Online Certificate Course
Simulation of Automated Vehicles  

Turning the vision of autonomous driving into reality requires a fundamental digital transformation which forces engineers to face multidimensional and interdisciplinary challenges. Computer simulation offers a key technology for handling these complex tasks and will be a game changer as a strategic element of product lifecycle. But more than ever before, agile, cross-company and cross-border digital processes are required. This also places new demands on the workflow and knowledge of simulation experts. Our ENVITED academy Certificate Course "Simulation of Automated Vehicles" will provide you with a comprehensive overview and cross-disciplinary context of a data-driven simulation process for the virtual development and validation of automated vehicles. 

Our certificate course takes an application-oriented look at the requirements of current and future data-driven simulation processes. In the context of virtual 3D worlds, technologies from data acquisition to processing, analysis and quality assessment will be presented. Participants will gain insight about different sensor types as well as methods for sensor fusion, integration, modeling, simulation, validation and artificial intelligence approaches. On the way to the simulation of Advanced Driver Assistance Systems (ADAS) and their driving functions, basics of scenario description, traffic flow and agent models are covered. The course builds on standardization projects such as ASAM OpenX and covers open source software approaches to simplify participants' entry into the field and community. Experienced lecturers from Science and Industry will teach approaches to co-simulation, credible simulation and virtual testing, as well as technologies for studies and experiments in the driving simulator environment. Distributed ledger technologies will be introduced to participants as one possible technology on the path to data traceability and trust for continuous proof of virtual validation. Take advantage of your opportunity for professional development and networking and join our community for an interactive and forward-looking online course.  

At a glance 

 

Degree
Diploma of Advanced Studies (Certificate Course)

Study Mode
part-time, online

Period of Study
9 months  (November - July), ~120 training hours

Study Organizations
SCMT / School of Management and Technology (SMT) of Steinbeis Hochschule Berlin (SHB)

Language of Instructions
English

Examination Mode
one online case presentations per module (four total) + one written scientific / transfer work

Number of Participants
at least 10

Requirements for Admission
University entrance qualification or professional qualification

Study Fees
6.400 € + VAT for members of asc(s e.V.   |   8.000 € + VAT regular
 

 

Who should take part?

 

Our Certificate Course "Simulation of Automated Vehicles" is aimed at professionals and young expterts in the automotive engineering industry, who like to qualify for activities in the simulation of automated vehicles and/or link existing knowledge in the overall context:

  • Beginners and cross-starters
  • Development and software engineers
  • Project leaders
  • Business developers
  • Employees in software and consulting companies

with focus on

  • Advanced Driver Assistance Systems (ADAS)
  • Automated and Autonomous Driving
  • Virtual Test / Test Fields
  • Vehicle Electronics
  • Mechatronics
  • Software Development
  • System Development
  • Product Development

The part-time Certificate Course "Simulation of Automated Vehicles" consists of the following four interactive online modules:

  • MODULE A: Overview & Virtual 3D Environments
  • MODULE B: Sensors
  • MODULE C: Scenarios & Driving Functions
  • MODULE D: Virtual Test & Certification

Each indivudual module consists of seven training units plus one case presentation unit (3-4 hours each).

Examination Mode
Every participant choose one case topic per module. Cases are small, application-oriented tasks which are provided by the lecturers. Cases are worked on alone or in a group and presented and discussed in a separate case presentation unit at the end of each module. In addition to the four case presentations, a written scientific paper must be prepared as a certificate of achievement. The topic can also be selected and can be an application-oriented, written transfer work for a task from your company. Cases and scientific paper / transfer work will be accepted by the lecturers.

 

MODULE A: Overview & Virtual 3D Environments

25 November 2021  |  9 a.m. - 12:30 p.m. CET 
Kick-off event
Participants + Module Lecturers


More details to follow.

25 November 2021  |  2 p.m. - 6 p.m. CET 
A1 - Overview Simulation Ecosystem
Lutz Morich (Audi AG)


Motivation:
  • Three Reasons why the marekt entry of autonomous driving functions could fail
  • Something has changed …

Overview on Eco-System:
  • Sharing is caring
  • Roles and rersponsibilities
  • Network and traceability

Some hard and soft facts
  • Standardisation
  • Coopetition

Outlook
  • The European perspective and competitors from Asia and the US The long and winding road to autonomous vehicles in real traffic

26 November 2021  |  2 p.m. - 6 p.m. CET 
A2 - Mobile Mapping & Data Processing
M.Reiter, D.Tosic (3D Mapping Solutions GmbH)

  • Mobile Mapping Technology and Systems
  • Position and Orientation Systems
  • Mapping of any kind of roads
  • Data organisaton / road databases
  • Post-processing and quality management
  • (automatic) Homogenization
  • Scanner and image data-processing
  • Examples
  • 9 December 2021  |  2 p.m. - 6 p.m. CET 
    A3 - Data Analysis & HD Maps
    Florian Günther (3D Mapping Solutions GmbH)

  • Object data catalogues and object attributes
  • Object data extraction
  • Scenario extraction options
  • Result: as-built-plan and its applications
  • Road logic and topology
  • Data formats , e.g. OpenDRIVE, OpenCRG
  • Quality management / data quality certificates
  • Application software examples
  • 10 December 2021  |  2 p.m. - 6 p.m. CET 
    A4 - City Models
    Maximilian Sindram (virtualcitysystems GmbH)


    Urban Information Modeling
    • Virtual 3D City Models
    • CityGML motivation and overview
    CityGML Details
    • Modeling of buildings, streets, terrain models, other objects
    • Multi-level modeling
    • Geometric-topological modelling
    • Spatio-semantic coherance
    • Surface properties
    • Implicit geometries
    • Extension mechanisms
    CityGML applications from practice
    • Urban information hub
    • Urban simulation (environment and traffic)
    CityGML and OpenDRIVE
    • Principals of ODR Standard
    • Differences in modeling paradigms
    • Model transformation

    20 January 2022  |  2 p.m. - 6 p.m. CET 
    A5 - 3D Environments
    N.N. (Triangraphics GmbH)


    General
    • dynamic vs static (ground truth), Scene Maps vs Scenario
    Data & Formats
    • GIS Formats: Raster, Vector,...
    Materials
    • PBR and lighting
    • Sensor material definition, segmentation
    Metainformation, Tags & Codes
    • Materials, Collision Volumes etc.
    • FACC, OSM attributes,…
    Scene map features
    • Road generation
    • Traffic signals, markings, decals, road furniture,...
    • Bridges, tunnels, underpasses,…
    • Buildings, vegetation, waterways
    Modelling
    • Quality Parameters: poly-count, textures, LODs
    • Sensor Modelling rules
    Target Platforms
    • Game engines, automotive platforms
    Use-Cases & Corner Cases
    • ALKS,…

    21 January  2022  |  2 p.m. - 6 p.m. CET 
    A6 - Material Models / OpenMaterial
    Dr. Ludwig Friedmann (BMW AG)


    OpenMaterial – Presentation

    Simulation-based development and test of automated driving
    • Software architecture
    • File formats
    • Interfaces
    Sensor simulation
    • Environment representation
    • Modeling
    3D models and materials
    • Model structure
    • Rendering
    • Khronos glTF 2.0
    • OpenMaterial
    OpenMaterial – Exercise
    • 3D model creation and rendering in Blender
    • Application of physical material properties
    • Physically based rendering using the OpenMaterial pathtracer

    3 February 2022  |  2 p.m. - 5 p.m. CET 
    A7 - Case Presentations & Discussion
    Participants + Module Lecturers


    More details to follow.

    MODULE B: Sensors

    4 February 2022  |  2 p.m. - 6 p.m. CET 
    B1 - Sensor Basics
    Jürgen Wille (FrontMod GmbH)


    ADAS sensor technology
      Sensor types and there application
    • Ultrasonic sensors
    • Camera sensors
    • Radar sensors
    • LIDAR sensors
    Sensor characteristic
    • Sensor parameter
    • Detection range
    • Strength and weakness
    • Environmental influence
    ADAS architecture
    • Sensor calibration
    • Sensor data recording setup

    17 February 2022  |  2 p.m. - 6 p.m. CET 
    B2: Sensor Fusion & Integration
    Jürgen Wille (FrontMod GmbH)


    Sensor integration
    • Integration methods
    • Influence of mounting position
    Sensor fusion
    • Architecture
    • Fusion stages
    • Plausibility Checks
    • Reliability
    Beyond sensor fusion
    • Connected car concepts
    • Applications of automous driving

    18 February 2022 |  2 p.m. - 6 p.m. CET 
    B3: Sensor Simulation
    Jürgen Wille (FrontMod GmbH)


    Modeling platforms
    • Available tools
    • Simulation methods
    Sensor representation & integration
    • Coordination systems
    • Mounting point
    • Modeling parameter
    • Environment modeling parameter
    • Detection Area
    Sensor behaviour modeling
    • Functional
    • Phenomenological
    • Physical
    Sensor data
    • Sensor processing chain
    • File formats
    • Interfaces
    Applications
    • On-/Offline simulation
    • Co-simulation
    • Hardware-In-Loop (HIL)

    10 March 2022  |  2 p.m. - 6 p.m. CET 
    B4: FMI + OSI
    Pierre Mai (PMSF IT Consulting)


    Introduction to the FMI Standard, History, Scope and Vision

  • Use & benefit in the simulation process
  • What is an FMU?
    • Contents and important concepts (FMU, Variables, Types, Kinds of FMUs, Multi-Platform, Additional Resources, ...)
  • FMI 3.0 - new extensions and directions
    • (vECU, SE, ...)
  • FMI in practice:
    • Tool-based FMU generation, Code-based FMU generation, FMU import
  • FMI in Context:
    • Related resources, Organisations and Standards (SSP, OSI/OSMP, SmartSE Rec, MA)


    Introduction to OSI
  • Use & benefit in (sensor) simulation process
  • OSI Data Layer
  • OSI Packaging Layer - OSMP
  • OSI in practice:
    • OSI-based Sensor Modeling & Simulation
  • OSI in Context:
    • Related Resources, Organisations and Standards (SSP, ASAM, OpenX)

    11 March 2022   |  2 p.m. - 6 p.m. CET 
    B5: Sensor Model Validation
    C. Linnhoff, P. Rosenberger (TU Darmstadt)


    Holistic demonstration from requirements to sensor model uncertainty quantification:
    • Sensor effect ontology by Perception Sensor Collaborative Effect and Cause Tree (PerCollECT)
    • Requirements for sensor models by Cause, Effect and Phenomenon Relevance Analysis (CEPRA)
      • Requirements for the ODD description
      • Possible SUTs to be tested with sensor models
      • Sensor hard- and software to be modeled incl. interface description
    • Exemplary requirement list for lidar modeling
    • Implementation of an exemplary effect chain in a lidar sensor model
    • Model validation
      • Model calibration vs. validation
      • Experiment design
      • Isolated effect as visible in real sensor data
      • Replay-to-sim (Reference data as input)
    • Metrics for sample validation
    • Inter- / extrapolation of sample validation results for model application

    24 March 2022  |  2 p.m. - 6 p.m. CET  
    B6: SiL Simulation (Component)
    Dr. Hardi Hungar (DLR)


    Defining the framework and illustration on sample cases

  • Methodological frame of SiL simulation
    • Simulation problem definition
      - Process step
      - Simulation task definition
  • - Simulation preparation
    • - Abstraction level (modeling level)
      - Simulation algorithmic
      - Tool requirements
  • Simulation setup
    • - Tool and model selection
      - Tool instantiation
  • Result evaluation
    • - Extraction of the contribution of the simulation

    25 March 2022 |  2 p.m. - 6 p.m. CET 
    B7: AI for AD / Sensor Processing
    N.N.


    More details to follow.

    31 March 2022  |  2 p.m. - 6 p.m. CEST 
    B8: Case Presentations & Discussion
    Participants + Module Lecturers


    More details to follow.

    MODULE C: Scenarios & Driving Functions

    1 April 2022  |  2 p.m. - 6 p.m. CEST 
    C1 - Scenario Design
    Dr. Martin Fischer (DLR)


    Scenario Definition

  • Terms
  • Scenario Layers

  • Scenario Description
  • Level of Detail
    • (abstract, functional, logical, concrete)
  • Description Languages
    • (Overview & intensive explanation of OpenSCENARIO)
    Scenario Examples

    Practice Session on Scenario Design

    Scenario Generation & Data Bases
  • Statistical Data
  • Recorded Data
  • Artificial Scenarios


  • Special Scenario Challenges
  • From Test Case to Scenario Description
  • Different Scenarios for diff. XIL simulations
  • Provoking dangerous/critical situations
  • Multi Human-in-the-Loop scenarios
  • 7 April 2022 | 2 p.m. - 6 p.m. CEST
    C2: Traffic Simulation / Agent Models
    Dr. Raphael Pfeffer (
    IPG Automotive GmbH)


    Introduction:
    • Use cases for Traffic Simulation & Agent Models across Automotive domains
    • Traffic simulation and agent models for ADAS/AD
    Theory:
    • Overview on traffic models
      • classification: macroscopic
    • Human driver models
    • AI based models & social forces
    • Simulation enviroment: Model interfaces (e.g. sensors, lanes...)
    Industry State-of-the-Art, Examples & Demos:
    • Traffic flow simulation
    • HDM
    • AI & neuroscientific based models
    • examples

    8 April 2022 | 2 p.m. - 6 p.m. CEST
    C3: ADAS Simulation
    Christopher Wiegand (dSpace GmbH)


    Introduction & Overview – ADAS/AD Systems Modelling aspects & terminology
    • What is the Operational Design Domain?
    • What is the Dynamic Driving Task?
    • What is a Scenario?
    Simulation Models, Simulators & System under test
    • System under Test: Requirements on simulations
    • Simulators: SIL, HIL & DIL
    • Simulation Models
    • Sensor Models (e.g. fidelity levels for Radar Lidar, Camera and Ultra Sonic Sensor)
    • Environment & Scenery
    • Scenarios
    • Traffic
    • Vehicle Dynamics
    Interfaces (e.g. FMU, OpenDrive, OpenScenario & OSI, Co-Simulations)

    How to make sure simulations provide reliable results and can be used for validation?

    28 April 2022 | 2 p.m. - 6 p.m. CEST
    C4: SSP
    Peter Lobner (eXXcellent solutions GmbH)


    Introduction:

    • Block introduction & agenda
    • Challenges in development of complex simulation systems
    • Challenges adressed by SSP
    Introduction to the SSP Standard, history, scope & vision

    SSP Walkthrough: Creating a SSP model from scratch alongside the simulation process to explore the SSP core principles & concepts

    SSP advanced principles & concepts

    Use in specific contexts, outlook & potentials (OSI connectors, SSP4Traceability, ...)

    29 April 2022 | 2 p.m. - 6 p.m. CEST
    C5 - Co-Simulation
    Dr. Martin Benedikt (Virtual Vehicle)


    Intro SystemSimulation

  • Complicated and complex Systems
  • System of Systems
  • Need for distributed, modular Simulation
  • Modular simulation within the VDP
  • Examples

  • Integration Challenges
  • Standards
    • (FMI, SSP, DCP, etc.)
    Numerical Integration
  • Methods
  • Examples

  • Co-Simulation Platform use by participants
  • FMU developmetn and provision
  • FMU Integration
  • Co-Simulation configuration)
  • 12 May 2022 | 2 p.m. - 6 p.m. CEST
    C6: Credible Simulation
    Dr. Martin Benedikt (Virtual Vehicle)


    Virtual-enriched Development Process

  • Motivation for virtual testing
  • How is simulation used?

  • Credibility Definition
  • History and recent developments
  • Relation to Quality

  • Process and Artefact quality
  • History and related standards
    • (ISO, ASPICE, etc.)
  • Credible Simulation Process
  • Credible Assessment Framework

  • Credibility Argumentation
  • MBS representation for analysis
  • Application Example (ALKS)
  • 13 May 2022 | 2 p.m. - 6 p.m. CEST
    C7: AV Software
    Prof. D. Watzenig / M. Schratter (Virtual Vehicle)


    Automated Driving Software

  • System architecture overview
  • Different system levels
  • Automated Driving stacks
    • Commercial solutions
      Open-source solutions
    Demo Automated Driving SW stack
  • Introduction Autoware
  • Autoware running on a research vehicle
  • Demo 1: Lidar-based localization
  • Demo 2: Path planning
  • 2 June 2022  | 2 p.m. - 6 p.m. CEST
    C8: Case Presentations & Discussion 
    Participants + Module Lecturers


    More details to follow.

    MODULE D: Virtual Test & Certification

    3 June 2022  |  2 p.m. - 6 p.m. CEST 
    D1 - Scenario Test Automation & Valid.
    Jann-Eve Stavesand  (dSpace GmbH)


    General Overview of Test Strategies for the Safety Argumentation and Homologation of ADAS/AD
    • Terms and Definitions - to understand the lectures content
    • Automotive Industry Insights - Impact on Homologation
    • Data-driven Development Enables Autonomous Driving
    • Existing Standards and Current Research Activities
    • A Blueprint for New AD/ADAS Test Strategies
    • Use Cases Requirements Based Testing on Closed Loop HIL
      • Use Cases Requirements Based Test SIL
        • Use Cases Requirements Based Testing MIL
        • Use Cases Fault Injection on MIL
      • Use Cases Open Road Testing with a Scenario-based Approach
        • Use Cases Scenario-based Testing on Proving Grounds
        • Use Cases Hardware Reprocessing / Data Replay
        • Use Cases Vehicle in the Loop
        • Use Cases Driver in the Loop, Scenario-based
        • Use Cases Scenario-based SIL Closed Loop
    • Artificial Intelligence impacting testing
    • Possible new standards of testing

    24 June 2022 | 2 p.m. - 6 p.m. CEST
    D2: Driving Simulator Technologies I
    Dr. Jens Häcker (
    Simulation Systems Consulting)


    Introduction: digital validation/verification of chassis and assistance systems
    • Digital Development: SiL/HiL, Integration Human-Simulation: Driver-in-the-Loop
    • Application: MMI, vehicle handling and driver behavior, vehicle dynamics assessment and chassis development, vehicle safety, training

    Technical aspects of driving simulators
    • software framework/driving simulation: vehicle dynamics and models
    • road and environment, traffic simulation
    • scenario generation, databases
    • visual system, motion system, audio system and vibration
    • cabin and controls: steering simulation, pedals, UI

    Visual Systems
    • overview and historical development: flight simulation, first driving simulators
    • visual system processing, projector and screen, static and dynamic systems, performance, image generation software, tools and databases
    • projection, displays, cave, HMD
    • spatial perception: stereo systems, technical solutions, goals and limits

    Simulator motion systems and human perception
    • mapping of vehicle motion in a simulator
    • motion perception and vection
    • motion cueing algorithms for motion sim.
    • technical implementation and example syst.

    25 June 2022 | 2 p.m. - 6 p.m. CEST
    D3: Driving Simulator Technologies II
    Dr. Jens Häcker (Simulation Systems Consulting)


    Virtual Reality systems and applications

    Human in the control loop: Human Factors
    • immersion and presence
    • perceptual fidelity in the design of virtual environments
    • validity of simulator experiences, driving behavior/reaction/perception, perception of realism/hazard/risk
    • medical aspects: kinetosis and motion perception, physiological and psychological care, supervision of test persons
    • ethical aspects: test person as a “guinea pig”, high risk situations, accidents, ethical review committee

    Methodology: design of simulator experiments
    • conceptual design of a driving simulator experiment:objective (goal and limits), experimental setup, „customer vs. experimenter“
    • selection criteria for test participants
    • data acquisition: subjective vs. objective data, evaluation criteria, measurements, questionnaires, video
    • statistics: sample size, sample distribution, demographic aspects, evaluation and interpretation
    • experimenter: qualification, training, „researcher bias“, emergency training, after care
    • testing and preliminary experiment

    Scope of Simulator studies and example applications
    • driving simulator experiments for chassis development and vehicle handling/comfort
    • evaluation of assistance systems
    • case-studies for autonomous driving

    30 June 2022 | 2 p.m. - 6 p.m. CEST
    D4: Test vs. Simulation 
    Dr. Hardi Hungar (DLR)


    • Simulation validity issues
    • Methodological approach to
      simulation validation
    • Example instantiation of simulation validation
    • Deriuving assertions from combined test and simulation (contributed evidence)

    1 July 2022 | 2 p.m. - 6 p.m. CEST
    D5 - Functional Safety
    Dr. Hardi Hungar (DLR)


    Defintion of "Safety Case"
    • Purpose
    • Relation to relevant standards
    • Important terms and concepts
    Structure of a safety case Constituents
    • arguments and factual evidence
    Safety Case example sketch

    Relation to develoment activities

    14 July 2022 | 2 p.m. - 6 p.m. CEST
    D6: Distributed Ledger Technologies I
    C. v. Driesten (BMW) / Prof. F. Matthes (TUM)


    DLT as process facilitator
    • DLT for data-driven, simulation-based development (identity management, logging)
    • automation of testframeworks
    • state of the art
    • remaining/inherent challenges

    15 July 2022 | 2 p.m. - 6 p.m. CEST
    D7: Distributed Ledger Technologies II
    C. v. Driesten (BMW) / Prof. F. Matthes (TUM)


    DLT on more technical level
    • blockchain basics: consensus, safety assumptions, attack vectors, p2p networks, core concepts
    • public vs permissioned ledgers
    • smart contracts: language design, safety concepts and token standards
    • change management process: governing and upgrading decentralized and distributed systems
    • utilizing economies of scale and network effects of shared and open source resources
    • example projects: knowledge and application transfer to the automotive domain

    28 July 2022  | 2 p.m. - 6 p.m. CEST
    D8: Case Presentations & Discussion 
    Participants + Module Lecturers


    More details to follow.

    An on-site final event at a driving simulator facility is planned for September 2022. More information to follow.

    Notice:

    • Individual modules can be booked separately. Degree: Diploma of Basic Studies.
    • All live modules take place online via Zoom and the dates may still change slightly.

    Benefit from the extensive and application-oriented expertise of our lecturers from business and science:

     

    Lutz Morich  (Audi AG)


    Lutz Morich studied mechanical engineering at RWTH Aachen University and began his professional career as a trainee in technical development at AUDI AG. 16 years of experience in managing projects and organizational units in management positions. Since 2017 he has been responsible for "Processes, Methods and Tools of the Virtual Disciplinary Environment" and several R&D projects with cooperation partners from industry, science and municipalities that deal with interdisciplinary and technical questions of automated traffic.


    Training unit: A1 - Overview Ecosystem


     

    Marina Reiter (3D Mapping Solutions GmbH)


    Marina Reiter is working as a geodetic engineer at 3D Mapping Solutions GmbH since 2019. She received her B.Sc. degree in geography at the LMU Munich. While studying at the University of Würzburg she graduated as M.Sc. in remote sensing analysing the distribution of urban green areas in the 80 biggest cities in Germany. At the department of Geodetic Analytics, she is involved in pre- and postprocessing LIDAR data and creating surface models for worldwide automotive companies.


     Training units:  A2 - Mobile Mapping & Data Processing 


     

    Dragana Tosic (3D Mapping Solutions GmbH)


    After receiving her M.Sc. degree in 2019 at the Technical University of Munich in the field of Mobile Mapping data classification Dragana Tosic continued her path in this area as a project engineer in the Geodetic Analytics department at 3D Mapping Solutions. Some of the areas she is active in at this position are determination and correction of vehicle trajectories, system calibration, highly precise data homogenisation, preparation of precise 3D plans and terrain models for various purposes and different formats, as well as data quality management.


     Training units:  A2 - Mobile Mapping & Data Processing 


     

    Florian Günther (3D Mapping Solutions GmbH)


    Florian Günther is a project leader and training manager in the field of high-precision and high-resolution mapping of road networks at 3D Mapping Solutions GmbH since 2018. He studied Business Administration and Cartography|Geomedia at the University of Applied Sciences Munich. He graduated as B.Sc. in the field of computer animation and 3-dimensional LiDAR surveys about Bibracte at the European Archaeological Center, France. Since then, he was involved in data analysis and processing HD maps for worldwide automotive industry and research driven use-cases. At the department of HD Maps his current focus is on providing user-specific cases in advanced ADAS or test and validation applications for autonomous driving, such as the combination and integration of different formats like OpenDRIVE, GIS and 3d Modelling.


     Training units:  A3 - Data Analysis & HD Maps


     

    Maximilian Sindram (virtualcitysystems GmbH)


    In his position as business development manager at virtual city systems, Maximilian Sindram focuses on spatial and semantic modeling, analysis, and visualization of 2D and 3D geodata. Key areas are urban information modelling, urban simulation, and smart cities. Maximilian Sindram studied geography at the Ludwig-Maximilians-University in Munich. After his studies he worked as a junior researcher at the ifo Institute in Munich on research related topics to GIS in economics before leaving in 2012 to join the Chair of Geoinformatics at TU Munich. Since January 2018 he has been working as Business Development Manager at virtual city systems. As a lecturer at TU Munich, he has been awarded the faculty's teaching prize several times. In addition to his professional tasks, Maximilian Sindram is involved in professional associations and standardization committees. Among others, his contribution to the modeling of the OpenDRIVE standard in ASAM e.V. and his profound knowledge of the OGC standard CityGML are worth mentioning.


     Training units:  A4 - City Models


     

    N.N. (Triangraphics GmbH)

    Description to follow


     Training units:  A5 - 3D Environments


     

    Dr. Ludwig Friedmann (BMW AG)


    Since 2018: Solution Architect Simulation Autonomous Driving (BMW Group)

    • Simulation architecture, 3D models and materials
    • Distributed simulation frameworks
    • Standardization

    2016-2018: Product Manager Software Development Tools/Methods (Audi AG)

    • Simulation @ Autonomous Intelligent Driving GmbH
    • Distributed simulation software
    • Virtual environment and 3D models

    2010-2016: Research Associate/PhD Candidate (TUM)

    • Flight simulation software
    • Real-time simulation of rotorcraft downwash
    • Multi-channel rendering

     Training units:  A6 - Material Models - OpenMaterial


     

    Jürgen Wille  (FrontMod GmbH)


    Jürgen Wille studied precision engineering at FH Ulm and information technology at the University of Paderborn. He began his professional career as research associate at TU Berlin and the Fraunhofer Institute IZM. He joined Valeo GmbH in 2001 and worked in the field of hardware design and simulation methods over 17 years. Since 2006, he has been involved in the field of perception sensor model development and EMC verification. His focus was lying on ultrasonic and radar sensors and optimisation of sensor mounting positions inside virtual car models. He was involved in the European project "ENABLE-S3" and build up several sensor HIL tester to enable autonomous parking. Jürgen founded FrontMod GmbH in 2018. FrontMod is member of the ASC-S and develops sensor models for OSI standard.


     Training units:  B1 - Sensor Basics   |   B2 - Sensor Fusion & Integration   |   B3 - Sensor Simulation


     

    Pierre R. Mai ( PMSF IT Consulting)


    As the founder and owner of PMSF IT Consulting focuses on the intersection between system development and simulation. One key area in the past decade has been the development and standardization of simulation and model interfaces for use in the automotive industry development processes. In this vein Pierre R. Mai is a member of the Modelica Association FMI and SSP, as well as founding member of the ASAM OSI and OpenSCENARIO standardization projects. In the past he coordinated the establishment of the ASAM Simulation Area and the transfer of the OpenX standards to ASAM in an interim capacity. Pierre R. Mai studied computer science at the Technical University Berlin with a focus on programming language design, implementation and constraint systems receiving his degree in 2002. Since then he has founded and lead a number of businesses in the simulation and technology domain, with a broad industrial and automotive customer base.


     Training units:  B4 - FMI + OSI


     

    Clemens Linnhoff (TU Darmstadt)


    Clemens Linnhoff received the B.Sc. and M.Sc. degrees in mechatronics from the Technical University of Darmstadt in 2016 and 2018 respectively. Since 2019, he has been working as Research Associate and PhD Candidate with the Institute of Automotive Engineering at the Technical University of Darmstadt, under the lead of Prof. Dr. rer. nat. Hermann Winner. Currently, he is involved in the German projects "SET Level" and "Verification & Validation Methods" in the field of perception sensor model development and model verification. His research is focused on the simulation of environmental influences on perception sensors, with special interest on radar and lidar simulation. Together with his research group at TUDa FZD, he established the PerCollECT initiative (https://github.com/PerCollECT) to collect and provide perception sensor cause effect chains in a tree-shaped ontology. Furthermore, the research group provides open source perception sensor models within a unified FMI/OSI model framework under https://gitlab.com/tuda-fzd/perception-sensor-modeling.


     Training units:  B5 - Sensor Model Validation


     

    Philipp Rosenberger (TU Darmstadt)


    Philipp Rosenberger received his B.Sc. and M.Sc. degrees in mechatronics from the Technical University of Darmstadt in 2013 and 2016 respectively. Since 2016, he has been working as Research Associate and PhD Candidate with the Institute of Automotive Engineering at Technical University of Darmstadt, under the lead of Prof. Dr. rer. nat. Hermann Winner. He was leading the work package for simulation and stimuli within the European project "ENABLE-S3" and was responsible for the sensor model development and validation within the German project "PEGASUS". Currently, he is involved in the German projects "SET Level" and "Verification & Validation Methods" to continue his work on model development and validation. His research is focused right now on the methodology for perception sensor model validation, with special interest on experiment design and fidelity criteria for the models. Besides, he is a founding member and part of the Change Control Board of the ASAM OSI standard. Together with his research group at TUDa FZD, he established the PerCollECT initiative (https://github.com/PerCollECT) to collect and provide perception sensor cause effect chains in a tree-shaped ontology. Furthermore, the research group provides open source perception sensor models within a unified FMI/OSI model framework under https://gitlab.com/tuda-fzd/perception-sensor-modeling.


     Training units:  B5 - Sensor Model Validation


     

    Dr. Hardi Hungar (DLR - Institute of Transportation Systems)


    Hardi Hungar received a PhD in computer science from the Christian Alberechts University in Kiel, and has the venia legendi (habilitation) at the Carl-von-Ossietzky University Oldenburg. For many years, he has worked on methods and tools for the development of dependable and safety-critical systems. These concerned mainly applications in the transportation domain. He has held various positions in academia, research and industry. In his current position, he leads the team on "Processes and Methods for Verification and Validation" at the Institute of Transportation System, which is one of the institutes of the German Aerospace Center (DLR). He is currently working mainly on methods for the verification and validation of highly automated vehicles. His focus areas include concepts and languages for defining test scenarios, algorithms and tools to perform exhaustive virtual tests, standard-conformant development, and safety argumentations.


     Training units:  B6 - SiL Simulation  |  D4 Test vs. Simulation  |  D5 Functional Safety 


     

    Dr. Martin Fischer (DLR - Institute of Transportation Systems)


    Dr. Martin Fischer studied Electrical Engineering at the Hanover University and got his degree in 2003. In 2009 he graduated as Dr.-Ing. at the University of Braunschweig with his work on “Motion-cueing algorithms for moving-based simulators”. He works for the German Aerospace Centre - Institute of Transportation Systems as a researcher and he is leading the group “Human-Centered Simulation” in the department “Validation and Verification”. His research focuses on human-in-the-loop simulation methods and technologies.


     Training units:  C1 - Scenario Design


     

    Raphael Pfeffer (IPG Automotive GmbH)


    Raphael Pfeffer studied Industrial Engineering at the Karlsruhe Institute of Technology (KIT) and got his degree in 2012. In addition he holds an M.Sc. in Business Psychology & Leadership and a Ph.D. in Electrical Engineering and Information Technology in the field of functional safety of autonomous vehicles using simulation. In his professional career he has been with the automotive industry for 10 years and is currently leading the innovation team at IPG Automotive GmbH applying state-of-the-art technologies such as machine learning for the automotive development.


     Training units: C2 - Traffic Simulation / Agent Models


     

    Christopher Wiegand (dSpace GmbH)


    Christopher Wiegand is Strategic Product Manager at dSPACE GmbH, where he is responsible for the business fields Modelling & Simulation and Scenario Generation & Library. He studied electrical engineering and received his Dipl.-Ing. degree from the University of Paderborn in 2007. He joined the Fraunhofer Institute and Sensor Technology Group of the University of Paderborn as a research engineer and received a doctor’s degree in electrical engineering in 2012. 


     Training units: C3 - ADAS Simulation


     

    Peter Lobner (eXXcellent solutions GmbH)


    Peter Lobner studied Computer Science at the University Ulm and graduated as Dipl. Inf. in 2011. He then started his career as a software engineer at eXXcellent solutions GmbH and has gained experience in the development of complex software solutions in different industry sectors like E-Learning, Energy and Automotive over more than 10 years. He is currently working as software architect and project manager in different projects. One is orchideo | easySSP, a cloud based model editor and simulator for the System Structure & Parameterization (SSP) Standard of the Modelica Association. Moreover, he is a member of Modelica's SSP working group and actively participating in evolving the standard further. His interests are focused mainly on the creation of innovative & collaborative SaaS solutions and agile leadership.


     Training units:  C4 - System Structure and Parameterization (SSP) Standard


     

    Dr. Martin Benedikt  (Virtual Vehicle Resarch GmbH)


    Description to follow


     Training units:  C5 - Co-Simulation  |  C6 - Credible Simulation 


     

    Prof. Dr. Daniel Watzenig  (Virtual Vehicle Resarch GmbH)


    Daniel Watzenig received his M.Sc. degree in Electrical Engineering and the Ph.D. degree in Technical Science from Graz University of Technology, Austria, in 2002 and 2006, respectively. In 2009 he received the Venia Docendi (habilitation) for Electrical Measurement and Signal Processing. Since 2006 he has been Divisional Director and Scientific Head of the Automotive Electronics and Software Department of the Virtual Vehicle Research GmbH in Graz. In 2017 he has been appointed as Full Professor of Autonomous Driving at the Institute of Automation and Control, Graz University of Technology, Austria. He is founder and a team leader of the Autonomous Racing Graz Team, one of currently six teams of the global race series (Roborace). His research interests focus on sense & control of automated vehicles, signal processing, multi-sensor data fusion, uncertainty estimation and quantification, and robust optimization. He is author or co-author of over 200 peer-reviewed papers, book chapters, patents, and articles.


     Training units:  C7 - AV Software


     

    Markus Schratter  (Virtual Vehicle Resarch GmbH)


    Markus Schratter is a researcher in the field of automated driving. He studied Information and Computer Engineering at Graz University of Technology. In 2011, he joined Virtual Vehicle Research GmbH and was involved in different research projects. His main task is the development and integration of concepts into test vehicles. Currently, he writes his PhD thesis with the subject: How technology for highly automated driving can be used to improve active safety systems. In 2019, he joined Autonomous Racing Graz as technical lead and is in the racing team responsible for the architecture of the software stack and the integration of the different subsystems. His research interests are related to automated driving, robotics, sensors and the integration of complex/reliable systems.


     Training units:  C7 - AV Software


     

    Jann-Eve Stavesand (dSpace GmbH)


    Jann-Eve Stavesand heads dSPACE Consulting and supports customers worldwide on defining test strategies for complex E/E systems and on overcoming challenges in model-based development of safety-critical systems. He was involved in the development of ISO 26262:2018 with a focus on software and processes and is currently involved in the standardization of Safety Of The Intended Functionality (SOTIF). Here, too, the focus is on testing and quality assurance of the software and systems used, including the approval and homologation of these complex functions.


     Training units:  D1 - Scenario Test Automation & Validation


     

    Dr. Jens Häcker (Simulation Systems Consulting)


    Jens Haecker studied aerospace engineering and received his Dr.-Ing. degree from the University of Stuttgart in 2006. He joined Daimler AG in general research and advanced engineering and worked in simulation and testing of active chassis and steering systems and functional interfaces for autonomous driving. For the Daimler driving simulator at the Mercedes-Benz Technology Center he was responsible for mechatronics and further development of the motion platform and algorithms and represented Daimler as a member of the scientific committee of the Driving Simulation Association. He is a lecturer for control theory and simulation technologies in mechatronics at the Baden-Wuerttemberg Cooperative State University Stuttgart at Campus Horb. As founder of Simulation Systems Consulting he currently works as an engineering consultant providing services for specification and analysis of simulator systems, with special focus on technical and experimental aspects of human-in-the-loop simulation.


    Training units: D2 and D3 - Driving Simulator Technologies I +II - Experiments / Studies


     

    Carlo van Driesten  (BMW AG)


    Carlo van Driesten graduated from TU München with an M.Sc. in Electrical Engineering and Information Technology. He researched in the field of Radar Clutter Simulation at Rohde & Schwarz for hardware in the loop testing of ship radars before he joined BMW in the field of automated driving in 2016. As Systems Architect for Virtual Test & Validation he is focused on international standardization of simulation interfaces, data structures and open architectures for the purpose of virtually enhanced homologation processes. He initiated the OpenX Simulation Standards at ASAM e.V., authored the initial version of the ASAM Open Simulation Interface (OSI) and is mentor of the ENVITED Research Cluster at asc(s e.V. pursuing the goal of creating decentralized data markets for simulations. In 2018 he co-founded vDL Digital Ventures with StakeNow as the largest German staking service for Tezos which brought his greatest passions together: Automated driving and distributed ledger technologies.


     Training units:  D6 / D7 - Distribited Ledger Technologies


     

    Prof. Dr. Florian Matthes  (Technical University of Munich - TUM)


    Since 2002 Florian Matthes holds the chair for Software Engineering for Business Information Systems at Technische Universität München. The current focus of his work is on blockchain-based system engineering, the semantic analysis of legal texts, and privacy-preserving data and service management. He is co-founder of CoreMedia, infoAsset and Tr8cy, co-founder and chair of Blockchain Bayern e.V. scientifc advisor of Noumena Digital, member of the advisory board of the Ernst Denert-Stiftung für Software Engineering, and initiator and organizer of international conferences and workshops in software and enterprise engineering.


     Training units:  D6 / D7 - Distributed Ledger Technologies

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    Your Contact Person

    Dipl.-Ing. Alexander F. Walser
    Automotive Solution Center for Simulation e.V. 
    +49 711 699 659 - 0
    training@asc-s.de