adas strategic developments - vector · pdf filetooling overview adas - status & ongoing...

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)


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


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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


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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


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


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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


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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)


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


“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…


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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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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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


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)


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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, …

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

http://www.vector.com/

adas strategic developments - vector · pdf filetooling overview adas - status & ongoing...

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