Demands on Radar for autonomous driving ...

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Development needs on Radar for Autonomous Driving. Dr. Juergen Dickmann. Manager Radar,. Vehicle Automation. DAIMLER AG, Ulm, Germany. Intl. Radar ...
Development needs on Radar for Autonomous Driving

Dr. Juergen Dickmann Manager Radar, Vehicle Automation DAIMLER AG, Ulm, Germany

Intl. Radar Conference Philadelphia, 2016-05-05

Bertha-Tour 2013: The vision of autonomous driving became real

Dr. Juergen Dickmann

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Bertha-Tour 2013: Bertha vehicle appeared like a real S-Class

Dr. Juergen Dickmann

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Bertha-Tour-2013: … and Radar has been intensively used as the backbone 8x Radar LR-Radar

SR-Radar SR-Radar

LR-Radar

LR-Radar SR-Radar SR-Radar

LR-Radar

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Challenges for autonomous driving on Radar Precise Detection and simultanious Representation of static and dynamic world

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Automotive Radar Future More anticipatory perception information : High Definition Radar Perception

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Automotive Radar Future Localization Input: Radar based landmarcs

Dr. Juergen Dickmann

@ K. Werber, EUMC 008, EUMW2014

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Interpretation of the environment. Interpretation of the environment.

Parkingrow Parkinglot

???

Obstacle

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Automotive Radar Future Interpretation accelarater : Deep Learning and CNN

Deep Learning Structure

car Dr. Juergen Dickmann

Dr.

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Deep Learning for Cognitive Radar Grid-Maps PKW

PKW Bush

PKW

Pol e

PKW

PKW F e n c e PKW

PKW pol e PKW

PKW Bush Pfos ten

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Requirements for Radar driven by higher automation Step 2

Step 3

Step 4

Assistance

Partially automated

Highly automated

Fully automated

Driver as supervisor in automated driving tasks

System monitors it´s limits and hands over to driver if reached.

Driver System manages every task

Driver acts In critical situations emergency systems intervene

No parallel activity

Detection and Ranging

line of demarcation

Step 1

Ltd. parallel activity

Parallel activity or driverless operation possible

Imaging an Understanding

QM/ASIL-A, Blinddetection

ASIL-A/B, State awareness

Interoperable

Interoperable, unaff. by mitigation

Dr. Juergen Dickmann

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High Resolution = Imaging Radar R

A/D Time signals

FFT Range Representation R

(Amplitud vs Distance)

ϕ Vrel

FFT Range-Velocity-Representation v

(Amplitude vs. Range vs. Velocity

FFT Radar Image φ Dr. Juergen Dickmann

(Amplitude vs Range, Velocity and azimuth -angle) 12

Radar on Chip?

Flexibility

It depends on the fusion level RF-FE and DSP-FE undergo fast request changes, esp. on digital side.

Just in time available

Clock-Speed of RF/digital paths in line to meet high performance and Vehicle-SOP?

Cost

Volume rise for high performance sensors strong enough?

Dr. Juergen Dickmann

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More calculation power?

Yes, please!!!

ESR/DBF

Provides the physical basic input data in 3D!!!! to “Knowing your neighborhood”

High Res. Algorithms

Allows to get as many as possible precise detection per target as prerequisite input for understanding/perception stage

Machine Understanding

Highly sophisticated , huge data basis req. algorithm concepts as success factor

Dr. Juergen Dickmann

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Scalabilty of Radar Archtecture?

Yes, please!!!

Up-Grade to high performance

Allow for innovations like highly automated driving, which needs the ultimate performance

Up-Grade to Baseline ADAS

Basis for standard ADAS functions like ACC, Emergency Braking, Pre-Crash etc.

Modular&Scalable, Basis for all Tier 1

Basis module that fits to strd. Requirements for serial functions (NCAP, CPA etc.)

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More than 15 years of field (Product) experience, and now “Radar is in all platforms at DAIMLER”

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Summary Automotive Radar Future needs High Resolution Multimodale and Smart Radars

See al so: https://www.researchgate.net/profile/Juergen_Di ckm ann

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