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Autonomous Vehicles

This piece explores the intricacies of autonomous vehicles, focusing on what makes a vehicle truly autonomous, differentiating it from remote-controlled variants. The concept is illustrated through the "3 D's": Detection, Delivery, and Data-Gathering. Current technologies, such as Drive-By-Wire and advanced sensors, are examined alongside existing challenges like environmental understanding, navigation, and social issues regarding trust and liability. Insights from the DARPA Challenges illustrate the progress and ongoing hurdles in developing fully autonomous vehicles.

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Autonomous Vehicles

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Presentation Transcript

  1. Autonomous Vehicles By: Rotha Aing

  2. What makes a vehicleautonomous? • “Driverless” • Different from remote controlled • 3 D’s • Detection • Delivery • Data-Gathering

  3. 3D’s • Detection – Reasoning • The surroundings and current conditions • Data-gathering – Search • From the information search knowledgebase for purposed actions • What to do next? • Delivery – Learning • View and record results of actions

  4. Current Approaches • Fully Autonomous • Taxi-like cars • Autonomous in closed systems • Monorails • Assistance System • Environment Sensing • Distance Sensors • ABS

  5. Solution Template • Sensors: Figure out obstacles around the vehicle • Navigation: How to get to the target location from the present location • Motion planning: Getting to the location, getting by any obstacles, following any rules • Control: Getting the vehicle itself to move

  6. Current Issues • Technical • Sensors • Understanding the environment • Navigation • Know its current position and where it wants to go • Motion Planning • Navigation through traffic • Actuation • Operate the correct and needed features

  7. Issues • Social Issues • Trusting the car • Getting on public roads • Getting people to go in • Liability Issues • Lost Jobs

  8. What’s been solved? • Control • Navigation • Some issues of Sensory

  9. Control • Drive-By-Wire • Sends messages to onboard computers • Physical ties are unlinked • In most current cars

  10. Drive By Wire • When sensor/trigger is pressed, it sends message to the car to perform the tasks

  11. DBW in Autonomous Vehicles • Replace the human driver • Activate the sensors/triggers • SciAutonics • Servomotors for each gear • Large servomotor with belt drive for steering

  12. Navigation • Already available • Combination of: • GPS • Roadside database

  13. Sensory • Major issue: • Lack of computing power • “More processors” • Half completed • RADAR • Laser Detection • Cameras

  14. Sensory Information Issues • Factors of weather • Dust, rain, fog • Correctly Identifying an obstacle • Shadows vs. ditches • Shallow vs. deep • Speed of the vehicle and the speed data can be correctly received

  15. Motion Planning • Most challenging • Collision Detection • Affected by: • Quality of Sensory information • Quality of Controls • Need for algorithm that can determine movements quickly but also the correct ones

  16. “Road Map” • Decision Tree (Graph) • With points A and G • Fill in free spots (Configuration Space) • Try to link A to G • Configuration Space Algorithms • Sampling-based • Faster, less computing power • Combinatorial • More complete

  17. Configuration Space

  18. DARPA Challenge • Defense Advanced Research Projects Agency • 2004 Desert Course • 2005 Off-road, mountain terrain • 2007 Urban Challenge • Collision Avoidance • Obey traffic signs

  19. Stanley • 2005 DARPA Challenge winner • Volkswagen Touareg modified with onboard computers

  20. Stanley’s Sensory • 5 LIDAR lasers • 24 GHz RADAR • Stereo camera • Single-lens camera

  21. Path Analysis • Built in RDDF (database of course) • Vehicle predominantly followed the RDDF data

  22. Obstacle Detection • Machine Learning Approach • Accuracy value of data is based on how human’s perform • Slows down when a path can not be found quickly • Grid of either occupied, free, or unknown spots

  23. Issues with mapping scheme • Errors in determining environment • 12.6% of areas determined as obstacle was not

  24. Alice out of challenge

  25. Personal Opinions • Good progress since the first challenge • Not until the 2007 challenge will we really know if a fully autonomous vehicle is possible in the near future • Other approaches more likely to be developed into mainstream before fully autonomous vehicles

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