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ASAM MDF Image, Radar, Lidar, Sensor Logging

PROJECT NUMBER
P_2021_04
PROJECT TYPE
Minor Version Development
PROJECT LEADER
Mr. Tobias Langner, ETAS GmbH
DOMAIN
Measurement & Calibration
ENROLL BY
Jul 20, 2021
PROJECT START
Jun 2021
PROJECT END
Dec 2024
RELEASE
Mar 2025


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Motivation

Raw image, lidar, radar and sensor data gain more importance in the development of modern cars particulary in the field of AD (Autonomous Driving) and ADAS (Advanced Driver Assistance Systems). Large numbers of these data is recorded every day. Currently there is no harmonized way to store these types of data in ASAM MDF4.x. This complicates the development of tools that want to access them. It also means that the different analysis tools are not interoperable due to the different ways of writing the data. Achieving this interoperability is one of the main goals of ASAM MDF 4.x as a Standard File Format for exchanging data in the automotive industry.

 

Project Scope

The aim of this project is to clarify how sensor raw data can be handled in ASAM MDF 4.x. Use cases and requirements that have been collected so far are detailed in the project proposal (download requires member login). The proposal can be commented and further requirements can be requested.

 

About ASAM MDF

MDF (Measurement Data Format) is a binary File Format to store recorded or calculated data for post-Measurement processing, off-line evaluation or long-term storage. The format has become a de-facto Standard for Measurement & Calibration systems (MC-systems), but is also used in many other application areas.

As a compact binary format, ASAM MDF offers efficient and high performance storage of huge amounts of Measurement data. MDF is organized in loosely coupled binary blocks for flexible and high performance writing and reading. Fast index-based access to each sample can be achieved by loss-free re-organization (i.e. sorting) of the data. Distributed data blocks even make it possible to directly write sorted MDF files. The File Format allows storage of raw Measurement values and corresponding conversion formulas; therefore raw data can still be interpreted correctly and evaluated by post-processing tools.



Participating Companies

  • ETAS GmbH
  • Accurate Technologies Inc.
  • BMW AG
  • b-plus GmbH
  • DENSO Corporation
  • dSPACE GmbH
  • HighQSoft GmbH
  • Huawei Technologies Co. Ltd.
  • iASYS Technology Solutions Pvt. Ltd.
  • Kistler Chemnitz GmbH
  • Kithara Software GmbH
  • MAN Truck & Bus AG
  • NI (National Instruments)
  • OTSL Inc.
  • Porsche AG
  • RA Consulting GmbH
  • Robert Bosch GmbH
  • Vector Informatik GmbH
  • Xylon d.o.o.

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