ROSCon 2015
Hamburg, Germany

AUTOMATED DRIVING WITH ROS AT BMW.
MICHAEL AEBERHARD, THOMAS KÜHBECK, BERNHARD SEIDL, MARTIN FRIEDL,JULIAN THOMAS, OLIVER SCHEICKL.

HISTORY OF AUTOMATED DRIVING AT BMW.

BMW Track Trainer(2006).

Emergency stop assistant(2009).

Highly automated driving on themotorway (2011 / 2015)

Automated driving on the vehicle‘slimit (2014).

Fully automated remote valet
parking (2015).

360° collision avoidance(2015).

Aeberhard et al., “Experience, Results and Lessons Learned from Automated Driving on Germany‘s Highways“, IEEEIntelligent Transportation Systems Magazine, pp. 42-57, Spring 2015.

ADAPTIVE – EU RESEARCH PROJECT.

 BMW is partner in the EU research
project AdaptIVe.

 January 2014 – June 2017, €25
Million budget, 30 partners, 8countries.
 Goal is the widespread applicationof automated driving to improve
traffic safety, efficiency andcomfort.
 BMW prototype will demonstrateurban (partial automation) andhighway (conditional automation)
automated driving functions.
For more information, visit https://www.adaptive-ip.eu/.
Michael Aeberhard, BMW Group Research and TechnologyPage 3

ADAS VEHICLE FUNCTIONAL ARCHITECTURE.

SENSORSENVIRONMENT MODELADAS FUNCTIONS

Representations and Fusion

Maneuver PlanningRoad Model and Localization

Trajectory Planning

VEH CONTROL

RadarCameras

HMISituation Interpretation

State Machine

Laser scanner

Driving strategy
Michael Aeberhard, BMW Group Research and Technology

Page 4

GEN2 RESEARCH PROTOTYPE.
BMW 335I GT.

Michael Aeberhard, BMW Group Research and Technology

Page 5SENSOR SETUP IN GEN2 RESEARCH PROTOTYPE.

Michael Aeberhard, BMW Group Research and Technology

Page 6

HARDWARE ARCHITECTURE.

Michael Aeberhard, BMW Group Research and Technology

Page 7

CHOOSING A FRAMEWORK.

MicroFramework
BMW Group Research and Technology

1 BMW internally developed
Framework for prototyping ADAS.
 Shared memory transportmechanism.
 Synchronized execution of softwaremodules.
 Internal development
limited/complex.

EB Assist ADTF
Elektrobit Automtive2

 Commercial product popular within
the automotive industry(OEMs/Suppliers).
 Readily available toolboxes tohardware used in the automotiveindustry.
 Easy to use GUI for manipulating
various features and configuration asystem.
https://www.elektrobit.com/products/eb-assist/adtf/

ROS
Open Source Robotics Foundation

 Popular open source robotics
framework.
 Reliable distributed architecture.
 Wide use in the robotics researchcommunity.
 Huge selection of “off-the-shelf”
software packages for
hardware/algorithms/etc.

3

CHOOSING A FRAMEWORK.

MicroFramework
BMW Group Research and Technology

1

EB Assist ADTF
Elektrobit Automtive

2

ROS
Open Source Robotics Foundation

Why we ended up choosing ROS for the BMW research department: Autonomous driving benefits from robotics research and ROS has been
become very popular in the robotics community.
 Stability and reliability from a very large user-base.
 Quick tests and integration of already-available algorithms and software BMW internallydeveloped saves development
 Commercial
product popular within
 Popular open source robotics
packagestime.

Framework for prototyping ADAS.
the automotive industry
middleware.
Opensource.
 Shared memory transport(OEMs/Suppliers).
 Reliable distributed architecture.
mechanism.
Readily available toolboxes to Wide use in the robotics research Easier cooperation with universities
and other research institutes.
 Synchronized execution of software
hardware used in the automotivecommunity.
modules.  Gain experience at BMW industry.
 Hugeselection of “off-the-shelf”
with using ROS and learn about its
advantages
 Internal development
 Easyto
to otheruse GUIsolutions
for manipulating
software packages
for/disadvantages with respect research department
shouldlimited/complex.
various features and configuration a
hardware/algorithms/etc.
try something new!
system.
https://www.elektrobit.com/products/eb-assist/adtf/

3

ROS ARCHITECTURE.

ADAS Algorithms/sensor_data/vehicle_data/trajectory/hmi_data
Situation Interpretation

ros2ethernet

Ethernet Data

ethernet2ros

Environment Model andSensor FusionEthernet Data

Planning

Michael Aeberhard, BMW Group Research and Technology

Page 12ROS ARCHITECTURE.
With the simulator:

Michael Aeberhard, BMW Group Research and Technology/trajectory/hmi_data
Situation Interpretation

Planning

Ethernet Data

BMW Simulator Software

Ethernet Data/sensor_data/vehicle_data

ros2simulator

Environment Model andSensor Fusion
simulator2ros

BMW Simulator Software

ADAS Algorithms

Page 13

ROS ARCHITECTURE.
In the research vehicle:

Michael Aeberhard, BMW Group Research and Technology/trajectory/hmi_data
Situation Interpretation

Ethernet Data

MicroAutobox II

Ethernet Data/sensor_data/vehicle_dataros2autobox

Environment Model andSensor Fusion
gateway2ros
hardware2ros

Gateway or sensor hardware

ADAS Algorithms

PlanningPage 14

USING MATLAB/SIMULINK WITH ROS.
 MathWorks released the Robotics System Toolbox this year for ROS
integration with Matlab/Simulink.

 Easily read and analzye data from ROS Bags  useful for evaluating
the system.
 Some of our software is implemented as a Simulink model.
 Use the Toolbox to easily integrated this software into the ROS
eco-system:

http://www.mathworks.com/products/robotics/
Michael Aeberhard, BMW Group Research and Technology

Page 15

VIDEO – LASERSCANNER.

Michael Aeberhard, BMW Group Research and Technology

Page 16

VIDEO – GRIDS.

Michael Aeberhard, BMW Group Research and Technology

Page 17

VIDEO – OBJECTS AND LANE MARKINGS.

Michael Aeberhard, BMW Group Research and Technology

Page 18

VIDEO – LOCALIZATION.

Michael Aeberhard, BMW Group Research and Technology

Page 19

VIDEO – ENVIRONMENT MODEL.

Michael Aeberhard, BMW Group Research and Technology

Page 20

VIDEO – TRAJECTORY PLANNING.

Michael Aeberhard, BMW Group Research and Technology

Page 21

VIDEO – AUTOMATED DRIVING FUNCTION.

Michael Aeberhard, BMW Group Research and Technology

Page 22DEVELOPED TOOLS.
 Several RQT Plug-Ins for various purposes:
 Plug-Ins with specific functionality,for example simulating input and/oroutput for testing.
 Improved Bag Record/Play Plug-In(rosparam dump/load, extra
meta-data, map view, etc.).
 Lots of RViz Plug-Ins for visualizing our interfaces.
 Avoid using markers to reduce traffic.
 More flexibility with Ogre API.
 Integration of selection mechanism for displaying object-specific data.
Michael Aeberhard, BMW Group Research and TechnologyPage 23

WHAT WE LIKE ABOUT ROS.
 Reliability and stability.
 Minimalism of a basic ROS node.
 Distributed architecture.
 ROS Message concept.

 “Off-the-shelf” tools such as RViz, RQT, Bag, diagnostics, etc.
 Future potential (ROS 2, ROS Industiral, new tools, etc.).
 Lots of software packages to try out!

Michael Aeberhard, BMW Group Research and Technology

Page 24

THERE IS STILL A LOT OF POTENTIAL.
 More options in the message transport mechanisms.
 ROS 2 with DDS could be a huge improvement.

 GPU transport in order to minimize GPU  CPU data transfers.
 Easier ROS Message migration / compatibility (MD5 Checksum on .msg file maybe not thebest solution?).
 Continue to improve the already very useful tools.
 RViz – plug-ins, labeling framework.
 RQT – Topic Monitor, Plot, Bag, etc.
 Node Manager GUI (something similar to node_manager_fkie).
 Easy configuration management for different robots (currently a hodge-podge of launch files
for different vehicles).
 Compliance to industry standards for software (ISO, AUTOSAR, etc.).
Michael Aeberhard, BMW Group Research and TechnologyPage 25

THANK YOU FOR YOUR ATTENTION.
Contact: michael.aeberhard@bmw.de

Michael Aeberhard, BMW Group Research and Technology