1 / 50

Intelligent Cars: Exploring Problems and Solutions

This research explores the motivation behind adding intelligence to cars, investigates current problems and solutions, and identifies future research trends. It covers definitions, design goals, driver operations, occupant safety and comfort, and solutions such as machine vision and sensors.

seaver
Download Presentation

Intelligent Cars: Exploring Problems and Solutions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

  2. Purpose • 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

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

  4. Definitions • 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. Intelligent Environments

  5. Definitions • 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. Intelligent Environments

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

  7. Role Models: Benny and Herbie Intelligent Environments

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

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

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

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

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

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

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

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

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

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

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

  19. 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). Intelligent Environments

  20. PATH Architecture. Intelligent Environments

  21. Vision-Based Intelligent Navigator Intelligent Environments

  22. State-transition Graph Intelligent Environments

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

  24. Distinguishing the Types of Objects Intelligent Environments

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

  26. Intelligence Vendors • Motorola • IBM • Philips • Bosch • … Intelligent Environments

  27. 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. Intelligent Environments

  28. Motorola Digital DNA • FlexRay protocol. • DaimlerChrysler and BMW • Adapting to the User. • Intelligence in Silicon. Intelligent Environments

  29. 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 …” Intelligent Environments

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

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

  32. 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. Intelligent Environments

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

  34. Consumers • Toyota • Volvo • BMW • Lexus • Nissan • Honda • Hyundai Intelligent Environments

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

  36. Intelligent … • Doors • Mirrors • Locks • Tires • Temperature Control Intelligent Environments

  37. Intelligent … • Steering • Seats • Speed • Entertainment • Air Flow Control Intelligent Environments

  38. 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 Intelligent Environments

  39. 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

  40. Future: Riding Cars Intelligent Environments

  41. Lexus Appeal Intelligent Environments

  42. The NAME is … Intelligent Environments

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

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

  45. Questions? Intelligent Environments

  46. References • 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

  47. References • 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 Intelligent Environments

  48. References • 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 Intelligent Environments

  49. References • 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

  50. Web References • 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://e-www.motorola.com/webapp/sps/site/overview.jsp?nodeId=02M0ylfWcbfM0yrBwp3h#block • http://www.studioillustrators.com/Illustrations/Cartoon%20car.jpg Intelligent Environments

More Related