Initial Results in Vision Based Road and Intersection Detection and Traversal.

Abstract

The use of artificial neural networks in the domain of autonomous driving has produced promising results. ALVINN has shown that a neural system can drive a vehicle reliably and safely on many different types of roads, ranging from paved paths to interstate highways (9). The next step in the evolution of autonomous driving systems is to intelligently handle road junctions. In this paper, we present an addition to the basic ALVINN driving system which makes autonomous detection of roads and traversal of simple intersections possible. The addition is based on geometrically modelling the world, accurately imaging interesting parts of the scene using this model, and monitoring ALVINN's respouse to the created image.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1995
Accession Number
ADA311299

Entities

People

  • Todd M. Jochem

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Application Software
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Computer Programs
  • Detection
  • Digital Information
  • Monitoring
  • Neural Networks
  • Personal Information Managers

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Logistics and Supply Chain Management.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks