SANY Group has announced that its fourth-generation autonomous heavy-duty truck, co-developed with autonomous driving firm Pony.ai, is nearing readiness for mass production, with the first batch scheduled for commercial operation next year. The partnership aims to accelerate the digitalization and low-carbon transformation of the logistics sector, particularly in China.
The new electric model is equipped with a battery pack exceeding $400$ kWh. According to projections, each vehicle is expected to reduce annual carbon emissions by approximately 60 tons, aligning with industry decarbonization goals.
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A key focus of the vehicle’s design is safety and reliability. The truck utilizes SANY’s fully redundant drive-by-wire chassis, which provides dual-backup architecture across six core systems: steering, braking, communication, power supply, computing, and sensing. The vehicle has also successfully undergone rigorous electromagnetic compatibility (EMC) and extreme-temperature testing.
Zhou Wanchun, Vice President of SANY Group, emphasized the importance of the hardware foundation for large-scale deployment. “Mass production of the fourth-generation autonomous truck marks another milestone in SANY’s Digitalization and decarbonization strategy. Our industry-leading fully redundant drive-by-wire chassis provides a reliable hardware foundation for autonomous driving,” Zhou said.
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For operational efficiency, the companies have developed a “1+4” autonomous platooning solution, which involves one manned lead truck followed by four unmanned electric vehicles. Based on pilot program estimations, this platooning model can achieve a 29% reduction in per-kilometer freight costs and increase operating profit by 195%. This solution is designed to be replicated across smart-port operations and other logistics scenarios.
The strategic collaboration, which began in 2022, combines SANY’s vehicle development and chassis capabilities with Pony.ai’s autonomous driving software, transitioning the partners’ joint efforts from prototypes to scalable production under a “Vehicle + Technology + Scenario” model.