centimeter-level precise positioning.

With six cameras and two millimeter-wave radars, the new truck can achieve long- and short-range object detection, support high-speed driving and execute assisted lane changes.

Pony.ai has developed a set of automatic driving software and hardware integrated systems for heavy trucks, which can realize the L4 automatic driving function on busy highways. 

It also combines topography and road conditions in the real-time planning of routes and intelligently operates vehicle accelerators, brakes and other control schemes to reduce fuel consumption.