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Intelligent automatic overtaking system using vision for vehicle detection

  • Vicente Milanés*
  • , David F. Llorca
  • , Jorge Villagrá
  • , Joshué Pérez
  • , Carlos Fernández
  • , Ignacio Parra
  • , Carlos González
  • , Miguel A. Sotelo
  • *Corresponding author for this work
  • UPM-CSIC
  • University of Alcalá

Research output: Contribution to journal › Article › peer-review

126 Citations (Scopus)

Abstract

There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manœuvres involving vehicles - overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomous overtaking manœuvre. To this end, a fuzzy-logic based controller was developed to emulate how humans overtake. Its input is information from the vision system and from a positioning-based system consisting of a differential global positioning system (DGPS) and an inertial measurement unit (IMU). Its output is the generation of action on the vehicle's actuators, i.e.; the steering wheel and throttle and brake pedals. The system has been incorporated into a commercial Citroën car and tested on the private driving circuit at the facilities of our research center, CAR, with different preceding vehicles - a motorbike, car, and truck - with encouraging results.

Original languageEnglish
Pages (from-to)3362-3373
Number of pages12
JournalExpert Systems with Applications
Volume39
Issue number3
DOIs
Publication statusPublished - 15 Feb 2012
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Advanced vehicle control and safety systems
  • Fuzzy logic
  • Intelligent transportation systems
  • Road vehicle control
  • Stereo vision

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