Autonomous trucks

Autonomous trucks are safe, scalable, and ready for the road

Autonomous driving in freight transportation requires more than individual components. It requires the interaction of sensors, computing power, software, vehicle architecture, and safety concepts. We develop the technologies the technologies and system expertise needed to make this possible.

Discover how autonomous commercial vehicles perceive their environment, process information, and execute safe driving maneuvers, and how individual technology building blocks become an integrated system.

Autonomous driving for commercial vehicles can advance freight transportation in several areas. The actual impact depends on the specific use case, technical system design, and operating conditions. Five aspects are particularly important.

These benefits do not result from a single function. They require an overall system that understands its environment, assesses situations, acts safely, and monitors its own system status.

An autonomous truck must reliably perceive its environment, process large volumes of data within a short time, and derive a safe vehicle response. We view these functions as one integrated system task.

Cameras, radar, and LiDAR provide data on objects, road geometry, distances, and relevant traffic situations. The sensor information is combined to create the most consistent possible model of the environment.

The calculated action is executed through the driving function. This includes steering, acceleration, braking, and other functions required for the safe movement of the commercial vehicle.

Rain, fog, nighttime conditions, and glare place particularly demanding requirements on environmental perception. A robust system design therefore considers different sensor principles, their respective performance, and their integration into the vehicle architecture.

The positioning of sensors on the truck is also critical. Sensors must cover the relevant area, be mechanically and thermally integrated into the vehicle, and remain accessible for diagnostics, maintenance, and replacement when required.

Learn more about radar technology and camera technology.

Autonomous trucks generate and process large volumes of sensor data. Central computing resources must combine this information in real time, assess situations, and derive suitable driving maneuvers.

High-performance computers perform key tasks within the automated driving system. They provide the required computing power and enable multiple functions to be processed in parallel.

Computing power alone is not enough. The hardware must be designed for robust use in a commercial vehicle. This includes suitable thermal management, a stable power supply, defined communication paths, and an architecture that can be integrated into the vehicle’s electrical/electronic architecture.

Depending on the system concept, computing units can process tasks such as environmental perception, situation assessment, planning, and vehicle control separately or within coordinated functional chains. Parallel computing architectures support the monitoring and safeguarding of safety-critical functions.

• Data acquisition: sensors provide information about the environment.
• Processing: computing units combine and prepare the data.
• Situation assessment: the system identifies relevant objects, movements, and traffic situations.
• Decision: potential driving maneuvers are assessed and prioritized.
• Vehicle response: the driving functions execute the decision accordingly.

Learn more about high-performance computers for autonomous driving.

For autonomous commercial vehicles, safety must be embedded in the system architecture from the outset. We call this “Safety by design.” It applies to sensors, computing power, software, communication paths, and vehicle functions. The goal is a system design that detects faults, assesses their impact, and triggers an appropriate response.

A safety-oriented system continuously monitors its own status. If it detects a deviation in a sensor, computing unit, or communication path, it must assess the situation and initiate the appropriate response.

Depending on the system architecture, redundant functions may support limited continued operation. If safe continued operation is not possible, the system initiates a defined maneuver designed to minimize risk. It considers the available vehicle functions, the current driving situation, and the environment to bring the vehicle to the safest possible state.

Safety from the start does not end at an individual control unit. Perception, situation assessment, planning, steering, braking, power supply, and communication must be considered as one connected functional chain.

A fail-safe system architecture can use different paths for the regular driving function and its safety backup. The key is to clearly define each function, assess it independently, and validate it under realistic conditions.

We actively use data-driven development to systematically increase the robustness of autonomous systems. We structure and analyze real-world driving and environmental data, identify critical and rare scenarios, and convert them into reproducible test cases. This allows us to systematically assess relevant situations and identify development needs early.

We use simulations to examine large numbers of complex and rare situations and efficiently compare variants. Combined with real-world data, scenario search, simulation, verification, and testing, this creates a reliable foundation for systematically advancing environmental perception, planning, and vehicle control. This data-driven approach helps make system performance traceable and improve robustness step by step.

Autonomous commercial vehicles require a coordinated overall system. We combine electronics, software, safety, and production expertise to develop robust, integrable solutions for commercial-vehicle applications from individual technology building blocks.

We consider the entire path from environmental perception to a safe driving maneuver, as well as the factors that are critical for industrial implementation: validation, diagnostics, serviceability, scalability, and lifecycle management.

Autonomous driving for commercial vehicles raises different questions for vehicle manufacturers, development partners, and fleet operators. However, the technical foundation is the same: an integrated system that is safe, robust, and suitable for the relevant use case.

For vehicle manufacturers and development partners, the objective is to integrate autonomous driving functions into existing or new vehicle platforms. This requires alignment between the system architecture, sensors, computing power, actuators, and safety concept.

We support you in combining technology building blocks into an overall system and bringing together the requirements of development, validation, and industrialization.

This includes:

• Development and integration of hardware and software building blocks
• Scalable system architectures for different vehicle platforms
• Alignment of sensors, computing power, actuators, and electrical/electronic architecture
• Safety concepts, redundancy, and defined fallback strategies
• Validation and verification in simulation, laboratory, and vehicle environments
• Preparation for industrial processes and series-production requirements
• Collaboration across the entire development lifecycle

For fleet operators and logistics companies, the central question is where autonomous commercial vehicles can make a tangible contribution. Use cases with recurring routes, clearly defined operating processes, and suitable infrastructure are particularly relevant.

Autonomous driving for commercial vehicles can open up new possibilities for transportation planning and organization. This requires a system designed for safety, high technical reliability, and suitable integration into dispatching, maintenance, service, and operational support.

Questions to evaluate together include:

• Which routes and operating situations are suitable?
• What requirements apply to the vehicle, infrastructure, and control center?
• How should diagnostics, maintenance, and repairs be organized?
• What interfaces are needed for dispatching and fleet management?
• How can a phased rollout be implemented using clearly defined use cases?

We combine international expertise in the automotive and commercial-vehicle industries with experience in vehicle electronics, hardware, software, and systems development. We develop solutions for automated and autonomous driving while addressing the requirements of safety-critical systems and industrial implementation.

Autonomous commercial vehicles require the coordinated interaction of many technologies. We combine sensors, computing platforms, electrical/electronic architectures, software integration, and vehicle functions into a system-level approach that connects development and operations.

Multiple high-performance computers (HPCs) process sensor data in real time. The system identifies situations, assesses potential risks, and calculates suitable driving maneuvers.

A solution for autonomous commercial vehicles must do more than work in a demonstrator. It must integrate into different vehicle platforms and industrial processes while addressing diagnostics, maintenance, ongoing development, and lifecycle requirements.