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