In most cases, it is actually sufficient to look at the ECU’s inputs and outputs to functionally test a component (Figure 1). However, this becomes difficult when state machines are used in the ECU. Their current states can only be derived indirectly by their effects at the ECU’s outputs. In the case of sensors whose values are not transmitted over the network system, it is also very difficult for the test engineer to localize errors to the software interface. From outside the ECU, it is not clear exactly where the sensor value was incorrectly processed.

Different methods that offer access to internal ECU data are used, depending on the phase of ECU development. In early phases, for example, internal ECU values are often output in so-called “reserved development messages” (Figure 1). For the functional developer at a supplier, this is an effective and quick method that precisely targets a specific objective. However, these supplemental messages must be removed for later development phases, especially for system integration and series production. They induce additional bus load, and in the worst case they might even collide with messages of other system components. Another way to access internal values is through diagnostics (Figure 1). Some information is available directly via diagnostics, e.g. diagnostics offers access to fault memory. Special diagnostic services are also provided to read the required values from memory. The advantage here is that a standardized access method is used. The only precondition is full integration of the diagnostic driver; this is generally provided in today’s ECUs. The disadvantage of this method is that a lot of unnecessary diagnostic protocol information is transmitted along with the actual measured values, and this adds load to the network system interface. A data flow analysis of many values is not possible, especially since the measured values do not contain time stamp information.

XCP For Test Access

If network interface load needs to be kept low, an alternative is to use a calibration protocol. Originally, such protocols were developed for the ECU calibrator. They let calibrators modify parameters or characteristic maps in the ECU to optimize their algorithms. With the XCP protocol standardized by ASAM, the user can read individual values directly from the ECU as needed. The protocol can also periodically supply a defined set of measured values from the ECU via so-called Data Acquisition (DAQ) lists. The XCP protocol was defined for efficient provision of data over the network medium. As an example, after configuration the DAQ lists can be transmitted in response to a single identifier from the test system. In addition, measurement times of the DAQ lists can be synchronized to internal ECU processes. Automated test systems place similar requirements on the system. Use of the XCP protocol makes it possible to integrate internal values in test sequences without excessive loading of the ECU or the network system used. Another reason that a widely used standard like XCP is ideal is that it is very easy to configure in the tool chain. All necessary information is already in the A2L file such as internal program memory locations with their names and communication parameters. Depending on the development environment, the A2L file is either automatically generated, or it may need to be generated in a separate step from the linker-map information. In the test tool, the user only has to configure this file once for each ECU used in the test. In a second step, the user selects the symbols needed for the test sequences from the A2L file.

CANoe Option .AMD/XCP

Option .AMD/XCP supplements the CANoe test tool from Vector with the convenient option of reading and writing internal ECU values. Besides supporting the XCP standard, it also supports the previous protocol CCP. Once the A2L file has been configured and the necessary values selected, CANoe automatically acquires them and maps them as system variables. The user can then use these variables in any of the testing tasks. Besides offering access to ECU inputs and outputs, they also provide an in-depth look into the ECU’s memory (Figure 2).

In simple analysis tasks, users can display the data in the Trace or Graphic Window and use panels to evaluate the results. For more complex test sequences, CANoe’s Test Feature Set offers extensive options for creating test cases and automatically evaluating them. For example, this enables checking of the Network Management state machine for correct functionality. The necessary stimulation is performed in the CANoe rest-of-bus simulation, and the ECU’s reaction is not just measurable on the network; it is directly measurable in the ECU over XCP. The effort required to execute test cases is also significantly reduced, e.g. for test cases that require sensors. The test system writes the sensor values directly to memory cells in the ECU over XCP. This eliminates the need to connect and control original sensors at the ECU inputs – a demanding task. The ECU is notified that the sensor and associated hardware driver have measured the values correctly. The same approach can be used in the other direction. Here it is assumed that the output stage and actuator have been tested and accepted. In this case, the test system measures the value that the application prescribes to the driver stage over XCP.

Access With Large Quantities Of Data

If large quantities of data need to be exchanged between the test system and the ECU in a test case, or if especially quick processes need to be monitored, an XCP connection over a CAN network is no longer effective. In such cases, direct access to the ECU’s debug interfaces is recommended. This could be implemented via a NEXUS or JTAG interface, for example. These protocols directly access the ECU memory − partly without load on the microcontroller. Taking this approach, the user can quickly read out very large quantities of data from the system without loading the network and the ECU.

Vector VX hardware, for example, offers direct access to an ECU’s NEXUS or JTAG interface (Figure 2). Since this hardware communicates with the test system via XCP-on-Ethernet, integration in CANoe is as easy as integration for XCP access over CAN. Combining VX hardware with the CANoe test system further improves test system performance, without any negative effects on the communication medium. (MT)

NB: Oliver Falkner is group leader at Vector in product management of the Networks and Distributed Systems product line. Views expressed are personal.

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European ride-hailing platform Bolt has selected the NVIDIA Alpamayo Stack autonomous driving software to operate its vehicle fleet in Europe, starting with Lucid automobiles.

The deployment commences in Madrid in 2027, with subsequent deployment planned in Germany and France. The initiative supports the integration of at least 25,000 Level 4-ready Lucid vehicles equipped with NVIDIA Hyperion compute and sensor architecture. The program contributes to Bolt's objective of deploying 100,000 autonomous vehicles across Europe and the UNECE region by 2035. The system integrates reasoning artificial intelligence with perception and planning modules alongside NVIDIA Halos safety controls.

Jevgeni Kabanov, President and Head of Autonomous Driving, Bolt, said, “Autonomous driving will change how people move around cities, and Europe should play a major role in how that future is built. Our ambition isn't to bring autonomous driving to just a handful of cities. We want to make autonomous ride-hailing available at scale across Europe, with 100,000 vehicles on our platform by 2035. We're bringing together some of the best technologies in the world to make that possible. Following our first autonomous mobility launch in Luxembourg, our next step with NVIDIA and Lucid is to begin a programme in Madrid in 2027. The Region of Madrid is pioneering a structured framework for commercial autonomous mobility in coordination with national authorities. Germany will also be a priority for what comes next, with cities already setting out clear ambitions for autonomous mobility.”

Rishi Dhall, Vice-President of Automotive, NVIDIA, said, “Robotaxis will scale when every vehicle is built on a common, safety-engineered foundation. NVIDIA Hyperion standardises the compute and sensor architecture across vehicle platforms, while NVIDIA Alpamayo Stack and Halos provide the driving intelligence and safety foundation. Bolt’s European platform, operational experience and work with cities and regulators make it a strong partner to bring autonomous ride-hailing to market at scale in Europe.”

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French tier 1 supplier Valeo has announced plans to develop and industrialise high-performance compute platforms utilising the NVIDIA Hyperion reference architecture and NVIDIA Halos safety system.

The initiative combines Valeo's vehicle integration capabilities with centralised computing architectures to support software-defined mobility systems. The platform utilises the NVIDIA DRIVE AGX Thor architecture to deliver processing performance and redundancy for Level 4 autonomous driving, commercial trucking and robotaxi applications. The development framework enables automakers to integrate features and deploy autonomous technologies across vehicle models.

Marc Vrecko, Chief Executive Officer, Valeo Brain Division, said, "Our work with NVIDIA marks a significant milestone in our mission to make autonomous driving a safe, scalable reality. By seamlessly integrating NVIDIA’s advanced compute power into our next-generation platforms, we are delivering the flexible, centralised intelligence vehicle manufacturers require to redefine the driving experience and meet the evolving demands of tomorrow’s intelligent vehicles."

Rishi Dhall, Vice-President of Automotive, NVIDIA, said, "Valeo’s expertise in high-performance computing, vehicle integration and automotive-scale industrialisation will help automakers adopt NVIDIA Hyperion and NVIDIA Halos at production scale. Together, NVIDIA and Valeo are providing the AI performance, functional safety and scalability needed to accelerate the development of Level 4 autonomous vehicles and robotaxis."

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HCLTech has introduced an artificial intelligence (AI) verification and validation platform utilising NVIDIA simulation tools, agentic systems and open models.

The offering targets vehicle manufacturers and tier-1 suppliers to automate software validation workflows and accelerate release cycles. Built on a simulation-first operating model, the platform connects requirements, test creation, execution, analysis and compliance reporting.

The system integrates HCLTech's engineering expertise and validation model with NVIDIA Omniverse, Cosmos, Alpamayo, NuRec and Isaac Sim technologies to generate scenarios in virtual environments, reducing reliance on physical testing.

Additionally, the platform utilises the NVIDIA Agent Toolkit to orchestrate AI agents powered by Nemotron open models across the validation lifecycle.

Pankaj Tagra, Chief Growth Officer and Global Head of Mobility, HCLTech, said, “Automotive software is evolving faster than traditional validation processes were designed to handle. Frequent software updates, increasingly complex vehicle systems and the need to demonstrate compliance across changing configurations can make validation slow, fragmented and difficult to scale. Powered by NVIDIA, HCLTech’s V&V for Auto is designed to help organisations shift from periodic, labor-intensive testing to continuous, intelligent validation, using simulation and AI to make software release decisions with greater speed and confidence.”

Dr. Sebastian Scheurle, EMEA Industry Lead of Automotive Enterprise, NVIDIA, said, “Validation now sets the pace for software-defined vehicles. With NVIDIA Omniverse, Cosmos and Nemotron at its core, this solution leverages world-class simulation and AI capabilities to support automakers in their journey towards moving more testing into simulation, covering rare and safety-critical scenarios earlier and releasing software with greater confidence.”

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HARMAN has received recognition from the AutoTech Breakthrough Awards, marking the fourth consecutive year the company has been honoured by the market intelligence organisation. The Ready Aware platform received the Driver Safety Solution designation for 2026.

Ready Aware operates as a software-defined vehicle-to-network solution that integrates infrastructure feeds, vehicle telemetry, cloud analytics and digital twin data to provide contextual in-vehicle warnings.

The system processes information regarding road conditions, weather, traffic hazards and signal timing to deliver alerts beyond the driver's line of sight. The architecture works with existing 4G and 5G cellular hardware and vehicle cloud environments, enabling automakers to deploy software updates without hardware modifications. The platform supports Euro NCAP compliance requirements and offers over 15 safety use cases, including intersection warnings, red-light notifications and hazard alerts.

Bryan Vaughn, Managing Director, AutoTech Breakthrough, said, “HARMAN Ready Aware is redefining vehicle safety from reactive intervention to proactive awareness. Almost a quarter of U.S. traffic deaths and roughly half of injuries are related to intersections. Cameras and sensors can be limited by physical occlusions and, on their own, may not have access to information about upcoming signal changes or other traffic conditions. Ready Aware’s software-defined model connects the intelligence already present in cities and connected vehicles, then delivers it to the driver as a timely, contextual alert. Ready Aware turns infrastructure data, vehicle telemetry and cloud analytics into actionable driver awareness—available today, scalable tomorrow, and quickly deployable.”

The system uses a cloud analytics and scoring layer named the Confidence Engine to filter data feeds, reduce false alerts and prioritise notifications to minimise distraction. Automakers can integrate the software via client-to-cloud or cloud-to-cloud configurations to support subscription services and feature monetisation.

Suman Sehra, Global Head of Connectivity Product and Portfolio Management, HARMAN, said, “Ready Aware gives automakers a flexible way to move connected vehicle safety from reactive intervention to proactive awareness. By transforming real-time road intelligence into timely, contextual alerts, Ready Aware helps drivers anticipate hazards before they come into view while giving automakers a scalable foundation to continuously enhance safety through software. This recognition reflects HARMAN’s vision for safer, more informed mobility.”

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