Automobile manufacturer
Development of the backend for driver assistance systems
Starting point
- Vehicles can currently only use local sensors for information gathering
- Information for the driver is limited to the current, direct environment
- There is no possibility to influence the sensorics and information gathering in the vehicle
- The exchange of information with other vehicles enables new assistance functions for new vehicle generations
Procedure
- Project implementation based on the agile SAFe methodology in conjunction with DevOps
- Definition of user stories in collaboration with the business department
- Development and planning in iterative sprints.
- Bi-weekly, productive deployment
- Collaboration as an interdisciplinary team with developers and operations
- Transformation of sensor data for later big data analysis and 3rd-party tools
- Performance and test management
Features/Project outcome
- Development of JavaEE microservices with Kafka and REST interfaces
- Development of an expert system (including GUI) to influence information gathering in vehicles
- Development of a scalable solution through cloudification and Docker
- Preparation of data for transfer to the Hadoop Data Lake
- Takeover of application management during development and live operation
Customer benefits
- New driving experience through the expansion of virtual sensor range with information from a real-time backend
- Fail-safe and highly available solution that scales with the rapidly increasing number of vehicles
- Faster and more stable development results through an agile project approach and interdisciplinary teams
- Future-proofing through integration with the data lake, with potential for advanced analytics & data science

Erich Holzinger | Senior Manager / Authorised Officer