1050: 車載用adas/自動運転プラットフォームdrive...

シニア・ソリューションアーキテクト馬路徹, 2015年9月18日

車載用ADAS/自動運転プラットフォームDRIVE PX

及びコックピト・プラットフォームDRIVE CXのご紹介

2

Agenda

Autonomous Driving System Architecture and DRIVE PX/CX Implementations

DRIVE PX for Map Module, AI Module and Computer Vision

DRIVE CX for HMI Module

Summary

3

Autonomous Driving System ArchitectureTypical Architecture

地図モジュール- 固定道路地図- ローカルダイナミックマップ

- 目標走行軌跡生成

速度制御モジュール- Adaptive Cruise Control- Pre-Crush System

エンジン・ブレーキ

操舵制御モジュール（車線維持制御）

ハンドル

HMI モジュール-手動、自動切換え操作システム- 稼動状況表示

ビッグデータ、道路・交通情報等（車外データ）

走行環境センシングおよび障害物認識- 前方の障害物センシング（ミリ波レーダ、レーザレーダ、カメラ）- レーンマーカセンシング

測位GPS

参考文献：「自動運転システム構成と要素技術」、保坂明夫、青木啓二、津川定之森北出版、2015年7月Reference: “Automated Driving System and Technologies”, Akio Hosaka et al, Morikita Publishing Co., Ltd., July 2015

人工知能モジュール- 環境理解- 判断- 目標走行軌跡修正

修正指示

修正指示

道路地図交通情報等

道路線形

障害物位置等

車間距離

白線距離

4

Autonomous Driving System ArchitectureTypical Architecture

MAP MODULE- Road Map

- Local Dynamic Map

- Target Path Generation

SPEED CONTROL

MODULE- Adaptive Cruise Control

- Pre-Crush System

Engine, Break

STEERING CONTROL

MODULE- Lane Keep Control

Steering

HMI MODULE- Auto/Manual Mode SW

Operation

- System Operation Status

Big Data, Road, Traffic Information etc

Driving Environment Sensing and Obstacle Recognition- Front Obstacles Sensing (Mili-wave Radar, Laser Radar, Camera)

- Lane Marker Sensing

Position

Sensing

GPS

AI MODULE- Environment Recognition

- Decision Making

- Target Path Tuning

AdjustingAcceleration

Adjusting Direction

Road MapTraffic Information

Road Structure

ObstacleLocation

CarDistance

Lane Distance


5

Autonomous Driving System ArchitectureMAP MODULE implementation by DRIVE PX/CUDA

SPEED CONTROL


- Pre-Crush System

Engine, Break

STEERING CONTROL


Steering


Operation





Position

Sensing

GPS


- Decision Making



Adjusting Direction


Road Structure

ObstacleLocation

CarDistance

Lane Distance

DRIVE PX / CUDA


- Local Dynamic Map



6

Autonomous Driving System Architecture+ AI MODULE implementation by DRIVE PX/DL

SPEED CONTROL


- Pre-Crush System

Engine, Break

STEERING CONTROL


Steering


Operation





Position

Sensing

GPSAdjusting Direction


Road Structure

ObstacleLocation

CarDistance

Lane Distance

DRIVE PX / CUDA DRIVE PX / DL


- Local Dynamic Map



- Decision Making




7

Autonomous Driving System Architecture+ HMI MODULE Implementation by DRIVE CX/HMI

SPEED CONTROL


- Pre-Crush System

Engine, Break

STEERING CONTROL


Steering




Position

Sensing



Road Structure

ObstacleLocation

CarDistance

Lane Distance


DRIVE CX/HMI


- Local Dynamic Map



- Decision Making



Operation

- System Operation

Status



8

Autonomous Driving System Architecture+ Computer Vision Processing by DRIVE PX/DL & CV -> Almost All Processings by Tegra

SPEED CONTROL


- Pre-Crush System

Engine, Break

STEERING CONTROL


Steering


Position

Sensing



Road Structure

ObstacleLocation

CarDistance

Lane Distance


DRIVE CX/HMI


- Local Dynamic Map



- Decision Making



Operation

- System Operation

Status

Computer VisionDeep Learning

VisionWorks

DRIVE PX / DL & CV



10

Audi zFAS Example as a Low-Speed Autonomous Driving: Obstacle Recognition, Target Path Generation by one Tegar K1

From GTC2015

11

Deep Learning Revolutionize Computer Vision

CONVENTIONAL

DEEP NEURAL NETWORK

(…)

Required Separate Algorithms/Apps- Pedestrian: HOG etc- Traffic Sign: Hough Transform + Character Recog. etc

Only simple context recognition- Pedestrian Y/N Only (no additional info)- Speed Limit Signs Only

One Deep Neural Net App can Detect various Objects- Pedestrian, Cars, Traffic Signs, lanes- Also with many attributes (Car: Police Car, Van, Sedan, Truck, Ambulance….)

12

TEGRA X1 CLASSIFICATION Performance

AlexNet

0

10

20

30

40

50

60

70

80

90

100

Tegra K1 Tegra X1

IMAG

ES /

SECO

ND

14

Growing Performance of Automotive Tegra Products will allow further Integration in the Future

Tegra 2 Tegra 3

Tegra 4

Tegra K1

0

200

400

600

800

1000

1200

GFLO

PS

FP16/INT16

Core i7

Tegra X1

CPU

GPUGPU

CPU

Tegra X1 (FP16)

Note: 4790K Core i7, CPU @ 4GHz, GPU @ 350 MHz

TIME

15

DRIVE PX For Map Module, AI Module and Computer Vision

16

DRIVE PX

An advanced computing platform based on NVIDIA Tegra processors for autonomous driving cars

FEATURES

The ability to capture and process multiple HD camera and sensor inputs

A rich middleware for computer graphics, computer vision and deep learning

A powerful and easy to develop platform for algorithm research and rapid prototyping

NVIDIA CONFIDENTIAL — DRIVE PX DEVELOPMENT PLATFORM Preliminary information — Subject to change

17Proprietary & Confidential

All Information Subject to Change

DRIVE PX Camera & Display Interfaces

Group A Group B Group C

12 simultaneous LVDS camera inputs

• All cameras synchronized within each Group (3 groups)

2 LVDS display ports

Display

18

Other Interfaces to AurixCAN*, LIN*, FlexRay* and Ethernet

48-pin Automotive Grade

Vehicle Harness

CAN 2.0 (x6)

FlexRay (x2)

LIN (x4)

UART (x1)

Ethernet (x1)

1x Power

19

Hardware Specs PROCESSORS

Dual Tegra X1 VCM; each VCM consists of:

Tegra X1 processor

DRAM: 4GB

NOR FLASH: 64MB

eMMC: 64GB

Inter-Tegra X1 VCM Communication

SPI and USB 3.0 for direct inter-Tegra communication and through Ethernet Switch

ASIL-D MCU

Camera and IO controls through ASIL-D MCU.


20

Hardware Specs PERIPHERALS

Sensors:

Vision Sensors interface:

12x LVDS Cameras

Sensor Interfaces for Radar, LIDAR, Vehicle Dynamics etc.:

CAN 2.0; LIN; Ethernet; Flexray

Displays:

LVDS interface (x2)

Power Management of ECU:

System power monitor/control — ASIL-D MCU


21

DRIVE PX software specs

OS: NVIDIA Vibrante Linux 4.064-bit Kernel Linux, Quickboot, AutoSAR RunTimeEnvironment

Graphics: Open GL ES 3.1

Development Tools/Samples: Delivered through Jetpack 2.x

Graphics debugger, PerfKit, DNN Classifier Sample, Vision Works 1.0 (beta) Computer Vision libraries and Samples

ASIL MCU Support for CAN, Ethernet, Flexray and LIN; AutoSAR framework

External Storage for Video RecordingUSB3.0 interface for camera output in RAW or H.265/H.264 encoded formats

Camera: NVMedia and Driver support for LVDS camera

Open Source Collaboration initiatives/Compliance:

Yocto 1.8Genivi7 Compliant


22

WORLD CLASS SOFTWARE TOOLSFaster debug and analysis reduces development costs

Preliminary information — Subject to change

TEGRA GRAPHICS DEBUGGER

Visualize GPU performance metrics

Automated analysis of GPU bottlenecks

PERFKIT

Performance monitoring

Automated bottleneck analysis

ECLIPSE IDE

Standard Linux development environment

23

DRIVE PX LINUX SOFTWARE STACK

Preliminary information — Subject to change

Imaging (Camera) Pipeline

Linux

Performance Microprocessor A

Graphics/ComputeNVMedia

CUDA/EGL/Open GL ES

Tegra™ X1 Hardware (ARM, GPU & SoC Peripherals) Safety MCU

Safety MCU

MCA

L

Applications

T1/OEM SW OS/3rd SW/HW NVIDIA Licensed SW Drive PX HardwareElektrobit

AUTOSAR BSW on Linux

Linux

Performance Microprocessor B

Tegra™ X1 Hardware (ARM, GPU & SoC Peripherals)

AUTOSAR BSW on Linux

ApplicationsApplications

Linux BSP/Drivers

Filesystem(s)

Linux BSP/Drivers

Graphics/Compute

CV/DL Libraries

Imaging (Camera) Pipeline

Graphics/Compute NVMedia

CUDA/EGL/Open GL ES

Filesystem(s)

Graphics/Compute

CV/DL Libraries

AUTOSAR

on

Safety

MCU

24

DRIVE CXFor HMI MODULE

25NVIDIA CONFIDENTIAL

THE SOUL OF

NVIDIA DRIVE™ CXDIGITAL COCKPIT CAR COMPUTER

Natural Speech

OTA updates

Advanced Visuals

Hypervisor – Cluster Cockpit

26

DRIVE CXTODAY

ADVANCED VISUALS – Digital CLUSTER

27

DRIVE CX ADASAlso supported by DRIVE PX

Best-in-Class

Surround View

28

NVIDIA DRIVE Design

Design StudioProfessional artist environment

Design ArchitectIntegrated engineeringenvironment

NVIDIA’s HMI Platform version 8.0

29

Today(no internet connection)

Google(with Internet Connection)

DRIVE CX(no internet connection)

ACCURACY LOW1M parameters

HIGH30M parameters

HIGH30M parameters

VOCABULARY SMALL50k words

LARGE4M words

LARGE4M words

SPEED SLOW500+ ms latency

FAST

… or no response

(lost internet

connection)

FAST

… always

Fail-safe NATURAL LANGUAGE SPEECH

30

SUMMARY

1. Autonomous Driving System Architecture consists of Sensing Module, Map Module, AI Module and HMI Module. DRIVE PX and CX can implement all functions with CUDA, Deep Learning , Computer Vision and HMI Frameworks.

2. DRIVE PX consists of two powerful Tegra X1 processors with the total performance of 2.3TFLOPS. It comes with a rich middleware for GPU Computing, Deep Learning and Computer Vision.

3. DRIVE CX powerful Tegra X1 processor enables the fail-safe Natural Speech Recognition, advanced visual quality which offers a safe, versatile and high-quality HMI. This is essential for the critical human-car interaction in the Autonomous Driving Cars.

4. Today, we might start with a few DRIVE PX and a DRIVE CX. However, the continuous performance and feature enhancement in the future will make it possible to implement the total system by a single DRIVE platform if required.

THANK YOU

1050: 車載用adas/自動運転プラットフォームdrive...

Technology