Download Autonomous Intelligent Vehicles: Theory, Algorithms, and by Hong Cheng PDF

By Hong Cheng

ISBN-10: 1447122798

ISBN-13: 9781447122791

Autonomous clever automobiles pose specific demanding situations in robotics, that surround problems with atmosphere conception and modeling, localization and map development, course making plans and decision-making, and movement control.

This vital text/reference offers state of the art study on clever cars, protecting not just issues of object/obstacle detection and popularity, but additionally points of auto movement keep watch over. With an emphasis on either high-level thoughts, and functional element, the textual content hyperlinks conception, algorithms, and problems with and software program implementation in clever car research.

Topics and features:

  • Presents a radical creation to the advance and most modern growth in clever automobile examine, and proposes a uncomplicated framework
  • Provides detection and monitoring algorithms for established and unstructured roads, in addition to on-road motor vehicle detection and monitoring algorithms utilizing boosted Gabor features
  • Discusses an method for a number of sensor-based multiple-object monitoring, as well as an built-in DGPS/IMU positioning approach
  • Examines a car navigation technique utilizing worldwide views
  • Introduces algorithms for lateral and longitudinal car movement control

An crucial reference for researchers within the box, the large assurance of all features of this examine also will attract graduate scholars of computing device technology and robotics who're attracted to clever vehicles.

Dr. Hong Cheng is Professor within the college of Automation Engineering, and Director of the trend popularity and desktop Intelligence Institute on the collage of digital technological know-how and expertise of China.

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Extra resources for Autonomous Intelligent Vehicles: Theory, Algorithms, and Implementation

Example text

When there exist state transitions in the behavior layer, the corresponding component of the tactical layer is executed. Among the four tactical components, the road tactical component is to seek a proper lane and to monitor other agents in the same and neighboring lanes. The intersection tactical component handles intersection queuing behavior and safe merging. The zone tactical component takes care of basic navigation in unconstrained cases. The blockage tactical component implements obstacle detection and judging whether there are temporary traffic jams, and acts accordingly.

Whereas both radar and laser sensors have the same problems of low spatial and temporal resolutions. Hence, vision sensors possess key advantages over active ones, for foreseeing in massive and widespread applications on autonomous intelligent vehicles. At the same time, vision-based road detection and tracking approaches have a few limitations: • Vision sensors are less robust than laser sensors and radar sensors in extreme illumination conditions, such as fog, night, sunshine, rain. • Large amount of video/image data is a great challenge for embedded systems.

J. Field Robot. 25(8), 467–492 (2008) 3. : A survey of intelligent vehicle applications worldwide. In: Proceedings of the IEEE on Intelligent Vehicles Symposium, 2000. IV 2000, pp. 25–30. IEEE, New York (2000) 4. : Little Ben: The Ben Franklin racing teams entry in the 2007 DARPA Urban Challenge. DARPA Urban Challenge 25(9), 231–255 (2009) 5. : The TerraMax autonomous vehicle. J. Field Robot. 23(9), 693–708 (2006) 6. : UNSCARF—a color vision system for the detection of unstructured roads. In: Proc.

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