A Study of Different Observation Models for Cooperative Localization in Platoons

Elwan Héry; Philippe Xu; Philippe Bonnifait

doi:10.1109/ITSC57777.2023.10422253

A Study of Different Observation Models for Cooperative Localization in Platoons

Elwan Héry, Philippe Xu, Philippe Bonnifait

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Localization and perception for autonomous vehicles are often studied separately. However, they can be regroup on a dynamic map representing the environment of the vehicle. This dynamic map can be exchanged with other vehicles to be fused with their own dynamic maps to increase their accuracy. This paper presents a decentralized data fusion method for cooperative localization based on both Extended Kalman Filter and Covariance Intersection Filter. Different observation models of the relative measurements from the perception (Cartesian and polar relative poses, distances, bearings and relative yaws) are compared. The approach is tested on data for 10 vehicles generated from a real dataset and completed with a simulated perception.

Original language	English
Title of host publication	2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6108-6113
Number of pages	6
ISBN (Electronic)	9798350399462
DOIs	https://doi.org/10.1109/ITSC57777.2023.10422253
Publication status	Published - 1 Jan 2023
Externally published	Yes
Event	26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 - Bilbao, Spain Duration: 24 Sept 2023 → 28 Sept 2023

Publication series

Name	IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
ISSN (Print)	2153-0009
ISSN (Electronic)	2153-0017

Conference

Conference	26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023
Country/Territory	Spain
City	Bilbao
Period	24/09/23 → 28/09/23

Access to Document

10.1109/ITSC57777.2023.10422253

Cite this

Héry, E., Xu, P., & Bonnifait, P. (2023). A Study of Different Observation Models for Cooperative Localization in Platoons. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023 (pp. 6108-6113). (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC57777.2023.10422253

Héry, Elwan ; Xu, Philippe ; Bonnifait, Philippe. / A Study of Different Observation Models for Cooperative Localization in Platoons. 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 6108-6113 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

@inproceedings{dc8845b6a536438cb73942e824479900,

title = "A Study of Different Observation Models for Cooperative Localization in Platoons",

abstract = "Localization and perception for autonomous vehicles are often studied separately. However, they can be regroup on a dynamic map representing the environment of the vehicle. This dynamic map can be exchanged with other vehicles to be fused with their own dynamic maps to increase their accuracy. This paper presents a decentralized data fusion method for cooperative localization based on both Extended Kalman Filter and Covariance Intersection Filter. Different observation models of the relative measurements from the perception (Cartesian and polar relative poses, distances, bearings and relative yaws) are compared. The approach is tested on data for 10 vehicles generated from a real dataset and completed with a simulated perception.",

author = "Elwan H{\'e}ry and Philippe Xu and Philippe Bonnifait",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 ; Conference date: 24-09-2023 Through 28-09-2023",

year = "2023",

month = jan,

day = "1",

doi = "10.1109/ITSC57777.2023.10422253",

language = "English",

series = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "6108--6113",

booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023",

}

Héry, E, Xu, P & Bonnifait, P 2023, A Study of Different Observation Models for Cooperative Localization in Platoons. in 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, Institute of Electrical and Electronics Engineers Inc., pp. 6108-6113, 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, 24/09/23. https://doi.org/10.1109/ITSC57777.2023.10422253

A Study of Different Observation Models for Cooperative Localization in Platoons. / Héry, Elwan; Xu, Philippe; Bonnifait, Philippe.
2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 6108-6113 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Study of Different Observation Models for Cooperative Localization in Platoons

AU - Héry, Elwan

AU - Xu, Philippe

AU - Bonnifait, Philippe

PY - 2023/1/1

Y1 - 2023/1/1

N2 - Localization and perception for autonomous vehicles are often studied separately. However, they can be regroup on a dynamic map representing the environment of the vehicle. This dynamic map can be exchanged with other vehicles to be fused with their own dynamic maps to increase their accuracy. This paper presents a decentralized data fusion method for cooperative localization based on both Extended Kalman Filter and Covariance Intersection Filter. Different observation models of the relative measurements from the perception (Cartesian and polar relative poses, distances, bearings and relative yaws) are compared. The approach is tested on data for 10 vehicles generated from a real dataset and completed with a simulated perception.

AB - Localization and perception for autonomous vehicles are often studied separately. However, they can be regroup on a dynamic map representing the environment of the vehicle. This dynamic map can be exchanged with other vehicles to be fused with their own dynamic maps to increase their accuracy. This paper presents a decentralized data fusion method for cooperative localization based on both Extended Kalman Filter and Covariance Intersection Filter. Different observation models of the relative measurements from the perception (Cartesian and polar relative poses, distances, bearings and relative yaws) are compared. The approach is tested on data for 10 vehicles generated from a real dataset and completed with a simulated perception.

U2 - 10.1109/ITSC57777.2023.10422253

DO - 10.1109/ITSC57777.2023.10422253

M3 - Conference contribution

AN - SCOPUS:85186537141

T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

SP - 6108

EP - 6113

BT - 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023

Y2 - 24 September 2023 through 28 September 2023

ER -

Héry E, Xu P, Bonnifait P. A Study of Different Observation Models for Cooperative Localization in Platoons. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 6108-6113. (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). doi: 10.1109/ITSC57777.2023.10422253

A Study of Different Observation Models for Cooperative Localization in Platoons

Abstract

Publication series

Conference

Access to Document

Fingerprint

Cite this