Pedestrian flow estimation using sparse observation for autonomous vehicles

Ranulfo P.Bezerra Neto, Kazunori Ohno, Thomas Westfechtel, Satoshi Tadokoro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One of the major challenges that autonomous cars are facing today is the unpredictability of pedestrian movement in urban environments. Since pedestrian data acquired by vehicles are sparse observed a pedestrian flow directed graph is proposed to understand pedestrian behavior. In this work, an autonomous electric vehicle is employed to gather LiDAR and camera data. Pedestrian tracking information and semantic information from the environment are used with a probabilistic approach to create the graph. In order to refine the graph a set of outlier removal techniques are described. The graph-based pedestrian flow shows an increase of 61.29 % of coverage zone, and the outlier removal approach successfully removed 81 % of the edges.

Original languageEnglish
Title of host publication2019 19th International Conference on Advanced Robotics, ICAR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages779-784
Number of pages6
ISBN (Electronic)9781728124674
DOIs
Publication statusPublished - 2019 Dec
Event19th International Conference on Advanced Robotics, ICAR 2019 - Belo Horizonte, Brazil
Duration: 2019 Dec 22019 Dec 6

Publication series

Name2019 19th International Conference on Advanced Robotics, ICAR 2019

Conference

Conference19th International Conference on Advanced Robotics, ICAR 2019
CountryBrazil
CityBelo Horizonte
Period19/12/219/12/6

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering
  • Control and Optimization
  • Modelling and Simulation

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  • Cite this

    Neto, R. P. B., Ohno, K., Westfechtel, T., & Tadokoro, S. (2019). Pedestrian flow estimation using sparse observation for autonomous vehicles. In 2019 19th International Conference on Advanced Robotics, ICAR 2019 (pp. 779-784). [8981587] (2019 19th International Conference on Advanced Robotics, ICAR 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAR46387.2019.8981587