iLIDS4SAM: Integrated LiDAR Sensors for Safe & Smart Automated Mobility

The reliability and safety of autonomous vehicles takes top priority when it comes to mobility of the future. The events occurring in the surrounding environment must be identified comprehensively and quickly. This is particularly challenging in complex urban road and rail traffic. The "iLIDS4SAM" research project is dedicated to precisely this topic.

Eleven Austrian partners from industry and science are pooling their expertise for this purpose. They are working together to research sensors that provide autonomous vehicles on the road or rail with a 3D image of their surroundings and detect hazards in advance. The aim is to develop a powerful and cost-effective laser sensor system with data management based on deep learning. The sensor system will be tested in urban road and rail traffic as well as in agricultural applications in order to demonstrate both integration and practical performance.

It is an innovative showcase project because it covers the entire technology and application chain with hardware and software adjustments as well as laboratory and road-based tests.

Three-dimensional vision for vehicles

The team is working on innovative and compact lidar sensor systems to provide a greater field of vision with high resolution. Using microchip mirrors, a laser beam scans the surroundings with millimetre precision in order to measure the distance and shape of objects. The result is a 3D image of moving vehicles or pedestrians, traffic signs, roadside obstacles and even road markings.

A large field of vision combined with high resolution and a high frame rate result in a very large number of measurements that have to be performed per second. The challenges involve achieving a high measurement rate and thereby also a high data rate, as well as optimising and miniaturising all components, the connection technologies and the mirror design. The system is to be installed e.g. behind the windscreen, in the headlights or in the rear lights.

Learning sensors

Real test drives with the new LiDAR demonstrator are an important part of the project. The aim is to collect a large amount of real-world data in order to use learning algorithms to predict behaviour and be able to derive a hazard assessment. Big data as well as artificial intelligence are used to improve and optimise the system on a continuous basis.

The project ran until mid-2023. The innovative sensor is also being tested in the laboratory under difficult weather conditions such as fog, with simulations also being carried out. Real tests will follow in urban road and rail traffic as well as in agriculture. The project contributes to the SDGs by promoting the safety of all road users through smart technologies, improving smart and zero-emission mobility in urban and rural areas and strengthening the overall innovation capacity of the partners.

Consortium leader

• Infineon Technologies Austria AG

Additional consortium partners

• AVL List GmbH
• ams AG, EV Group E. Thallner GmbH
• FH Campus Wien Forschungs- und Entwicklungs-GmbH
• Infineon Technologies Austria AG
• Peschak Autonome Systeme GmbH
• RIEGL Research Forschungsgesellschaft mbH
• Silicon Austria Labs GmbH
• Graz University of Technology (Institute of Computer Graphics and Vision)
• TTTech Auto AG
• Virtual Vehicle Research GmbH