Clustering-Based Lateral Longitudinal Target Recognition of In-Vehicle LIDAR Data

In order to improve the accuracy of lateral and vertical target recognition in a car-following situation, the box plot is used to analyze and filter discrete points to overcome the LIDAR point data error; application of the modified adaptive K-means clustering algorithm which is based on the clustering evaluation index is applied to process the LIDAR point from LUX4; the candidate targets are output by clustering results. The test results show that the obstacle detection algorithm is more robust and reliable in the car-following situation.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 308-321
  • Monograph Title: CICTP 2016: Green and Multimodal Transportation and Logistics

Subject/Index Terms

Filing Info

  • Accession Number: 01606602
  • Record Type: Publication
  • ISBN: 9780784479896
  • Files: TRIS, ASCE
  • Created Date: Jun 29 2016 3:03PM