Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones

Qishen  Zhou; Roozbeh Mohammadi; Weiming Zhao; Kaihang  Zhang; Lihui  Zhang; Yibing  Wang; Claudio Roncoli; Simon  Hu

doi:10.1109/MT-ITS49943.2021.9529337

Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones

Qishen Zhou, Roozbeh Mohammadi^*, Weiming Zhao, Kaihang Zhang, Lihui Zhang, Yibing Wang, Claudio Roncoli, Simon Hu

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Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

47 Lataukset (Pure)

Abstrakti

Queue profile is a crucial measure for traffic management in the vicinity of signalized intersections. In this study, we develop a method to identify queue profile using high resolution data, which can be provided from various sources such as drones. Our methodology has three main components which are signal state estimation, queue profile identification, and lane detection. The developed algorithms are tested on the real-world dataset collected by drones as a case study for validation. Remarkably, our method only uses drone data as input and it is independent from any other data source such as geographic information system data. The results demonstrate satisfactory performance of the methodology in extracting queue profile information from raw drone data. The developed algorithm can be also applied on data collected via connected vehicles in future.

Alkuperäiskieli	Englanti
Otsikko	2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2021
Kustantaja	IEEE
Sivumäärä	6
ISBN (elektroninen)	978-1-7281-8995-6
DOI - pysyväislinkit	https://doi.org/10.1109/MT-ITS49943.2021.9529337
Tila	Julkaistu - 16 kesäk. 2021
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisuussa
Tapahtuma	IEEE International Conference on Models and Technologies for Intelligent Transportation Systems - Online, Heraklion, Kreikka Kesto: 16 kesäk. 2021 → 17 kesäk. 2021 Konferenssinumero: 7 https://ieeexplore.ieee.org/xpl/conhome/9529260/proceeding https://www.mt-its2021.tse.bgu.tum.de/

Conference

Conference	IEEE International Conference on Models and Technologies for Intelligent Transportation Systems
Lyhennettä	MT-ITS
Maa/Alue	Kreikka
Kaupunki	Heraklion
Ajanjakso	16/06/2021 → 17/06/2021
www-osoite	https://ieeexplore.ieee.org/xpl/conhome/9529260/proceeding https://www.mt-its2021.tse.bgu.tum.de/

Pääsy asiakirjaan

10.1109/MT-ITS49943.2021.9529337

ENG_Zhou_et_al_Queue_profile_identification_IEEE_MT_ITS_2021Accepted author manuscript, 879 KB

https://ieeexplore.ieee.org/document/9529337

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Linkki julkaisuun Scopuksessa

1 Aktiivinen

FINEST TWINS: Establishment of Smart City Center of Excellence
Nieminen, M.
01/12/2019 → 30/11/2026
Projekti: EU: Framework programmes funding

Siteeraa tätä

Zhou, Q., Mohammadi, R., Zhao, W., Zhang, K., Zhang, L., Wang, Y., Roncoli, C., & Hu, S. (2021). Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones. teoksessa 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2021 IEEE. https://doi.org/10.1109/MT-ITS49943.2021.9529337

@inproceedings{1d56f21a1c5546c1aad67105b99d26b1,

title = "Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones",

abstract = "Queue profile is a crucial measure for traffic management in the vicinity of signalized intersections. In this study, we develop a method to identify queue profile using high resolution data, which can be provided from various sources such as drones. Our methodology has three main components which are signal state estimation, queue profile identification, and lane detection. The developed algorithms are tested on the real-world dataset collected by drones as a case study for validation. Remarkably, our method only uses drone data as input and it is independent from any other data source such as geographic information system data. The results demonstrate satisfactory performance of the methodology in extracting queue profile information from raw drone data. The developed algorithm can be also applied on data collected via connected vehicles in future.",

keywords = "queue length, traffic management, high resolution data, trajectory data, clustering",

author = "Qishen Zhou and Roozbeh Mohammadi and Weiming Zhao and Kaihang Zhang and Lihui Zhang and Yibing Wang and Claudio Roncoli and Simon Hu",

note = "| openaire: EC/H2020/856602/EU//FINEST TWINS; IEEE International Conference on Models and Technologies for Intelligent Transportation Systems , MT-ITS ; Conference date: 16-06-2021 Through 17-06-2021",

year = "2021",

month = jun,

day = "16",

doi = "10.1109/MT-ITS49943.2021.9529337",

language = "English",

booktitle = "2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2021",

publisher = "IEEE",

address = "United States",

url = "https://ieeexplore.ieee.org/xpl/conhome/9529260/proceeding, https://www.mt-its2021.tse.bgu.tum.de/",

}

Zhou, Q, Mohammadi, R , Zhao, W, Zhang, K, Zhang, L, Wang, Y, Roncoli, C & Hu, S 2021, Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones. julkaisussa 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2021. IEEE, IEEE International Conference on Models and Technologies for Intelligent Transportation Systems , Heraklion, Kreikka, 16/06/2021. https://doi.org/10.1109/MT-ITS49943.2021.9529337

Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones. / Zhou, Qishen ; Mohammadi, Roozbeh ; Zhao, Weiming; Zhang, Kaihang ; Zhang, Lihui ; Wang, Yibing ; Roncoli, Claudio; Hu, Simon .

2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2021. IEEE, 2021.

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

TY - GEN

T1 - Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones

AU - Zhou, Qishen

AU - Mohammadi, Roozbeh

AU - Zhao, Weiming

AU - Zhang, Kaihang

AU - Zhang, Lihui

AU - Wang, Yibing

AU - Roncoli, Claudio

AU - Hu, Simon

N1 - Conference code: 7

PY - 2021/6/16

Y1 - 2021/6/16

N2 - Queue profile is a crucial measure for traffic management in the vicinity of signalized intersections. In this study, we develop a method to identify queue profile using high resolution data, which can be provided from various sources such as drones. Our methodology has three main components which are signal state estimation, queue profile identification, and lane detection. The developed algorithms are tested on the real-world dataset collected by drones as a case study for validation. Remarkably, our method only uses drone data as input and it is independent from any other data source such as geographic information system data. The results demonstrate satisfactory performance of the methodology in extracting queue profile information from raw drone data. The developed algorithm can be also applied on data collected via connected vehicles in future.

AB - Queue profile is a crucial measure for traffic management in the vicinity of signalized intersections. In this study, we develop a method to identify queue profile using high resolution data, which can be provided from various sources such as drones. Our methodology has three main components which are signal state estimation, queue profile identification, and lane detection. The developed algorithms are tested on the real-world dataset collected by drones as a case study for validation. Remarkably, our method only uses drone data as input and it is independent from any other data source such as geographic information system data. The results demonstrate satisfactory performance of the methodology in extracting queue profile information from raw drone data. The developed algorithm can be also applied on data collected via connected vehicles in future.

KW - queue length

KW - traffic management

KW - high resolution data

KW - trajectory data

KW - clustering

UR - http://www.scopus.com/inward/record.url?scp=85115831602&partnerID=8YFLogxK

U2 - 10.1109/MT-ITS49943.2021.9529337

DO - 10.1109/MT-ITS49943.2021.9529337

M3 - Conference contribution

BT - 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2021

PB - IEEE

T2 - IEEE International Conference on Models and Technologies for Intelligent Transportation Systems

Y2 - 16 June 2021 through 17 June 2021

ER -

Queue Profile Identification at Signalized Intersections with High-Resolution Data from Drones

Abstrakti

Conference

Pääsy asiakirjaan

SFX-saatavuus

Muut tiedostot ja linkit

Sormenjälki

Projektit

FINEST TWINS: Establishment of Smart City Center of Excellence

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