Komplexitätsreduktion und
Beschleunigung:
Das offene Fahrerassistenz-Framework
Dr. Michael Reichel 9. November 2016
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
An ACC Developer‘s World in 2002.
© Elektrobit (EB) 2016
Radar
Target vehicle candidates, their velocity / acceleration
Steering Wheel Angle
Target vehicle selection
Motor Speed Control
Ego vehicle speed control
Head Unit
System activation, status communication
Items to specify: 4.
2
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
A Driverless Car Developer‘s World in 2016.
© Elektrobit (EB) 2016
Radar
Camera
LIDAR
Sonar
Steering Wheel Sensors
Wheel Speeds
IMU / Gyro
Global Position
Maps
Motor Speed Control
Brake Pressure
Steering Angle Control
Regenerative Braking
Static obstacles
Lanes
Moving objects
Vehicle ego motion
Signs
Trajectory planning &
control
Fail-safe / -degraded
mechanisms
Head Unit
Side Tasks
Functional safety
Redundancies
Items to specify: 24.
0
5
10
15
20
25
30
2002 2004 2007 2010 2013 2015
Items to specify
1999: Mercedes S-Class Distronic
2002: VW Phaeton ACC
2005: Mercedes S-Class Distronic plus
2010: Audi A8 GPS-guided ACC
2006: Audi Q7 ACC plus / AEB
2013: Mercedes S-Class Dist.+ / Steering Assistant
2015: Audi Q7 Traffic Jam Assistant
+ brakes + sensor fusion + GPS maps + steering + automatic steering
3
0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
8000000
9000000
1 3 5 7 9 11 13 15 17 19 21 23#
Inte
ract
ion
s
# Components
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
# In
tera
ctio
ns
# Components
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
How Many Interactions Can We Expect For n Components?
© Elektrobit (EB) 2016
𝑛(𝑛 − 1)
2
24 components: 276 interactions
2𝑛−1 − 1 24 components: 8.4 million interactions
Best case: Every specification gets written
or checked only once
Worst case: All specifications must be re-examined
after one is changed
4
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
So What Does Help?
© Elektrobit (EB) 2016
Radar
Camera
LIDAR
Sonar
Steering Angle
Wheel Speeds
IMU / Gyro Global
Position
Maps
Automated Driving
Automated Emergency Brake
Automated Valet Parking
Interactions: 𝒏 ×𝒎 for 𝒏 sensors, 𝒎 functions
5
Sensor Data Fusion
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
So What Does Help?
© Elektrobit (EB) 2016
Radar
Camera
LIDAR
Sonar
Steering Wheel Sensors
Wheel Speeds
IMU/ Gyro
Global Position
Maps
Static obstacles
Lanes
Moving objects
Vehicle ego
motion
Signs
Interactions: 𝒏 +𝒎+ 𝐤 for 𝒏 sensors, 𝒎 functions, 𝒌 abstraction components
Automated Driving
Automated Emergency Brake
Automated Valet Parking
6
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
From Exponentiality to Linearity.
© Elektrobit (EB) 2016
Automated Driving
Automated Emergency Brake
Automated Valet Parking
Sensor Data Fusion: From echos to objects and free space
Motion Management: From brake pressure to trajectory control
HMI Management: From buttons and LEDs to user interactions
Well-defined interfaces
Well-defined interfaces
7
Automated Driving
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Functional Architectures
Can we make complicated behavior even simpler?
© Elektrobit (EB) 2016
Drive in your own lane!
Change lanes if you must!
Don‘t crash! (for heaven‘s sake!)
Come to a safe stop if necessary!
8
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Possible Approach: Behavior-Based Driving
© Elektrobit (EB) 2016 10
Applicability
Desire
Risk
Comfort
HMI Control
Trajectory Plan
Automated Valet Parking
Applicability
Desire
Risk
Comfort
HMI Control
Trajectory Plan
Driving in Own Lane
Applicability
Desire
Risk
Comfort
HMI Control
Trajectory Plan
Automated Lane Change
Applicability
Desire
Risk
Comfort
HMI Control
Trajectory Plan
Automated Emergency Brake
Applicability
Desire
Risk
Comfort
HMI Control
Trajectory Plan
Safe State Handling
Situative Function Arbitration
Behavior Arbitrator
Ruleset for Automated Driving
Ruleset for Manual Driving
Behavior Coordinator
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Architecture Is Key To Managing Complexity.
© Elektrobit (EB) 2016 11
Introducing robinos. Environment modeling and interpretation • vehicle localization in relative and absolute coordinates • environment model – objects, free space, roads, lanes, intersections, signs • interpretation of typical scenarios, recognition of a-typical scenarios
Interfaces for • interoceptive sensors – wheel ticks, steering angle, accelerometers / gyros • „smart“ environment sensors – point clouds, object lists • ADASISv3 for map, SENSORIS for cloud
Extensible function framework • rule-based coordination of functions • clear upgrade path from NCAP to HAD by adding functions • complex behavior emerges from coordinated elementary behavior • guaranteed testability / verifyability
Coordination of vehicle control and HMI • braking, steering, or full trajectory control • safe communication of vehicle state • safe hand-over / take-over management
Interfaces for • kinematic vehicle
components • instrument cluster • infotainment display
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
A Modular Framework for Automated Driving.
© Elektrobit (EB) 2016 12
Veh
icle
Ab
stra
ctio
n -
Sen
sors
Veh
icle
Ab
stra
ctio
n -
Act
uat
ors
Safety and Error Management
Fun
ctio
n S
pec
ific
Vie
ws
HD Positioning
Object Fusion
Grid Fusion
Road and Lane Fusion
Vehicle Database
Sensor
Data Fusion
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
HMI Management
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning
Safety and Error Management
Fun
ctio
n S
pec
ific
Vie
ws
HD Positioning
Object Fusion
Grid Fusion
Road and Lane Fusion
Vehicle Database
Sensor
Data Fusion
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
HMI Management
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning V
ehic
le A
bst
ract
ion
- A
ctu
ato
rs
Veh
icle
Ab
stra
ctio
n -
Sen
sors
Integrated safety concept • system health monitoring and diagnosis • safe-state triggering • options for redundant environment model
and functions (e.g. minimal risk manoeuvers)
Fun
ctio
n S
pe
cifi
c V
iew
s
Ve
hic
le A
bst
ract
ion
- S
en
sors
Ve
hic
le A
bst
ract
ion
- A
ctu
ato
rs
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
Safety and Error Management
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning V
eh
icle
Ab
stra
ctio
n -
Se
nso
rs
Fun
ctio
n S
pe
cifi
c V
iew
s
HD Positioning
Object Fusion
Grid Fusion
Road/Lane Fusion
Vehicle Database
Sensor Data Fusion
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
HMI Management
Ve
hic
le A
bst
ract
ion
- A
ctu
ato
rs
Safety and Error Management
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
robinos Key Concepts: Standardized Interfaces
© Elektrobit (EB) 2016 13
Every software component has • scalable, documented and standardized interfaces to other components • exchangeable interfaces to the base system / OS • a pre-industrialized algorithm core
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Common best practices accelerate testing
© Elektrobit (EB) 2016
Fun
ctio
n S
pe
cifi
c V
iew
s
Ve
hic
le A
bst
ract
ion
- S
en
sors
Ve
hic
le A
bst
ract
ion
- A
ctu
ato
rs
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
Safety and Error Management
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning V
eh
icle
Ab
stra
ctio
n -
Se
nso
rs
Fun
ctio
n S
pe
cifi
c V
iew
s
HD Positioning
Object Fusion
Grid Fusion
Road/Lane Fusion
Vehicle Database
Sensor Data Fusion
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
HMI Management
Ve
hic
le A
bst
ract
ion
- A
ctu
ato
rs
Safety and Error Management
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
robinos Key Concepts: Smart Redundancy
© Elektrobit (EB) 2016
Fun
ctio
n S
pe
cifi
c V
iew
s
Ve
hic
le A
bst
ract
ion
- S
en
sors
Ve
hic
le A
bst
ract
ion
- A
ctu
ato
rs
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
Safety and Error Management
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning V
eh
icle
Ab
stra
ctio
n -
Se
nso
rs
Fun
ctio
n S
pe
cifi
c V
iew
s
HD Positioning
Object Fusion
Grid Fusion
Road/Lane Fusion
Vehicle Database
Sensor Data Fusion
Behavior
Behavior
Behavior
Situative Behavior Arbitration
Situation Analysis
Situation Analysis
Situation Analysis
Path Planning
Path Planning
Path Planning
Trajectory Control
Longitudinal Control
Lateral Control
Motion Management
HMI Management
Ve
hic
le A
bst
ract
ion
- A
ctu
ato
rs
Safety and Error Management
15
HMI Management
HMI Ctrl
Traj. Plan
Object Fusion
Grid Fusion
Time to collision
• Model-based (EKF) • Classified, dynamic objects • ASIL possible
• Model-free (evidence-based) • Dynamic freespace • ASIL possible
Time to collision
Safety Decision
Single point of failure eliminated
configurable sensor mapping
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
A Modular Framework enables you to...
© Elektrobit (EB) 2016 16
Upgrade across models / Upgrade over time
NCAP
HAD
Ensure differentiation, shorten time to market
EB modules 3rd-party modules Your modules
Map onto concrete ECU architecture
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Best Practice Leverage: Project, Product Family, Industry
© Elektrobit (EB) 2016 17
Project-Level Architecture Best Practices: Reduce complexity
€
Product Family Architecture Best Practices: Re-use specified, developed, industrialized and tested components
€€
Industry-Wide Architecture Best Practices Peer review of functionalities, safety and security mechanisms Lower entry into HAD development No vendor lock-in
€€€
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Open robinos and EB robinos
© Elektrobit (EB) 2016
Open robinos
• specifies a reference platform for automated driving up to Level 5 (SAE) • architecture • interfaces • data flow • control mechanisms • software modules • functional safety aspects
• freely available and
licensed as Creative Commons
• Available for download today
EB robinos
• implements the open robinos specification
• provides software modules • for prototyping
in EB Assist ADTF • for rapid embedding
on AUTOSAR / DrivePX • for production
on vehicle ECU
• developed, tested,
verified according to functional safety standards
18
Download the open robinos specification
www.open-robinos.com
working group members welcome!
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Q4/2016 – More EB robinos components
Komplexitätsreduktion und Beschleunigung: Das offene Fahrerassistenz-Framework
Thank you!
© Elektrobit (EB) 2016 21
Industry-Wide Architecture Best Practices Peer review of functionalities, safety and security mechanisms Lower entry into HAD development No vendor lock-in
€€€
www.eb-robinos.com www.try-eb-robinos.com