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Authors: Ali Dehghani and Lucila Studencki

Affiliation: Coburg University of Applied Sciences and Arts, Faculty of Mechanical and Automotive Engineering, Coburg, Germany

Keyword(s): Pedestrian Intention Estimation, Multiple Pedestrian Tracking, Situational Awareness, Autonomous Driving, Autonomous Shuttle.

Abstract: Pedestrian intentions estimation and tracking have become essential for the development of autonomous vehicles (AVs). The vehicles need to be aware of pedestrians to avoid fatalities even in complex urban traffic. This requires understanding the most probable trajectory of pedestrians to accordingly plan the vehicle’s maneuvers. This complex task requires modeling how multiple pedestrians interact with each other and move depending on their environment. This paper employs a Gaussian Mixture Probability Hypothesis Density Filter, enhanced by the Generalized Potential Field Approach (GMPHD-GPFA), to simultaneously track multiple pedestrians and determine and predict their behavior seconds ahead. The model used considers the static environment of the pedestrians to estimate their intentions and improve prediction accuracy. The paper evaluates both the tracking efficiency of the algorithm and its capability to predict the intentions of multiple pedestrians.

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Paper citation in several formats:
Dehghani, A. and Studencki, L. (2024). Multi-Pedestrian Tracking and Map-Based Intention Estimation for Autonomous Driving Scenario. In Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-703-0; ISSN 2184-495X, SciTePress, pages 386-393. DOI: 10.5220/0012691700003702

@conference{vehits24,
author={Ali Dehghani and Lucila Studencki},
title={Multi-Pedestrian Tracking and Map-Based Intention Estimation for Autonomous Driving Scenario},
booktitle={Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2024},
pages={386-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012691700003702},
isbn={978-989-758-703-0},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Multi-Pedestrian Tracking and Map-Based Intention Estimation for Autonomous Driving Scenario
SN - 978-989-758-703-0
IS - 2184-495X
AU - Dehghani, A.
AU - Studencki, L.
PY - 2024
SP - 386
EP - 393
DO - 10.5220/0012691700003702
PB - SciTePress

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