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Intelligent Cars. Nikhil M. Chakravarthy CSE 6362 Spring 2003 Dr. Lawrence B. Holder, Jr. Purpose. Investigate the motivation of adding Intelligence to a car. Explore problems and solutions. Survey the current state of research. Identify future research trends. Outline.

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Intelligent cars l.jpg

Intelligent Cars

Nikhil M. Chakravarthy

CSE 6362

Spring 2003

Dr. Lawrence B. Holder, Jr.

Intelligent Environments

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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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  • Definitions / Motivation

  • Design Goals

  • Problems / Solutions - Theory

  • Current Industry Solutions

  • Future Trend

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  • Intelligence

    • An intelligent, incorporeal being, especially an angel.

    • The capacity to acquire and apply knowledge.

  • Artificial

    • Not genuine or natural.

    • Brought about or caused by sociopolitical or other human-generated forces or influences.

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  • Artificial Intelligence

    • 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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  • 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

  • Increase Safety.

  • Improve Operational Efficiency.

  • Enhance Driving Experience.

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Driver Operations

  • Speed Control

    • Ignition.

    • Accelerate.

    • Cruise.

    • Decelerate.

    • Stop.

    • Backup.

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Driver Operations

  • Direction

    • Turn left / right.

    • Go Straight.

  • Signals

    • Signal turns.

    • Turn Lights on / off.

    • Sound Horn.

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Driver Operations

  • Climate

    • Activate Wipers.

    • Open / Close Windows.

    • Open / Close Vents.

    • Activate Heater / AC / Fan.

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Driver Operations

  • Maintenance

    • Refuel.

    • Wash.

    • Service.

  • Abnormal Conditions

    • Breakdown.

    • Accident.

    • Theft.

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Occupant Safety

  • Collision Warning

    • Blind spot.

    • Pedestrian.

    • Roll Over.

  • Collision Avoidance

    • Steering.

    • Brakes.

    • Throttle.

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Occupant Comfort

  • Driver Assistance

    • Adaptive cruise control.

  • Vehicle Automation

    • Autonomous / Co-operative

    • Low Speed Automation

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  • Vision

    • Night

    • Bad Weather

    • Corners / Up Hill

  • Object

    • Stationary / In Motion

    • Direction / Speed

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  • Machine Vision

  • Radar

  • GPS + Digital Maps

  • Sensors

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Solutions : by-product

  • ‘Sensored’ Roads.

    • Speed Limit Signs.

    • Lane Markings.

      • Magnetic Referencing.

    • Road Signs.

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Research Prototypes

  • Partners for Advanced Transit and Highways.

  • Vision-Based Intelligent Navigator.

  • Distinguishing Objects Using Laser Radar and Vision.

  • “Smarter Car”.

    • Programmed Intelligence.

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Emergency Vehicle Maneuvers and Control Laws

  • 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

  • Scanning Laser Radar (SLR).

  • White Lane Markers.

    • Image Processing.

  • Objects

    • Vehicle

    • Delineator

    • Sign

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Distinguishing the Types of Objects

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Intelligence Vendors

  • Motorola

  • IBM

  • Philips

  • Bosch

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Motorola Digital DNA

  • 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

  • FlexRay protocol.

    • DaimlerChrysler and BMW

  • Adapting to the User.

  • Intelligence in Silicon.

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Motorola mobileGT™

  • “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 PowerPCarchitecture, ultra-reliable real-time OS, and open, scalable Java™ framework …”

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Motorola mobileGT™

  • Speech Recognition.

  • Graphical User Interface (GUI).

  • Wireless Communications.

  • GPS Navigation.

  • Digital Radio.

  • Web, and Email.

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Motorola mobileGT™

  • 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™

  • DNA Detection System.

    • 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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  • Preventive vehicle diagnostics.

  • IBM Blue Octane.

  • Multimedia.

    • Digital Music.

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  • Toyota

  • Volvo

  • BMW

  • Lexus

  • Nissan

  • Honda

  • Hyundai

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Intelligent …

  • Cruise Control

  • Headlights

  • Air Bags

  • Navigation

  • Body Color

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Intelligent …

  • Doors

  • Mirrors

  • Locks

  • Tires

  • Temperature Control

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Intelligent …

  • Steering

  • Seats

  • Speed

  • Entertainment

  • Air Flow Control

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Smart Airbags

  • “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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  • Emergency Road Side Infrastructure.

  • Insurance.

  • Government.

    • Speeding Tickets.

  • Artificial Intelligence.

    • Programmed vs. Learning

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  • Fascination for Intelligent Cars.

  • Problems and Solutions.

  • Commercial Solutions.

  • Technological Infrastructure.

  • Future Research Trends.

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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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  • 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 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): 189- 195, IEEE Transactions on Intelligent Transportation Systems, Sep 2002, Vol.3, Issue 3

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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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  • 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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