Physics Based Sensor simulation - NVIDIAon-demand.gputechconf.com/gtc-eu/...simulation...automotive-industry.pdf · Physics Based Sensor simulation ... Siemens offers solutions across

Physics Based Sensor simulationJordan Gorrochotegui - Product Manager Software and Services

Mike Phillips – Software Engineer

Realize innovation.Restricted © Siemens AG 2017

Siemens offers solutions across all automotive mega trends

Autonomous Vehicles Electrified Vehicles Mobility

Engineering the next product not just the best product for the future

Connected Vehicles

12

3

45

6

7

Smart fleets & multi-modal

transport

Autonomous driving &

driver assist systemsElectric vehicles &

supporting technology

Connecting car, driver and

infrastructure

Restricted © Siemens AG 2018

2018.MM.DDPage 3 Siemens PLM Software

Real world

Vehicle under development

Validation and Verification framework for AVs

MiL / SiL / Cluster

HiL / DiL / ViL

Proving ground / field test

V&V environments

Digital Twin

“World”

Digital Twin

“Vehicle”

Design adaptations

(HW/SW)

1M – 10M scenariosRequirements

Multiple variants

Certification -

Homologation

Simulation definition

Requirements &

system architectures

10 – 100 scenarios

1k – 10k scenarios

http://www.google.nl/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=qJzh71hkI4YzkM&tbnid=mCyJQKuxLZ2WQM:&ved=0CAUQjRw&url=http://www.autoweeklive.nl/informatie/&ei=hVtMU6f0H4jCPMiOgMgN&bvm=bv.64542518,d.ZWU&psig=AFQjCNEiAmfct_cLKttz4WFcygUFWDmmJw&ust=1397599429680038




Real world

Vehicle under development

Validation and Verification framework for AVs

MiL / SiL / Cluster

HiL / DiL / ViL

Proving ground / field test

V&V environments



Design adaptations

(HW/SW)

1M – 10M scenariosRequirements

Multiple variants

Certification -

Homologation

Simulation definition

Requirements &

system architectures

Digital Twin

“World”

Digital Twin

“Vehicle”





Example #1: MiL / SiL / Cluster

• Design space exploration using large scenario databases

• Virtual development, verification and robustness testing

• Optimized automated vehicle designs

V&V Environments

Laboratories / proving grounds / public roads



HiL / DiL / ViL

MiL / SiL / ClusterRun massive amounts of Prescan scenarios for

Automated Vehicle development and optimization





V&V Environments




HiL / DiL / ViL

MiL / SiL / Cluster

Example #2: HiL testing of central AD processing unit

• Training and evaluating Deep Neural Networks (DNNs)

• Virtual validation of automated driving processing units

• Accelerated automated vehicle development

PreScan synthetic sensor data injection for virtual validation of central AD processing units

Automated Driving processing unit

Automated Driving system validation






Free space detection on Nvidia Drive PX2




Object detection on Mentor DRS360



V&V Environments




HiL / DiL / ViL

MiL / SiL / Cluster

PreScan – HIL application examples





V&V Environments




HiL / DiL / ViL

MiL / SiL / Cluster

Example #3: Automated Driving physical validation

• Physical verification & validation services

• Certification of automated and connected systems

• Design consultancy for “next-generation” AD test facilities

TASS International Services and Siemens Testing Solutions for physical validation of automated and

connected driving technology





Development of automated vehicles requires realistic sensor data

DNN TrainingSensor developmentAlgorithm development Validation



? Realistic data

+ Inexpensive

+ Fast to acquire

+ Perfect repeatability

+ Physical sensor not needed

+ Annotation is free

+ Can be closed loop

+ Real data

- Expensive

- Time consuming

- Not (easily) repeatable

- Requires a physical sensor

- Must be annotated

- Open loop (recorded)

Two sources of sensor data

Recorded Simulated



Camera

&

Ground Truth

Radar

&

V2X

Lidar

&

Point Cloud



We use simulation to compute real world effects on actual sensors

Output verified & validatedRaw signal is computedPhysical artefacts are

faithfully reproduced

• Distortions

• Multi-bounce

• Time effects

• Weather

• …

• Lidar full-waveform signal

• Radar channel response

• Raw camera images

• …

• Verify against real sensors

• Validate for specific use cases



Physical Device World

Simulation Engine

Beam cross

sectionMTF

Color filter

array

Three key components are needed



Physics Based Lidar Simulation


2018.MM.DDPage 17 Siemens PLM SoftwareEnsuring digital continuity, multi-domain traceability and functional safety of autonomous systems

Our solutions support autonomous vehicle development needsAcross all engineering domains

Documents

Physics Based Sensor simulation - NVIDIAon-demand.gputechconf.com/gtc-eu/...simulation...automotive-industry.pdf · Physics Based Sensor simulation ... Siemens offers solutions across