Intelligent Cars Nikhil M Chakravarthy CSE 6362 Spring

Intelligent Cars Nikhil M. Chakravarthy CSE 6362 Spring 2003 Dr. Lawrence B. Holder, Jr. Intelligent Environments 1

Purpose n n Investigate the motivation of adding Intelligence to a car. Explore problems and solutions. Survey the current state of research. Identify future research trends. Intelligent Environments 2

Outline n n n Definitions / Motivation Design Goals Problems / Solutions - Theory Current Industry Solutions Future Trend Intelligent Environments 3

Definitions Intelligence n n n An intelligent, incorporeal being, especially an angel. The capacity to acquire and apply knowledge. Artificial n n n Not genuine or natural. Brought about or caused by sociopolitical or other human-generated forces or influences. Intelligent Environments 4

Definitions n Artificial Intelligence n n 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. Intelligent Environments 5

Motivation n n Traffic accidents. Military operations. Improve efficiency. Technical challenge. The LAW. Intelligent Environments 6

Role Models: Benny and Herbie Intelligent Environments 7

Design Goals n n n Increase Safety. Improve Operational Efficiency. Enhance Driving Experience. Intelligent Environments 8

Driver Operations n Speed Control n n n Ignition. Accelerate. Cruise. Decelerate. Stop. Backup. Intelligent Environments 9

Driver Operations n Direction n Turn left / right. Go Straight. Signals n n n Signal turns. Turn Lights on / off. Sound Horn. Intelligent Environments 10

Driver Operations n Climate n n Activate Wipers. Open / Close Windows. Open / Close Vents. Activate Heater / AC / Fan. Intelligent Environments 11

Driver Operations n Maintenance n n Refuel. Wash. Service. Abnormal Conditions n n n Breakdown. Accident. Theft. Intelligent Environments 12

Occupant Safety n Collision Warning n n Blind spot. Pedestrian. Roll Over. Collision Avoidance n n n Steering. Brakes. Throttle. Intelligent Environments 13

Occupant Comfort n Driver Assistance n n Adaptive cruise control. Vehicle Automation n n Autonomous / Co-operative Low Speed Automation Intelligent Environments 14

Issues n Vision n n Night Bad Weather Corners / Up Hill Object n n Stationary / In Motion Direction / Speed Intelligent Environments 15

Solutions n n Machine Vision Radar GPS + Digital Maps Sensors Intelligent Environments 16

Solutions : by-product n ‘Sensored’ Roads. n n Speed Limit Signs. Lane Markings. n n Magnetic Referencing. Road Signs. Intelligent Environments 17

Research Prototypes n n Partners for Advanced Transit and Highways. Vision-Based Intelligent Navigator. Distinguishing Objects Using Laser Radar and Vision. “Smarter Car”. n Programmed Intelligence. Intelligent Environments 18

Emergency Vehicle Maneuvers and Control Laws n n High-priority transit to emergency vehicles. Free-flowing and Stopped traffic. Automated Highway Systems. California Partners for Advanced Transit and Highways (PATH). Intelligent Environments 19

PATH Architecture. Intelligent Environments 20

Vision-Based Intelligent Navigator Intelligent Environments 21

State-transition Graph Intelligent Environments 22

Distinguishing Objects Using Laser Radar and Vision n n Scanning Laser Radar (SLR). White Lane Markers. n n Image Processing. Objects n n n Vehicle Delineator Sign Intelligent Environments 23

Distinguishing the Types of Objects Intelligent Environments 24

Fuzzy Logic + Neural Net = “Smarter Car” Intelligent Environments 25

Intelligence Vendors n n n Motorola IBM Philips Bosch … Intelligent Environments 26

Motorola Digital DNA n n 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. Intelligent Environments 27

Motorola Digital DNA n Flex. Ray protocol. n n n Daimler. Chrysler and BMW Adapting to the User. Intelligence in Silicon. Intelligent Environments 28

Motorola mobile. GT™ n “The mobile. GT™ 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 mobile. GT alliance, the major players in the business. With its single 32 -bit Power. PC architecture, ultrareliable real-time OS, and open, scalable Java™ framework …” Intelligent Environments 29

Motorola mobile. GT™ n n n Speech Recognition. Graphical User Interface (GUI). Wireless Communications. GPS Navigation. Digital Radio. Web, and Email. Intelligent Environments 30

Motorola mobile. GT™ n n n Remote Keyless Entry (RKE) systems. Vehicle immobilization systems. Passive entry systems. Tire Pressure Monitoring System. Anti-Lock Braking Systems. Intelligent Environments 31

Motorola e. Sensor™ n DNA Detection System. n n n 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. Intelligent Environments 32

IBM n n n Preventive vehicle diagnostics. IBM Blue Octane. Multimedia. n Digital Music. Intelligent Environments 33

Consumers n n n n Toyota Volvo BMW Lexus Nissan Honda Hyundai Intelligent Environments 34

Intelligent … n n n Cruise Control Headlights Air Bags Navigation Body Color Intelligent Environments 35

Intelligent … n n n Doors Mirrors Locks Tires Temperature Control Intelligent Environments 36

Intelligent … n n n Steering Seats Speed Entertainment Air Flow Control Intelligent Environments 37

Smart Airbags n “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 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 Mc. Curdy, "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 Intelligent Environments 38

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. Intelligent Environments 39

Future: Riding Cars Intelligent Environments 40

Lexus Appeal Intelligent Environments 41

The NAME is … Intelligent Environments 42

Losers n n n Emergency Road Side Infrastructure. Insurance. Government. n n Speeding Tickets. Artificial Intelligence. n Programmed vs. Learning Intelligent Environments 43

Summery n n n Fascination for Intelligent Cars. Problems and Solutions. Commercial Solutions. Technological Infrastructure. Future Research Trends. Intelligent Environments 44

Questions? Intelligent Environments 45

References n n 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 Intelligent Environments 46

References n 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 n 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 Intelligent Environments 47

References n n Embrechts, M. J. ; Di. Cesare, 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 21 st 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 Intelligent Environments 48

References n Moite, S. , “How smart can a car be? ”, Page(s): 277 279, Proceedings of the Intelligent Vehicles '92 Symposium. , 29 Jun-1 Jul 1992 Intelligent Environments 49

Web References n n n n 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/dis 136. jpg http: //images. amazon. com/images/P/630440123 X. 01. LZZZZZZZ. jpg http: //www. barchetta. cc/All. Ferraris/images/0412/james-bond-a-1. jpg http: //www. killermovies. com/images/movies/bond_die 1_001. jpg http: //dictionary. reference. com/ http: //www. spielberg-dreamworks. com/minorityreport/presskit/Tom_Car. jpg http: //gamingasylum. topcities. com/screens/movies/minority 2. jpg http: //ffmedia. ign. com/filmforce/image/haraldbelkerdesign_minorityreportlexus. jpg http: //ewww. motorola. com/webapp/sps/site/overview. jsp? node. Id=02 M 0 ylf. Wcbf. M 0 yr. Bwp 3 h #block http: //www. studioillustrators. com/Illustrations/Cartoon%20 car. jpg Intelligent Environments 50