PROJECTS

iLIDS4SAM

There’s a pressing need to expand their application to urban traffic.

Current driver assistance systems mainly address simple scenarios, like highway traffic or parking without pedestrians and cyclists. The bmvit’s “Automated-networked-mobile” action plan prioritizes seven use cases, three of which involve urban scenarios requiring 360° vision and predictive hazard detection. Euro NCAP also outlines test cases, including Vulnerable Road Users (VRUs) like pedestrians, children, and cyclists in urban traffic.

Main Objectives of iLIDS4SAM

The research project will develop novel LiDAR-based systems for predictive hazard assessment with VRUs in urban areas. Achieving a substantial enhancement in both field of view and resolution necessitates innovations across all components of a LiDAR sensor.

Required innovations in components of a LiDAR sensor

  • a hybrid laser source for shorter and more intense pulses at a higher repetition rate
  • a new mirror and package design with a larger area at larger deflection angles
  • a receiver with a larger detector field and a more efficient and
  • at the same time more accurate pulse detection and time measurement.

Main Results

New Test and Reference Systems

New test and reference systems based on the high-resolution LiDAR sensor are being developed for the highly relevant simulation and validation of driver assistance and autonomous systems in urban environments.

Use Cases

Finally, various selected use cases, including for road and rail vehicles in urban areas and agricultural applications, will be implemented to demonstrate the relevance and performance of the approach in practice.