Detecting Road Conditions in Front of The Vehicle Using Off-The-Shelf Camera

Shao Peng Lu, Min Te Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The development of road transportation makes it easier for people to drive their vehicles. Unfortunately, it also causes the increasing number of traffic accidents. Advanced driver assistance systems, which in many ways is based on the future trajectory prediction of the vehicle, are developed to alert the driver for potential dangers. Road conditions, including road geometry and the distance between lead vehicle and host vehicle, are important factors in improving accuracy of future trajectory prediction. The road conditions can be obtained by the camera affixed in the vehicle. In this paper, we propose an image processing system, which includes a curve detection algorithm (CDA) and a distance conversion (DC) algorithm, to obtain these road conditions from the image. First, CDA detects the lane stripes and calculates the vanishing point. The road trend can then be identified according to the location of the vanishing point. DC is used to convert the distance between the lead and host vehicles in the image to the real distance. Through analyses and experiments, it is shown that the proposed system achieves a higher precision than the baseline algorithms.

Original languageEnglish
Title of host publication2019 20th Asia-Pacific Network Operations and Management Symposium
Subtitle of host publicationManagement in a Cyber-Physical World, APNOMS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9784885523205
DOIs
StatePublished - Sep 2019
Event20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019 - Matsue, Japan
Duration: 18 Sep 201920 Sep 2019

Publication series

Name2019 20th Asia-Pacific Network Operations and Management Symposium: Management in a Cyber-Physical World, APNOMS 2019

Conference

Conference20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019
Country/TerritoryJapan
CityMatsue
Period18/09/1920/09/19

Keywords

  • distance estimation
  • image analysis
  • turn detection
  • Vehicle safety

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