Journey 6P Intelligent Driving Solution Selected by JD Logistics

Horizon Robotics Selects Journey 6P for JD Logistics

Beijing Horizon Information Technology Co Ltd, also known as Horizon Robotics, has announced that its Journey 6P intelligent driving solution was selected for an autonomous logistics vehicle project operated by JD Logistics Inc. The system will provide automotive-grade intelligent driving computing for the Plus version of JD Logistics’ sixth-generation L4 “Dulang” autonomous delivery vehicle. The selection expands the use of Horizon Robotics’ computing technology in autonomous logistics and positions Journey 6P as the computing platform for perception and decision-making functions on the vehicle. The project is focused on autonomous delivery operations that require intelligent driving capabilities across complex logistics environments.

Journey 6P Delivers 560 TOPS of Computing Power

A single Journey 6P chip provides 560 TOPS of computing power and incorporates Horizon Robotics’ BPU Nash architecture. The chip supports real-time inference for Transformer- and BEV-based models, allowing the system to process multiple sources of information for intelligent driving applications. These capabilities are designed to support multimodal perception, understanding of complex environments, and advanced decision-making. By combining substantial computing capacity with model support for perception and decision functions, Journey 6P provides the computing foundation required for the autonomous driving workloads planned for JD Logistics’ sixth-generation “Dulang” vehicle Plus.

Autonomous Delivery Vehicle Targets Complex Road Conditions

JD Logistics’ sixth-generation “Dulang” autonomous delivery vehicle Plus will use Journey 6P to deploy perception and decision-making models alongside multimodal sensor fusion. The configuration is intended to address operating conditions that can challenge autonomous logistics systems, including mixed pedestrian and vehicle traffic, narrow alleys, and frequent interactions with dynamic obstacles. These environments require the vehicle to interpret changing surroundings and make driving decisions in real time. The combination of Journey 6P computing, autonomous driving models, and multimodal sensing is therefore central to the vehicle’s ability to support L4 autonomous delivery operations across demanding logistics scenarios.

Deployment Could Reach One Million Autonomous Vehicles

Horizon Robotics said the number of autonomous logistics vehicles deployed through the partnership is expected to reach one million over the next three to five years. If achieved, that deployment would represent a substantial expansion of autonomous vehicle use within logistics operations and increase the practical scale of Journey 6P-based intelligent driving systems. The planned volume also indicates that the project is intended to move beyond limited pilot deployments toward broader operational use. The stated three-to-five-year timeframe provides the expected window for scaling the partnership’s autonomous logistics vehicle deployment.

Journey 6 Series Expands Across Logistics Applications

Horizon Robotics has already deployed Journey 6 series solutions in both line-haul transportation and last-mile delivery applications. The company’s technology is therefore being applied across different stages of logistics transportation rather than being limited to a single vehicle or operating environment. The broader deployment also includes other autonomous driving developments based on Journey 6 chips. These applications demonstrate how the product family is being positioned for commercial vehicle and logistics use cases where computing performance supports perception, decision-making, and autonomous operation. The JD Logistics project adds another major application to this expanding deployment base.

Journey 6M Platform Enters Mass Production

Inceptio Technology Shanghai Co Ltd has developed the Taurus computing platform around the Journey 6M chip, with the platform entering mass production and beginning deliveries. The development provides another example of Journey 6 technology moving into commercial logistics applications. In addition, KargoBot Beijing Technology Co Ltd and Go Further.AI have developed L4 autonomous freight transportation and logistics autonomous driving solutions based on Journey 6P. Together, these deployments show that Journey 6 chips are being incorporated into multiple autonomous transportation programs spanning freight and logistics operations, with different companies applying the computing platforms to their respective autonomous driving systems.

Industry Impact & Outlook

The selection of Journey 6P for JD Logistics’ L4 delivery vehicle could strengthen the role of high-performance automotive computing in commercial autonomous logistics, particularly as operations expand into complex urban and last-mile environments. The planned scale also raises the importance of reliable perception, sensor fusion, and real-time decision-making for large autonomous fleets. For Horizon Robotics, broader adoption across delivery and freight applications could deepen its position in logistics-focused intelligent driving computing, while JD Logistics gains a dedicated computing platform for its next-generation autonomous delivery vehicle. The partnership’s next phase will depend on the progression from the stated deployment plans toward broader vehicle implementation over the next three to five years.

Frequently Asked Questions

What role will Journey 6P play in JD Logistics’ autonomous vehicles?
Journey 6P will provide automotive-grade computing for the Plus version of JD Logistics’ sixth-generation L4 “Dulang” autonomous delivery vehicle, supporting perception and decision-making models. A single chip delivers 560 TOPS of computing power and uses Horizon Robotics’ BPU Nash architecture. The platform supports real-time inference for Transformer- and BEV-based models, helping process multimodal perception and complex environments. JD Logistics will combine these capabilities with multimodal sensor fusion to address mixed traffic, narrow alleys, and dynamic obstacles during autonomous logistics operations.