AVL List GmbH (Headquarters)

Public

ADAS & Autonomous DrivingChallenges and AVL Solutions for Development and Testing

Federico FerreroValerio CastelliDr. Bernhard Behr

October 2019

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▪ Accident free driving

▪ Driver relief and comfort functions

▪ Connectivity services

▪ Improved fuel/energy efficiency

▪ Reduced operating cost / new mobility concepts

Market Drivers & Challenges

Challenges

➢ Robust perception, right decision making and failure free actingrequire new, different to conventional development approaches & huge testing efforts

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Areas of ADAS/AD Engineering Services

For new levels of vehicle comfort, safety & efficiency

Key Facts AVL List GmbH: 1.75 bn€ TO 2018, 10.400 employees, 45 Affiliates world wide, Founded 1948, Chairman & CEO: Prof. Dr. h.c. Helmut List Provider of Engineering Services, Instrumentation & Test Systems including Simulation Technologies

System Design

use & test cases, hazard & risk analysis, architecture, sensors,

system safety, benchmark,

target setting

Tailored Controls & SWDevelopment

AD features development from

feasibility, concept to series,

market specific modifications

Calibration Testing

Validationderivative integration,

performance optimization,

testing & validation from lab to proving ground and road

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SOP Application References L2+European Premium OEMs

AVL is a trusted partner in ADAS SOP projects and has long term relationships with OEMs as engineer service provider

Development of longitudinal calibration and validation of various function packages in

all Audi powertrains

Source: Audi.de

ACC , APA, PEA, Speed Limiter

Contribution to development of a number of L0-L2 ADAS features for Jaguar Land Rover’s recent +

current models including next generation features

AVL has agreement from the customers to mention this projects for marketing purpose

LDW, LKA, ISL, BSA, DDM, NextGen

AVL is automotive industry partner for the development and

evaluation of objective ADAS criteria based on

AVL-DRIVETM ADAS

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SOP Reference System DesignEuropean HD Truck OEM

Requirements and SafetyEuropean Truck OEM: • Lane Centering: ~60 use & 90 test cases• Traffic Jam Assist: ~80 use & 120 test cases

Work Content• Use Case Development • Hazard and Risk Assessment (HARA)

based on ISO 26262• Validation Procedure and Worst Case Definition • Validation Test SOP 2019

AVL has best flexibility to design & specify ADAS according OEM preferences due to multiple supplier openness on system architectures & components

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System Design TopicsSystem & requirements engineering, use-& test cases

ADAS/AD system design

▪ E/E & Ctrl. architectures

▪ Use cases / test cases

▪ Hazard & Risk Analysis

▪ Worst Case scenario

▪ Target Setting

Perception

▪ Sensor input

▪ Sensor fusion

▪ Perception

▪ Occupancy grid

Trajectory & decision making

▪ Maneuver planning

▪ Trajectory calculation

▪ Embedded quality evaluation

Control & actuation

▪ Vehicle dynamics models

▪ Long./Lat. vehicle motion controls

▪ Actuators interface

Functional safety

▪ ISO 26262 functional & operational safety requirements

▪ SOTIF – safety of the intendedfunctionality

Connectivity

▪ V2X communication

▪ Back end systems

▪ Data security

Design Validation Plan

▪ Testing and validation strategies for lab & road

▪ Active safety, function & performance KPI

AVL has best flexibility to design & specify ADAS according OEM preferences due to multiple supplier openness on system architectures & components

CONTROLLER

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AVL SW & Functions Development

Customer Value: Development according “White Box” approach provide maximum in-house flexibility and market differentiation potential

AVL in-house generic ADAS controls

3 Types of Projects

▪ Feasibility demonstrations unmanned driving (L4) productivity oriented

▪ Tailored features (L3) as differentiation for an OEM

▪ SW modifications (L0-L2) because of country specifics

Long. Control

Lat. Control

DecisionMaking

ACC/LKA/LCA

ManeuverPlanning

Up to Level 2+

DecisionMaking

VehicleStatus

TrajectoryPlanning

Emergency Status

Level 3,4

Planning and Decision

Perception

Localization

Sensor Fusion

OccupancyGrid

Environment Model

Motion ControlEnvironment Perception

accelerater & braking

Map

cameras

SR/LRradar

Lidar

Ultra-sonic

IMU

V2X

Steering

HMI

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CONNECTED

Predictive Function Examplessmart & intelligent energy management

TRAFFIC LIGHTASSISTENT

PREDICTIVE THERMALMANAGEMENT

PREDICTIVE ADAPTIVE CRUISE CONTROL

ECOROUTING

COASTING ASSISTENTPREDICTIVE SHIFTING

AVL fully supports development and demonstration of new features improving energy efficiency, CO2 & driving attributes

PREDICTIVE HEV ENERGYMANAGMENT

FILTER REGENERATION

PREDICTIVE ADAPTIVE CRUISE CONTROL

Fuel Efficiency @High Level AD: Platooning

System Design

Tailored Controls & SWDevelopment

Calibration Testing

Validation

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ADAS Testing Capabilitiesat AVL HQ

Comprehensive test environment for basic and advanced ADAS + AD features in lab, on XiL and road

Autonomous Driving & Vehicle Development CenterLocation: Graz, Austria

Test Region Styria 500km public roads

Test tracksmultiple proving grounds

RW Fleet testing online OTA assessment

Driver in the loop safe & reproducible lab

Vehicle in the loop AVL DrivingCube

Virtual Environment extensive simulation & cloud

Partner of

AVL offer: Test Execution

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ADAS Performance Calibration & OptimizationSpecial Focus: Human Centric Solutions

AVL USP: Objective measurement technology for perceived safety & comfort feeling Customer Benefit: Market success via end consumers agreement on performance

How want drivers to be driven by automated features?

Scale Safety & Comfort

9-10 very convenient

8-9 convenient

7-8 acceptable

6-7 almost acceptable

5-6 disturbing

4-5 very disturbing

3-4 almost unacceptable

2-3 unacceptable

1-2 fail

AVL-DRIVE ADAS

23different

maneuvers applicable on

L1 to L3 comfort features

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Target Setting Function Performancebased on objective ‘AVL-DRIVE Autonomous’ assessment technology

Scale Safety & Comfort

9-10 very convenient

8-9 convenient

7-8 acceptable

6-7 almost acceptable

5-6 disturbing

4-5 very disturbing

3-4 almost unacceptable

2-3 unacceptable

1-2 fail

1. AVL USP: In-house developed technology for objective assessment of

perceived safety & comfort → criteria catalogue (>30)

2. AVL Benchmark Programcompetitor comparison

→ detailed target diagrams for calibration

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4

5

6

7

8

9

10

2012 2013 2014 2015 2016 2017 2018 2019

TO

TA

L R

AT

IN

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ADAS PERFORMANCE

AVL Benchmark Database 2012-2018

base for targets setting

• ACC▪ LKA

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ADAS/AD Real World TestingAVL Fleet Monitoring Technology

Automated logging and evaluation

of geotagged fleet data

AVLApproach

ServiceOffering

Execution of real world testing includingcomprehensive fleet test analysis

WhyImmense amount of testing &estimation of scenario coverage Demand: time saving approaches & scenariocollection with assessment

Com ModulCom ModulCom Modul

Com Modul

Com Modul

AVL-DRIVE

Queue

- Ring FiFo- Setup

MQTT Client

Kafka Client

… Client

Manipulator

- Filter- Encryption- Manipulation

Output Client

- Settings- Monitoring

ZMQ Client

x Client

Input Client

- Settings- Monitoring

- File- DB- MQTT Client- Kafka Client

- ZMQ Client- UI- …

Live UI

- Live- Replay- …

Fleet DB

Fleet HW concept

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Highlights ADAS/AD Real World Testing

Geo-tagged view of areas with POI markers

Statistics: fleet utilization, road types, mileage, events distribution…

Country specific identification of significant places

Maneuver Distribution Statistics

Road segment coverages

HighwaysLocal roadsMain roadsMinor roadsMotorwaysPedestrian roadsRegional roadsWalkways

TunnelsBridges

Rating below thresholds (target fulfillment)Identification of geo-areas of interest (POI)

Over the air transmission of result parameters

Test routes optimization

Automated logging and evaluation

of fleet data

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Comprehensive Proving Ground Testing

Comprehensive test environment for real world & proving ground testingenables complete testing + validation packages

AVL function & performance testing on proving ground in smart city area (HU)

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Safe & Reproducible Lab Testing with Driver Simulator on Hexapod

ADAS Testing and Validation on Driver Simulator

Location: Graz

Examples of parameter variations• speed of ego vehicle• speed of motor biker• distance to side lane / mid lane• payload of vehicle • …

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How are Automated Driving Functions Tested TODAY

OEMs mainly rely on office simulation for development and in-vehicle testing for validation

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A Seamless and Open Tool Chain with New Approaches is Necessary

Simulation

Same Results

Virtual TESTING Proving Ground Real World

Scenario, Maneuver, Test Case Abstraction incl. KPIs

Environment Abstraction

Vehicle Abstraction

The most efficient validation will be done by those who will use the best combination…

Required Elements:

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Proving Ground and Real World

Finalize and Confirm

Virtual TESTING:

Integrate, Analyze and Improve

Simulation:

Scale Testing of Variants (Vehicle Configurations and Scenarios)

Insights: Approach for The Best Combination…

reproduce

analyze

Optimize/Improve

+ specific test cases which cannot be done in simulation

+ specific test cases which cannot be done in simulation and/or virtual testing

Simulation Virtual Testing Proving Ground

Real World

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Scenarios – Core of ADAS Development & Validation

Most scenario cases are uninteresting…

… and some can become very interesting

Examples:

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Scenarios

Models

KPIs

Test Sequence Generator

Test Case Preparation

Scenario Preparation

Scenarios to test requirements

(DVPs)

Synthetic random scenarios

Scenarios from road data

Specific

(Sensor) Model

Model Preparation

(Sensor) Model

Editor

(Sensor) Model

Parametrization

Generic

(Sensor) Model

Test Systems

• Sensor testbeds• Powertrain

testbeds• Vehicle

dynamics testbeds

Integration of

reference simulation

environment

Test Execution

MIL/SIL

Model.CONNECT™

VIL (Driv.CubeTM)

Signals, Object lists, Streams (Video, 3D, ..)

Public Road

Testing using

reference DAQ

Cloud MIL/SILHIL Platform (Driving

Simulator)Private Test-Track

Model.CONNECT™

Testbed.CONNECT™

KPI Preparation

Data

Management

Online / Offline Evaluation &

Postprocessing

Data Management

Scenarios

AVL Scenario-Based ADAS/AD V&V Tool Chain

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Dynamic Ground Truth roof box:

Where we are working on …Dynamic Ground Truth System

Lidar reflections from road objects (e.g. vehicles

Extracted (Tagged)Scenarios fromRoad drives:

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ScenarioDatabase

Test the relevant / critical scenarios!

AVL Test Case Generator

Query scenario information

Scenario Preparation

Scenarios to test requirements

(DVPs)

Synthetic random scenarios

Scenarios from road data

Scenario generation

Where we are working on …Test Case Generation Methods

Test s

equence

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Where we are working on …Target: Extract the Relevant Cases

288.000.000 km to test>99% nothing happens

Identify relevant cases and transfer to testbed

Cut-In → Cut-Out

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Where we are working on …Vehicle in the Loop Testing

Steering Module:

Radar Stimulator:

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Where we are working on …Euro-NCAP Evaluation Package

Euro-NCAP Data Processing Package:

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Where we are working on …ADAS Parameter Mgt with CRETA

Project Coordinator

Software Team

Datasets

Simulation in LAB

Neural Network optimisation

Parameterisation in the car

Make sure that the correct parameters end up in the correct vehicle and

controller!

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Some Partnerships

Further joint activities:

AVL-TNO Cooperation: Integration of TNO scenario database for Test Planning and MIL/SIL Validation:

…

AVL-NORCOM Cooperation: Integration of NorCom BigData Platform into AVL Big Data Analytics solution:

AVL Stähle Cooperation:Development of a steering actuator for ADAS testing on Chassis dyno testbeds:

AVL-TÜV-NVIDIA Cooperation: Virtual homologation of piloted highway driving using NVIDIA DRIVE SIM and NVIDIA DRIVE PX:

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Calibration, Testing& Validation• Features integration e.g. derivatives • Full capability testing & validation

real world, proving ground and virtual• Calibration of ADAS features with

perceived safety & comfort optimization

Control & SW Development • Proof-of-concept new features• Customer specific ADAS & AD features development from concept to series

• Predictive & connected energy management features improving fuel consumption

System Design • Use & test cases definitions • HARA – hazard & risk assessment

with functional safety concept• Controller architecture, sensor layout• Benchmarking & targets setting

USP, Strengths• Proven series production experience

and references• In-house SW & controls development • ADAS performance technology for

human perception optimization

Summary ADAS/AD Engineering Offerings

Engineering solutions for series (L0-L3) & adv. development (L3+), applicable at PC & CV

PC: passenger cars / CV: commercial vehicles