Excellent solutions for automotive electronic data acquisition, calibration and recharging

￭ETK helps engineers reduce the time and workload of development and calibration

ECU and bus interface modules:

Multi-signal and multi-series can solve the problems of diversified equipment to be collected, diversified communication signals and diversified communication protocols, and improve data collection efficiency.

3.Data re-injection system:

The collected actual vehicle data is processed by algorithms and injected back into the autonomous driving system for simulation and testing, algorithm verification, or the reproduction of some scenes and states is equally important for development: through data re-injection, actual driving scenes and situations can be reproduced, and the performance and algorithms of the autonomous driving system can be evaluated and verified. The re-injected data can include sensor data, vehicle status information, and driving behavior data. The amount of data is huge and complex, and the difficulty of re-injection verification is greater than that of collection. Therefore, powerful data re-injection software is an indispensable and important tool in the development process.

Below, we will use ETAS’ ADAS data reinjection solution as an example to explain the actual solution for data reinjection.

The above picture shows ETAS' high-performance PC-based recharge solution, which has the characteristics of scalability and high bandwidth. In order to cope with the increasing number of ADAS-related sensors, the recharge system can support up to 16 cameras, 12 radars and 4 lidar inputs, as well as the synchronous acquisition and recharge of multiple bus interfaces (Ethernet, CAN, FlexRay), and replay the defined scenarios based on the recorded data to perform batch testing. This solution can use the data collected by the vehicle to recharge the ADAS ECU to verify the ADAS algorithm that is modified and iterated.

The ETAS data reinjection solution solves the problem in actual development that the release and regression testing of ADAS software requires the collection of hundreds or thousands of vehicle mileages. It improves the efficiency of executing release and regression tests in virtual test systems and hardware open-loop (HoL) systems, and also solves the problem that performing specific edge case testing on vehicles is very time-consuming and expensive.

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Future Prospects for Data Collection and Calibration

Data acquisition, calibration, and data re-injection play an increasingly important role in the automotive industry and will continue to grow and evolve in the future.

Here are some future perspectives on data acquisition, calibration, and data re-injection:

1. Diversification of data collection:

With the development of automobile technology, the diversity of data collection will become an important trend. In addition to traditional vehicle sensor data, more external data sources will be involved, such as Internet of Vehicles data, high-precision map data, traffic data, etc. This will provide a richer and more comprehensive data source for calibration work to better optimize and adjust vehicle performance and behavior, and can even be used to optimize traffic flow and solve traffic congestion.

2.Automated calibration:

As autonomous driving technology matures, automated calibration will become an important development direction. Automated calibration uses technologies such as machine learning and artificial intelligence to automatically adjust and optimize vehicle parameters through analysis of large amounts of data and model training. This will greatly reduce manual intervention and time costs, and improve calibration accuracy and efficiency.

3. Real-time calibration and online update:

As vehicles become more intelligent and connected, real-time calibration and online updates will become more important. Vehicles can obtain the latest calibration parameters and optimization strategies in real time through connection with cloud systems to adapt to different driving environments and road conditions. This will make vehicles more adaptable and performant, and enable them to quickly respond to changing needs and challenges.

4. Data Privacy and Security:

As data collection increases, data privacy and security issues will become more important. The collected data may involve the user's private information, so corresponding security measures need to be taken to ensure the safe transmission, storage and use of data. At the same time, data security during the calibration process also needs to be guaranteed to prevent data from being tampered with or used maliciously.

5. Calibration standards and specifications:

With the popularization of data collection and calibration, the formulation of calibration standards and specifications will become an important development direction. The formulation of unified calibration standards and specifications will help ensure the consistency and comparability of calibration and improve the efficiency and quality level of the entire industry. This will promote data sharing and cooperation and promote the further development of calibration technology.

6. Intelligent and adaptive reinjection data:

Data feedback will become an important means to achieve intelligence and adaptability. By feeding actual operating data back into the vehicle system, the system can continuously learn and optimize, adapt to different driving environments and driver behaviors, and provide a more intelligent and personalized driving experience.

7. Reinjection to achieve personalized driving experience:

Through data feedback, the vehicle can be optimized according to the driver's personalized preferences and habits. For example, according to the driver's driving style and preferences, the vehicle can adjust various settings such as seats and audio systems to provide a more comfortable and personalized driving experience.

8. Recharge to achieve system optimization and fault diagnosis:

Through data feedback, vehicle manufacturers and technology providers can analyze and evaluate the performance of vehicle systems and identify potential problems and failures. This will help improve system design and development, provide more effective fault diagnosis and maintenance strategies, and improve vehicle reliability and maintainability.