Pedestrian trajectory prediction in large infrastructures: A long-term approach based on path planning

Mario Garzón, David Garzón-Ramos, Antonio Barrientos, Jaime Del Cerro

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

This paper presents a pedestrian trajectory prediction technique. Its mail novelty is that it does not require any previous observation or knowledge of pedestrian trajectories, thus making it useful for autonomous surveillance applications. The prediction requires only a set of possible goals, a map of the scenario and the initial position of the pedestrian. Then, it uses two different path planing algorithms to find the possible routes and transforms the similarity between observed and planned routes into probabilities. Finally, it applies a motion model to obtain a time-stamped predicted trajectory. The system has been used in combination with a pedestrian detection and tracking system for real-world tests as well as a simulation software for a large number of executions.

Original languageEnglish
Title of host publicationICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics
EditorsOleg Gusikhin, Dimitri Peaucelle, Kurosh Madani
PublisherSciTePress
Pages381-389
ISBN (Electronic)9789897581984
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016 - Lisbon, Portugal
Duration: 29 Jul 201631 Jul 2016

Conference

Conference13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016
CountryPortugal
CityLisbon
Period29/07/1631/07/16

Keywords

  • Pedestrian trajectory prediction
  • Planning-based prediction
  • Trajectory forecast

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