Autonomous driving technology is rapidly advancing beyond passenger cars and into the heavy trucking industry, where safety, efficiency, and operational cost savings are critical priorities for construction fleets. The partnership between Plus, a leading self-driving truck technology company, and NVIDIA represents a significant milestone in bringing level 4 autonomy to Class 7 and Class 8 heavy trucks. For construction professionals managing fleets of dump trucks, concrete mixers, and heavy haulers, understanding how this technology works and what it means for the industry is essential. Just as infrastructure systems like a How Long Does a Septic System Last a require careful engineering and long-term planning, autonomous truck systems demand rigorous design and testing before they can be deployed safely on public roads.
Understanding the Plus and NVIDIA Autonomous Driving Partnership
Plus, founded in 2016, has established itself as a specialist in self-driving technology for large-scale autonomous transport. The company’s collaboration with NVIDIA centers on integrating the NVIDIA DRIVE Orin system-on-a-chip (SoC) into Plus’ next-generation autonomous driving system. This partnership combines Plus’ expertise in autonomous driving software with NVIDIA’s industry-leading computing hardware designed specifically for AI-powered vehicle applications.
Key Milestones and Achievements
- Plus has received more than 10,000 preorders for its autonomous driving system from fleet operators worldwide
- The company raised $200 million in new funding in February 2021, led by Guotai Junan International, CPE, and Wanxiang International Investment
- Mass production of the autonomous driving system began in 2021
- A former Navistar executive joined Plus as chief platform officer to support global deployment
- Chuck Joseph joined from Amazon’s Global Transportation Technology Group
- Collaborations established with Amazon AWS, Blackberry QNX, and Ouster
The substantial preorder volume indicates strong market demand for autonomous trucking solutions. Construction fleets operating heavy trucks across long distances stand to benefit significantly from the safety and efficiency improvements these systems promise.
How the Plus Autonomous Driving System Works
The Plus autonomous driving system is purpose-built for heavy trucks, which present unique challenges compared to passenger vehicles. A fully loaded Class 8 truck can weigh up to 80,000 pounds, requiring significantly more distance to stop and maneuver. The system addresses these challenges through a sophisticated sensor fusion approach.
Sensor Suite and Perception
The system employs a three-pronged sensing architecture:
- Lidar: Provides precise distance measurements and creates a 3D map of the truck’s surroundings, enabling the system to detect objects at long range even in low-light conditions
- Radar: Offers robust performance in adverse weather conditions such as rain, fog, and snow, where optical sensors may struggle
- Cameras: Deliver high-resolution visual data for identifying lane markings, traffic signs, signals, and other critical roadway features
Together, these sensors provide a 360-degree view of the truck’s environment. The data gathered feeds into the system’s perception algorithms, which identify objects, classify them, and predict their movement trajectories.
The Role of NVIDIA DRIVE Orin
The NVIDIA DRIVE Orin SoC is the computational backbone of the Plus system. Capable of delivering 254 trillion operations per second (TOPS), the processor handles the enormous computational demands of real-time autonomous driving. As Hao Zheng, Plus CTO and cofounder, explained, enormous computing power is needed to process the trillions of operations that the autonomous driving system runs every fraction of a second.
Key technical specifications of the NVIDIA DRIVE Orin include:
| Specification | Detail |
|---|---|
| Computing Performance | 254 trillion operations per second (TOPS) |
| Safety Certification | ISO 26262 Functional Safety ASIL-D (system level) |
| AI Capability | Deep neural network support for real-time decision making |
| Application | Autonomous driving system-on-a-chip for heavy trucks |
| Design Collaboration | Custom design developed with NVIDIA engineering team |
The ASIL-D safety certification is the highest level of automotive safety integrity defined by the ISO 26262 standard. This certification ensures that the system can achieve fail-operational performance, meaning the truck can continue to operate safely even if a component fails, which is critical for on-road safety at highway speeds.
Safety, Efficiency, and the Business Case for Autonomous Trucks
The primary drivers behind autonomous truck technology are improved safety and operational efficiency. For construction companies managing heavy truck fleets, these factors translate directly into reduced costs, fewer accidents, and more reliable project timelines.
Safety Improvements
Heavy trucks have inherent safety challenges due to their size, weight, and stopping distance requirements. The Plus autonomous system addresses these through several mechanisms:
- 360-degree situational awareness: The sensor suite eliminates blind spots that human drivers cannot overcome, providing continuous monitoring of all areas around the truck
- Predictive object tracking: The system identifies and tracks nearby objects, predicting their movement to anticipate potential hazards before they become critical
- Fail-operational architecture: Built on the ASIL-D certified NVIDIA Orin platform, the system can maintain safe operation even when individual components experience faults
- Over-the-air updates: The system can expand its feature set and operating design domain over time through software updates, allowing continuous safety improvements without requiring hardware replacements
Rishi Dhall, vice president of autonomous vehicles at NVIDIA, stated that Plus and its automated trucks are delivering true social benefits today through improved safety and efficiency. For construction fleets operating in mixed traffic environments, these safety features can reduce the risk of collisions and lower insurance costs over time.
Operational Efficiency Gains
Autonomous driving systems offer construction fleet operators several efficiency advantages:
- Optimized fuel consumption through smoother acceleration, braking, and gear selection
- Reduced driver fatigue on long-haul routes, enabling longer productive operating windows
- Consistent driving behavior that reduces wear and tear on tires, brakes, and drivetrain components
- Data-driven route optimization that avoids traffic congestion and construction delays
- Predictive maintenance scheduling based on real-time vehicle performance data
For construction projects where material delivery timing is critical, these efficiency gains can mean the difference between a project staying on schedule and costly delays. The ability to predict arrival times more accurately helps project managers coordinate concrete deliveries, aggregate shipments, and equipment mobilization more effectively.
Global Deployment Strategy and What It Means for Construction Fleets
Plus is pursuing an aggressive global rollout strategy for its autonomous driving system. The $200 million funding round supports the development of a sales and support network to help fleets integrate the Plus automated trucking system into their daily operations. The company is scaling deployments in the United States and China while planning expansion into Europe and other parts of Asia.
Deployment Timeline and Availability
The Plus system is expected to be commercially available in 2022 across multiple markets. The company began mass production of its autonomous driving system in 2021, positioning itself to fulfill the more than 10,000 preorders already placed. This timeline places Plus among the first autonomous truck technology providers to reach commercial scale.
| Market | Expected Availability | Focus Areas |
|---|---|---|
| United States | 2022 | Long-haul freight, interstate corridors |
| China | 2022 | Logistics hubs, port operations |
| Europe | Planned expansion | Cross-border freight, highway networks |
| Other Asia | Planned expansion | Emerging logistics markets |
Integration Challenges for Construction Operations
While autonomous technology holds great promise, construction fleets face unique integration challenges that differ from long-haul freight operations. Construction trucks often operate on uneven terrain, at job sites with unpredictable layouts, and in close proximity to workers and other heavy equipment. The Plus system is initially focused on highway driving scenarios where conditions are more predictable.
However, the over-the-air update capability means the system can gradually expand its operating design domain to include more complex environments. Construction fleet operators should consider several factors when evaluating autonomous technology:
- Route suitability: Identify which routes in your fleet operations are primarily highway-based and could benefit from autonomous features today
- Infrastructure compatibility: Ensure your yard and loading facilities can accommodate autonomous trucks that may arrive without a human driver
- Driver transition planning: Develop training programs to help drivers transition from active operation to supervisory roles as autonomy levels increase
- Maintenance capabilities: Build in-house capability to maintain and calibrate sensor systems including lidar, radar, and cameras
- Telematics integration: Plan for integration with existing fleet management and telematics systems to maximize data value
As construction professionals evaluate these emerging technologies, it is helpful to understand how other engineered systems achieve reliability through layered design principles. The same approach used in a Dry Stacked Interlocking Masonry System, where individual components work together to create a stable, resilient structure, mirrors the sensor fusion approach in autonomous driving where lidar, radar, and cameras combine to create a reliable perception system. Similarly, the rigorous classification and testing methods applied in the Geomechanics Classification System of Rocks for Engineering Purposes share common ground with the safety validation processes required for autonomous driving systems. And just as a Canal Irrigation System Design must account for variable flow conditions and maintain consistent performance across changing environments, autonomous truck systems must adapt to diverse road conditions while maintaining safe and predictable operation.
Strategic Partnerships Supporting Deployment
Plus has built a robust ecosystem of technology partners to support its deployment strategy. The collaboration with Amazon AWS provides cloud infrastructure for data storage, processing, and over-the-air update delivery. The partnership with Blackberry QNX brings a certified real-time operating system for safety-critical functions. The collaboration with Ouster supplies high-performance lidar sensors for the perception stack.
This multi-partner approach ensures that each component of the autonomous system benefits from best-in-class technology. For construction fleet operators, the depth of these partnerships provides confidence that the Plus system is built on proven, enterprise-grade technology platforms.
Conclusion
The partnership between Plus and NVIDIA marks a significant step forward in bringing autonomous driving technology to heavy trucks. With more than 10,000 preorders, $200 million in funding, and a clear roadmap for commercial deployment starting in 2022, the technology is moving from development to real-world application. For construction professionals managing heavy truck fleets, the safety and efficiency improvements offered by autonomous systems promise long-term operational benefits. While full autonomy in complex construction environments remains a future goal, the highway-focused systems being deployed today can already deliver measurable value. Construction companies that begin preparing for this technology now will be best positioned to capture its benefits as it becomes more widely available.