Coverart for item
The Resource Autonomous Ground Vehicles, (electronic resource)

Autonomous Ground Vehicles, (electronic resource)

Label
Autonomous Ground Vehicles
Title
Autonomous Ground Vehicles
Creator
Contributor
Author
Subject
Language
eng
Summary
In the near future, we will witness vehicles with the ability to provide drivers with several advanced safety and performance assistance features. Autonomous technology in ground vehicles will afford us capabilities like intersection collision warning, lane change warning, backup parking, parallel parking aids, and bus precision parking. Providing you with a practical understanding of this technology area, this innovative resource focuses on basic autonomous control and feedback for stopping and steering ground vehicles. Covering sensors, estimation, and sensor fusion to percept the vehicle mot
Cataloging source
EBLCP
http://library.link/vocab/creatorDate
1947-
http://library.link/vocab/creatorName
Özgüner, Ü.
Dewey number
629.2042
Index
no index present
LC call number
TL152.8
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorDate
1966-
http://library.link/vocab/relatedWorkOrContributorName
  • Acarman, Tankut
  • Redmill, Keith A.
Series statement
jdawson
http://library.link/vocab/subjectName
  • Motor vehicles
  • Motor vehicles
  • Automobiles
  • Automobiles
  • Motor vehicles
  • Intelligent transportation systems
  • Engineering
  • TECHNOLOGY & ENGINEERING
  • TRANSPORTATION
Label
Autonomous Ground Vehicles, (electronic resource)
Instantiates
Publication
Note
5.4.2 Parking Scenarios: General Parking Scenario and DARPA Urban Challenge Autonomous Vehicle Parking Scenario
Contents
  • Autonomous Ground Vehicles; Contents; Preface; Chapter 1 Introduction; 1.1 Background in Autonomy in Cars; 1.2 Components of Autonomy; 1.2.1 Sensors; 1.2.2 Actuators; 1.2.3 Communication; 1.2.4 Intelligence; 1.3 Notes on Historical Development; 1.3.1 Research and Experiments on Autonomous Vehicles; 1.3.2 Autonomous Driving Demonstrations; 1.3.3 Recent Appearances in the Market; 1.4 Contents of this Book; References; Chapter 2 The Role of Control in Autonomous Systems; 2.1 Feedback; 2.1.1 Speed Control Using Point Mass and Force Input; 2.1.2 Stopping; 2.1.3 Swerving
  • 2.2 A First Look at Autonomous Control2.2.1 Car Following and Advanced Cruise Control; 2.2.2 Steering Control Using Point Mass Model: Open Loop Commands; 2.2.3 Steering Control Using Point Mass Model: Closed-Loop Commands; 2.2.4 Polynomial Tracking; 2.2.5 Continuous and Smooth Trajectory Establishment; 2.2.6 The Need for Command Sequencing; References; Chapter 3 System Architecture and Hybrid System Modeling; 3.1 System Architecture; 3.1.1 Architectures Within Autonomous Vehicles; 3.1.2 Task Hierarchies for Autonomous Vehicles; 3.2 Hybrid System Formulation
  • 3.2.1 Discrete Event Systems, Finite State Machines, and Hybrid Systems3.2.2 Another Look at ACC; 3.2.3 Application to Obstacle Avoidance; 3.2.4 Another Example: Two Buses in a Single Lane; 3.3 State Machines for Different Challenge Events; 3.3.1 Macrostates: Highway, City, and Off-Road Driving; 3.3.2 The Demo '97 State Machine; 3.3.3 Grand Challenge 2 State Machine; 3.3.4 The Urban Challenge State Machine; References; Chapter 4 Sensors, Estimation, and Sensor Fusion; 4.1 Sensor Characteristics; 4.2 Vehicle Internal State Sensing; 4.2.1 OEM Vehicle Sensors
  • 4.2.2 Global Positioning System (GPS)4.2.3 Inertial Measurements; 4.2.4 Magnetic Compass (Magnetometer); 4.3 External World Sensing; 4.3.1 Radar; 4.3.2 LIDAR; 4.3.3 Image Processing Sensors; 4.3.4 Cooperative Infrastructure Technologies; 4.4 Estimation; 4.4.1 An Introduction to the Kalman Filter; 4.4.2 Example; 4.4.3 Another Example of Kalman Filters: Vehicle Tracking for Crash Avoidance; 4.5 Sensor Fusion; 4.5.1 Vehicle Localization (Position and Orientation); 4.5.2 External Environment Sensing; 4.5.3 Occupancy Maps and an Off-Road Vehicle; 4.5.4 Cluster Tracking and an On-Road Urban Vehicle
  • 4.6 Situational Awareness4.6.1 Structure of a Situation Analysis Module; 4.6.2 Road and Lane Model Generation; 4.6.3 Intersection Generation; 4.6.4 Primitives; 4.6.5 Track Classification; 4.6.6 Sample Results; References; Chapter 5 Examples of Autonomy; 5.1 Cruise Control; 5.1.1 Background; 5.1.2 Speed Control with an Engine Model; 5.1.3 More Complex Systems; 5.2 Antilock-Brake Systems; 5.2.1 Background; 5.2.2 Slip; 5.2.3 An ABS System; 5.3 Steering Control and Lane Following; 5.3.1 Background; 5.3.2 Steering Control; 5.3.3 Lane Following; 5.4 Parking; 5.4.1 Local Coordinates
Control code
ocn769343997
Dimensions
unknown
Extent
1 online resource (288 p.)
Form of item
online
Isbn
9781608071937
Specific material designation
remote
Label
Autonomous Ground Vehicles, (electronic resource)
Publication
Note
5.4.2 Parking Scenarios: General Parking Scenario and DARPA Urban Challenge Autonomous Vehicle Parking Scenario
Contents
  • Autonomous Ground Vehicles; Contents; Preface; Chapter 1 Introduction; 1.1 Background in Autonomy in Cars; 1.2 Components of Autonomy; 1.2.1 Sensors; 1.2.2 Actuators; 1.2.3 Communication; 1.2.4 Intelligence; 1.3 Notes on Historical Development; 1.3.1 Research and Experiments on Autonomous Vehicles; 1.3.2 Autonomous Driving Demonstrations; 1.3.3 Recent Appearances in the Market; 1.4 Contents of this Book; References; Chapter 2 The Role of Control in Autonomous Systems; 2.1 Feedback; 2.1.1 Speed Control Using Point Mass and Force Input; 2.1.2 Stopping; 2.1.3 Swerving
  • 2.2 A First Look at Autonomous Control2.2.1 Car Following and Advanced Cruise Control; 2.2.2 Steering Control Using Point Mass Model: Open Loop Commands; 2.2.3 Steering Control Using Point Mass Model: Closed-Loop Commands; 2.2.4 Polynomial Tracking; 2.2.5 Continuous and Smooth Trajectory Establishment; 2.2.6 The Need for Command Sequencing; References; Chapter 3 System Architecture and Hybrid System Modeling; 3.1 System Architecture; 3.1.1 Architectures Within Autonomous Vehicles; 3.1.2 Task Hierarchies for Autonomous Vehicles; 3.2 Hybrid System Formulation
  • 3.2.1 Discrete Event Systems, Finite State Machines, and Hybrid Systems3.2.2 Another Look at ACC; 3.2.3 Application to Obstacle Avoidance; 3.2.4 Another Example: Two Buses in a Single Lane; 3.3 State Machines for Different Challenge Events; 3.3.1 Macrostates: Highway, City, and Off-Road Driving; 3.3.2 The Demo '97 State Machine; 3.3.3 Grand Challenge 2 State Machine; 3.3.4 The Urban Challenge State Machine; References; Chapter 4 Sensors, Estimation, and Sensor Fusion; 4.1 Sensor Characteristics; 4.2 Vehicle Internal State Sensing; 4.2.1 OEM Vehicle Sensors
  • 4.2.2 Global Positioning System (GPS)4.2.3 Inertial Measurements; 4.2.4 Magnetic Compass (Magnetometer); 4.3 External World Sensing; 4.3.1 Radar; 4.3.2 LIDAR; 4.3.3 Image Processing Sensors; 4.3.4 Cooperative Infrastructure Technologies; 4.4 Estimation; 4.4.1 An Introduction to the Kalman Filter; 4.4.2 Example; 4.4.3 Another Example of Kalman Filters: Vehicle Tracking for Crash Avoidance; 4.5 Sensor Fusion; 4.5.1 Vehicle Localization (Position and Orientation); 4.5.2 External Environment Sensing; 4.5.3 Occupancy Maps and an Off-Road Vehicle; 4.5.4 Cluster Tracking and an On-Road Urban Vehicle
  • 4.6 Situational Awareness4.6.1 Structure of a Situation Analysis Module; 4.6.2 Road and Lane Model Generation; 4.6.3 Intersection Generation; 4.6.4 Primitives; 4.6.5 Track Classification; 4.6.6 Sample Results; References; Chapter 5 Examples of Autonomy; 5.1 Cruise Control; 5.1.1 Background; 5.1.2 Speed Control with an Engine Model; 5.1.3 More Complex Systems; 5.2 Antilock-Brake Systems; 5.2.1 Background; 5.2.2 Slip; 5.2.3 An ABS System; 5.3 Steering Control and Lane Following; 5.3.1 Background; 5.3.2 Steering Control; 5.3.3 Lane Following; 5.4 Parking; 5.4.1 Local Coordinates
Control code
ocn769343997
Dimensions
unknown
Extent
1 online resource (288 p.)
Form of item
online
Isbn
9781608071937
Specific material designation
remote

Library Locations

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      Chatham Street, Liverpool, L7 7BD, GB
      53.403069 -2.963723
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