Multi-Pedestrian Tracking and Map-Based Intention Estimation for Autonomous Driving Scenario

Ali Dehghani, Lucila Studencki

2024

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.

Paper Citation

in Harvard Style

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 - Volume 1: VEHITS; ISBN 978-989-758-703-0, SciTePress, pages 386-393. DOI: 10.5220/0012691700003702

in Bibtex Style

@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 - Volume 1: VEHITS},
year={2024},
pages={386-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012691700003702},
isbn={978-989-758-703-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS
TI - Multi-Pedestrian Tracking and Map-Based Intention Estimation for Autonomous Driving Scenario
SN - 978-989-758-703-0
AU - Dehghani A.
AU - Studencki L.
PY - 2024
SP - 386
EP - 393
DO - 10.5220/0012691700003702
PB - SciTePress