ADAS Strategic Developments - Vector · PDF fileTooling Overview ADAS - Status & Ongoing...
Transcript of ADAS Strategic Developments - Vector · PDF fileTooling Overview ADAS - Status & Ongoing...
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V0.1 | 2017-07-04
Vector India Conference 2017
Tooling Overview ADAS - Status & Ongoing Developments
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ADAS solution - Efficient development of multisensor applications
Contents of Vector ADAS solution – algorithm prototyping
Rapid prototyping and
Bypassing
High speed ECU (RAM)
measurement
ADAS ECU Data recording
and Road validation
ADAS Algorithm &
software development
Algorithm toolbox / library for sensor data fusion, probabilistic filtering and tracking
Development tool for implementing, debugging and testing multi sensor applications in Visual Studio (C#, C/C++)
vADASdeveloper
Typical user group: Algorithm & function developers
Generic source code generator for complex algorithms
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Development tool for implementing, debugging and testing multi sensor applications
vADASdeveloper - Prototyping environment for Sensor Data Fusion
Automotive network access, cameras, LIDAR etc. for algorithm prototyping in C#/C++/C
Extensible
User-built components
Domain libraries (OpenCV, Simulink DLLs etc.)
Built-in High Performance Recording (CANape engine)
Data replay - offline analysis and debugging
BST (own format), MDF
Custom file types, ADTF
Raw data for sensor re-simulation Integrated into Microsoft Visual Studio - easy offline debugging.
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Fusion Example : 360° Multisensor Application (radar/video fusion)
vADASdeveloper - Prototyping environment for Sensor Data Fusion
8 radars (2 long/2 mid/4 corner), 1 object detecting camera ECU (MobilEye), 2 reference cameras
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Simple display of object overlays in all windows
Interactive configuration
No need for graphics coding
New Visualization Component – Video, Map & Scene views
vADASdeveloper 2.5 – New Features
Video display & GFX object overlay
Perspective display of objects
2D (windows pixel based) status information
Web based map display
OpenStreetMap, HERE, …(tiles)
Vehicle position, street signs, sensor detections…
3D Scene display
Freely configurable view and perspective
Hotkeys for Bird’s Eye, Ego-Vehicle, Driver- and Rear-view
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“Vector Camera Calibration Tool” (CANape 15 & vADASdev 2.0 SP)
Easy “Pixel-to-Vehicle-coordinates” calibration for reference cameras using chessboard
Also supports fish-eye cameras
Working with reference cameras - Automatic Video Calibration Process
vADASdeveloper 2.5 – New Features
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Performance optimized display for complex data and high data rates
Use case: Perception and
LIDAR point cloud display
Built-in drivers for LIDARs and reference systems
Velodyne
IBEO (LUX/HAD)
Upcoming: Quanergy
Working with LIDARs - Scene view & LIDAR drivers
vADASdeveloper 2.5 – New Features
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Object based graphical configuration for object display/overlay
Predefined graphical objects like Cuboid, PointCloud, CircleSector, Text,…
Coordinate systems: Cartesian, Spherical, Geographic, Pixel
Predefined unit conversions: m, km, yd, mile,…
Visualization Component – GFX Configuration
vADASdeveloper 2.5 – New Features
Select Application Data Object (output pin)
Drag & drop data object
Select GFX-Object Type
Bind Application data to GFX-Object properties
VIDEO
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Video: Easy-to-use 3D graphics & LIDAR support
vADASdeveloper 2.5 – New Features
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More sensors – LIDAR, HD maps, V2X
ETH, SomeIP support
Tool coupling and FMI – Simulation environments as data source/data sink
Timesync – Support for PTP / GPS
Outlook Prototyping Environment
vADASdeveloper - Prototyping environment for Sensor Data Fusion
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vADASdeveloper - Prototyping environment for Sensor Data Fusion
Detail: ClosedLoop – MIL (study)
vADASdeveloper
Testcase_1
Testcase_2
…
Testcase_n
Control of virtual scenario
Replay premade scenario, or
Parameterize scenario “template” from test control e.g.
> Object trajectories
> Lighting conditions
> Sensor model parameters (false detections rates, time behavior,..)
Sensor output from virtual scene e.g. radar objects,
Includes sensor error modeling (checking “robustness” of algorithm)
Algorithm result
FMI/FMU
Test Controller
FDX or FMI/FMU
DUT Control by tester
FDX
Dynamic model output
Virtual Scenario Framework
Vehicle dynamics model
Artificial road scene
Baselabs “Models” Real time capable, probabilistic sensor
models
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ADAS solution – ECU Data recording and Road validation
Contents of Vector ADAS solution / Typical Use Cases
Rapid prototyping and
Bypassing
High speed ECU (RAM)
measurement
ADAS ECU Data recording
and Road validation
ADAS Algorithm &
software development
Time synchronized measurement and calibration of ECUs
Graphical object overlay - Video/GPS window - Bird’s eye view
CANape Option „Driver Assistance“
Typical user group: ECU Validation engineers
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Occupancy Grid (New in CANape 15)
ADAS solution – ECU Data recording and Road validation
Use Case
Where are drivable regions?
Typical input to path planning algorithms
Display of static vehicle surrounding in a 2D grid
BirdsEyeView
Perspective display (video overlay)
Acquisition from ECU
Direct - as A2L “Map” via XCP, or
Built-up map in CASL user code from ECU signals
Sensor 1 Result
Visualization
Data Fusion Algorithm
Sensor 2 0 0.2 0.1 0 0 0
0 0.1 0.2 0 0 0
0.2 0 0.3 0 0 0
0 0.4 1 0 0 0
0.1 0.1 0.5 0 0.2 0
0 0 0 0.1 0.1 0
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CANape 15 - Distributed High-Performance Recording for XCP on Eth devices
ADAS solution – ECU Data recording and Road validation
“Distributed High-Performance Recording” on one or more PCs
Time synchronization, start, stop, trigger via Ethernet
Extension with customer specific (raw data) recorders possible
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AD
AS /
HAD
HW
Multicore / Multiprocessor
64bit
Ethernet
SW
AS adaptive / POSIX OS
Dynamic Objects
SOA
TimeSync/TSN
Some challenges ADAS / HAD has for MC tools…
ADAS solution – ECU Data recording and Road validation
IncrBandwidth on physical access / debug ports
XCP has 32+8bit address space
No “Passive listening” on stub line any more
Ever changing semantics on RAM addresses
Must connect actively to ECU data provider service
Tool must know about ECU’s time domain(s)
Memory virtualization by OS
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ADAS solution – ECU Data recording and Road validation
CANape 15 - Distributed High-Performance Recording for XCP on Eth devices
Up to 1 Gbyte/s per recording PC
Scalable
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High End Aurora approach
ADAS solution – High speed ECU (RAM) measurement
Up to 25 Gbit AURORA (was: 6)
5 Gbit (was: 1,8) HSSL2 Cable
VX145x POD
MC Tool
ECU
VX1135 Base Module 2 x 1Gbit (was: 1 x 1)
New Requirement:
Next Gen ESP-ECU: i.e 4 x 6,25 GBit/s
Radar-ECU: Raw Data + XCP
Fusion-ECU: PCIe + IFX Aurora on one POD
CANape
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ADAS solution – High speed ECU (RAM) measurement
2,5 GBit AURORA
2 x 2,5 GBit HSSL Cable
VX1438 POD
VX1135 Base Module
MC Tool
Radar ECU
4 x 400 MBit Raw Data
Radar ECU: Infineon Aurix Setup: XCP-Data + Radar-Raw Data
CANape
CPU0
CPU1
CPU2
1 or 2 x 1 GBit Eth.
Port xxxx: Raw Data
Port yyyy: XCP Data
( incl. Dynamic Address )
2D FFT, Classification, Detections , „Tracks“
Radar Raw Data
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Combined PCIe + IFX Aurora POD approach for Fusion-Controllers
ADAS solution – High speed ECU (RAM) measurement
5 Gbit PCIe
5 GB/s HSSL2 Cable
VX1461 POD
MC Tool
2 x 1 Gbit/s - XCPonEth - XCPonCAN - XCPonFR
CANape
1 x 2,5 Gbit/s Aurora
1 x FR A+B
5 x CAN-FD
VX1135C / VX1135D
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Support for SOA and AS Adaptive ETH / SomeIP
MC on 64bit controllers
Inherit ADAS sensor devices & views from vADASdev
Outlook CANape and Option DA (ADAS topics)
ADAS solution – ECU Data recording and Road validation
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Integrated ADAS development tool chain
Overview ADAS Development Tool Chain
ADAS solution - Efficient development of multisensor applications
Code Generator “Code”
C/C++ Code
CANape / vSignalyzer Offline Data Analysis
Models
Rapid controller prototyping
vADASdeveloper (Fusion) Algorithm prototyping
Data Fusion Library “Create”
vADASdeveloper run ADAS algorithm validation
CANape + Option DA ADAS ECU validation
VX1000 ECU Calibration Hardware
ECU Reprogramming / “Flashing”
Offline algorithm evaluation
PC based sensor fusion prototype
CANape for High Performance Recording
Dynamic models
Other Image Processing
C/C++/…
User Code
Embedded BSW & project work: DCU Architecture, Safety/ISO26262, Function optimization, …
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22 © 2017. Vector Informatik GmbH. All rights reserved. Any distribution or copying is subject to prior written approval by Vector. V0.1 | 2017-07-04
For more information about Vector and our products please visit www.vector.com
Authors: Alexander Aydt Vector Germany