A laser-scanner-based approach toward driving safety and traffic data collection

  • Authors:

  • Huijing Zhao;Masaki Chiba;Ryosuke Shibasaki;Xiaowei Shao;Jinshi Cui;Hongbin Zha

  • Affiliations:

  • Key Laboratory of Machine Perception and the School of Electronics Engineering and Computer Science, Peking University, Beijing, China;Technical Research Center, Mazda Motor Corporation, Yokohama, Japan;Center for Spatial Information Science, University of Tokyo, Chiba, Japan;Center for Spatial Information Science, University of Tokyo, Chiba, Japan;Key Laboratory of Machine Perception and the School of Electronics Engineering and Computer Science, Peking University, Beijing, China;Key Laboratory of Machine Perception and the School of Electronics Engineering and Computer Science, Peking University, Beijing, China

  • Venue:
  • IEEE Transactions on Intelligent Transportation Systems
  • Year:
  • 2009

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Abstract

This work is motivated by the following two potential applications: 1) enhancing driving safety and 2) collecting traffic data in a large dynamic urban environment. A laser-scanner-based approach is proposed. The problem is formulated as a simultaneous localization and mapping (SLAM) with object tracking and classification, where the focus is on managing a mixture of data from both dynamic and static objects in a highly dynamic environment. A trajectory-oriented closure is also proposed using the sporadically available global positioning system (GPS) measurements in urban areas to assist for global accuracy, particularly when the vehicle makes a noncyclical measurement in a large outdoor environment. Experiments are conducted using the data that were collected along a course near 4.5 km in a highly dynamic environment. Possibilities of the approaches toward the two potential applications are demonstrated, and avenues for future works are discussed.