Transcript Intelligent Vehicles - The School of Electrical Engineering and

Intelligent Cars
Nikhil M. Chakravarthy
CSE 6362
Spring 2003
Dr. Lawrence B. Holder, Jr.
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Purpose
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Investigate the motivation of adding
Intelligence to a car.
Explore problems and solutions.
Survey the current state of research.
Identify future research trends.
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Outline
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Definitions / Motivation
Design Goals
Problems / Solutions - Theory
Current Industry Solutions
Future Trend
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Definitions
Intelligence
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An intelligent, incorporeal being, especially an
angel.
The capacity to acquire and apply knowledge.
Artificial
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Not genuine or natural.
Brought about or caused by sociopolitical or
other human-generated forces or influences.
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Definitions
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Artificial Intelligence
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The ability of a computer or other machine
to perform those activities that are
normally thought to require intelligence.
The ability of a man made machine to
acquire and apply knowledge.
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Motivation
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Traffic accidents.
Military operations.
Improve efficiency.
Technical challenge.
The LAW.
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Role Models: Benny and
Herbie
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Design Goals
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Increase Safety.
Improve Operational Efficiency.
Enhance Driving Experience.
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Driver Operations
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Speed Control
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Ignition.
Accelerate.
Cruise.
Decelerate.
Stop.
Backup.
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Driver Operations
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Direction
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Turn left / right.
Go Straight.
Signals
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Signal turns.
Turn Lights on / off.
Sound Horn.
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Driver Operations
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Climate
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Activate Wipers.
Open / Close Windows.
Open / Close Vents.
Activate Heater / AC / Fan.
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Driver Operations
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Maintenance
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Refuel.
Wash.
Service.
Abnormal Conditions
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Breakdown.
Accident.
Theft.
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Occupant Safety
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Collision Warning
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Blind spot.
Pedestrian.
Roll Over.
Collision Avoidance
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Steering.
Brakes.
Throttle.
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Occupant Comfort
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Driver Assistance
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Adaptive cruise control.
Vehicle Automation
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Autonomous / Co-operative
Low Speed Automation
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Issues
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Vision
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Night
Bad Weather
Corners / Up Hill
Object
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Stationary / In Motion
Direction / Speed
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Solutions
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Machine Vision
Radar
GPS + Digital Maps
Sensors
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Solutions : by-product
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‘Sensored’ Roads.
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Speed Limit Signs.
Lane Markings.
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Magnetic Referencing.
Road Signs.
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Research Prototypes
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Partners for Advanced Transit and
Highways.
Vision-Based Intelligent Navigator.
Distinguishing Objects Using Laser
Radar and Vision.
“Smarter Car”.
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Programmed Intelligence.
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Emergency Vehicle Maneuvers
and Control Laws
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High-priority transit to emergency
vehicles.
Free-flowing and Stopped traffic.
Automated Highway Systems.
California Partners for Advanced Transit
and Highways (PATH).
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PATH Architecture.
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Vision-Based Intelligent
Navigator
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State-transition Graph
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Distinguishing Objects Using
Laser Radar and Vision
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Scanning Laser Radar (SLR).
White Lane Markers.
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Image Processing.
Objects
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Vehicle
Delineator
Sign
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Distinguishing the Types of
Objects
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Fuzzy Logic + Neural Net =
“Smarter Car”
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Intelligence Vendors
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Motorola
IBM
Philips
Bosch
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Motorola Digital DNA
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Automobiles contain 200 to 450
semiconductors worth approximately
$165 (Selantek, 1998).
By 2001, the content is expected to be
worth up to $1,500 per vehicle.
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Motorola Digital DNA
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FlexRay protocol.
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DaimlerChrysler and BMW
Adapting to the User.
Intelligence in Silicon.
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Motorola mobileGT™
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“The mobileGT™ platform from Motorola is a
complete system and alliance, enabling the
latest, customized driver information
technology. It's a solution providing
automakers and tier-one manufacturers a
single recognized platform from the
automotive semiconductor leader. It's a
solution supported by the mobileGT alliance,
the major players in the business. With its
single 32-bit PowerPC architecture, ultrareliable real-time OS, and open, scalable
Java™ framework …”
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Motorola mobileGT™
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Speech Recognition.
Graphical User Interface (GUI).
Wireless Communications.
GPS Navigation.
Digital Radio.
Web, and Email.
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Motorola mobileGT™
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Remote Keyless Entry (RKE) systems.
Vehicle immobilization systems.
Passive entry systems.
Tire Pressure Monitoring System.
Anti-Lock Braking Systems.
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Motorola eSensor™
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DNA Detection System.
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Binding properties of DNA and RNA.
Electronic circuit element.
Detectable electronic signal.
Disposable biochip cartridges, detection
reagents, electronic biochip reader, software
and protocols.
Convenient, economically feasible.
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IBM
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Preventive vehicle diagnostics.
IBM Blue Octane.
Multimedia.
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Digital Music.
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Consumers
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Toyota
Volvo
BMW
Lexus
Nissan
Honda
Hyundai
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Intelligent …
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Cruise Control
Headlights
Air Bags
Navigation
Body Color
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Intelligent …
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Doors
Mirrors
Locks
Tires
Temperature Control
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Intelligent …
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Steering
Seats
Speed
Entertainment
Air Flow Control
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Smart Airbags
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“This fall, more than a third of new cars must, by
federal mandate, be able to sense the difference
between an adult occupant, a child and an empty
seat. Airbags would then only inflate as much as
needed. Weight and tension sensors under seats and
in seatbelts are the first step, but Siemens, TRW and
Motorola are developing lasers, 3-D cameras and
electrical fields that can determine occupants'
position as well as their size. "The existing
technology can determine if someone's in a seat,"
notes TRW engineer Roger McCurdy, "but the real
value will be when airbags determine when someone
is out of position -- that's the root cause of injuries. "
’’ – Popular Science April 2003
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Smart Airbags
A ceiling-mounted sensor "sees" who's in the car and inflates airbags to the
appropriate size. Illustration by Garry Marshall, Popular Science April 2003.
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Future: Riding Cars
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Lexus Appeal
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The NAME is …
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Losers
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Emergency Road Side Infrastructure.
Insurance.
Government.
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Speeding Tickets.
Artificial Intelligence.
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Programmed vs. Learning
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Summery
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Fascination for Intelligent Cars.
Problems and Solutions.
Commercial Solutions.
Technological Infrastructure.
Future Research Trends.
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Questions?
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References
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Bishop, “A Survey of Intelligent Vehicle Applications
Worldwide”, Proceedings of the IEEE Intelligent
Vehicles Symposium, 2000.
Toy, C.; Leung, K.; Alvarez, L.; Horowitz, R.,
“Emergency vehicle maneuvers and control laws for
automated highway systems”, Page(s): 109-119,
IEEE Transactions on Intelligent Transportation
Systems, Jun 2002, Vol.3, Issue 2
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References
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Kato, S.; Tsugawa, S.; Tokuda, K.; Matsui, T.; Fujii,
H., “Vehicle control algorithms for cooperative driving
with automated vehicles and intervehicle
communications”, Page(s): 155- 161, IEEE
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Transactions on Intelligent Transportation Systems,
Sep 2002, Vol.3, Issue 3
Shimomura, N.; Fujimoto, K.; Oki, T.; Muro, H., “An
algorithm for distinguishing the types of objects on
the road using laser radar and vision”, Page(s): 189195, IEEE Transactions on Intelligent Transportation
Systems, Sep 2002, Vol.3, Issue 3
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References
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Embrechts, M.J.; DiCesare, F.; Luetzelschwab, M.J.; ,
“Fuzzy logic and neural net control for the “Smarter
Car“ ”, Systems, Man and Cybernetics, 1995. Page(s):
371 -376, IEEE International Conference on
'Intelligent Systems for the 21st Century'., Volume: 1,
22-25 Oct 1995
Miura, J.; Itoh, M.; Shirai, Y., “Toward vision-based
intelligent navigator: its concept and prototype”,
Page(s): 136- 146, IEEE Transactions on Intelligent
Transportation Systems, Jun 2002, Vol.3, Issue 2
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References
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Moite, S., “How smart can a car be?”, Page(s): 277 279, Proceedings of the Intelligent Vehicles '92
Symposium., 29 Jun-1 Jul 1992
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Web References
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http://www.motorola.com/mot/documents/0,1028,123,00.pdf
http://www.businessweek.com/adsections/smartcars/smcaroads.htm
http://www.popsci.com/popsci/auto/article/0,12543,434957,00.html
http://www.motorola.com/lifesciences/esensor/tech_overview.html
http://www.islandnet.com/~kpolsson/forsale/dis136.jpg
http://images.amazon.com/images/P/630440123X.01.LZZZZZZZ.jpg
http://www.barchetta.cc/All.Ferraris/images/0412/james-bond-a-1.jpg
http://www.killermovies.com/images/movies/bond_die1_001.jpg
http://dictionary.reference.com/
http://www.spielberg-dreamworks.com/minorityreport/presskit/Tom_Car.jpg
http://gamingasylum.topcities.com/screens/movies/minority2.jpg
http://ffmedia.ign.com/filmforce/image/haraldbelkerdesign_minorityreportlexus.jpg
http://ewww.motorola.com/webapp/sps/site/overview.jsp?nodeId=02M0ylfWcbfM0yrBwp3h
#block
http://www.studioillustrators.com/Illustrations/Cartoon%20car.jpg
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