Connected Development in Driver Assistance – Paving the Way to Automated Driving Through Remote Validation and Big Data Analysis

The increasing complexity of driver assistance systems as well as the growing volume of data pose particular challenges to the development and validation of new systems. Connected Development is a new cloud-based approach which simplifies the validation process and shortens development iterations. Connected Development is an ongoing cycle, consisting of collecting data from the vehicle fleet and transferring it into a cloud storage, data management and analysis, writing new optimized software on request and software updates via remote flashing.

Even before the project starts, the engineers define which functions and driving situations should be monitored by Remote Validation. An on-board unit is required for transferring data to the cloud backend. While driving, surround sensors constantly capture the environment and process a multitude of data. If a defined situation occurs, such as Automatic Emergency Braking, only data from surround sensors categorized as relevant is captured by the on-board unit. The data is then uploaded to the cloud backend via a secure wireless connection practically in real time. At the same time and in the same manner, vehicle networking helps save data from locations around the world with different climatic conditions and from a range of vehicle configurations. The data center collects, organizes, checks and saves the recorded data from all networked vehicles and makes them available to the engineers. In this way, the engineers can effectively analyze the data from relevant driving scenarios. New software versions with optimized function performance and the corresponding validation jobs can instantly be developed based on the latest findings. After successful laboratory tests, the new software can be distributed securely and efficiently in the development vehicles via remote flashing.

Connected Development enables shorter learning cycles, increased efficiency and guaranteed quality in the development of new driver assistance systems. The field data exploration continues this approach even after serial production begins. In this case, it serves as a key enabling technology for the validation of future highly automated driving functions as well as for new data-based services such as Predictive Diagnosis and Maintenance.