Spatiotemporal Analysis of Shared Situation Awareness among Connected Vehicles

Seungmo Kim

doi:10.1109/IV55156.2024.10588469

Spatiotemporal Analysis of Shared Situation Awareness among Connected Vehicles

Seungmo Kim

Electrical & Computer Engineering

Research output: Contribution to book or proceeding › Conference article › peer-review

Abstract

Shared situation awareness (SSA) has been garnering explosive interest in various applications for intelligent transportation systems (ITS). In addition, the delay-constrained nature of supporting vehicular networks makes it critical to precisely analyze the performance of a SSA procedure. Extending the relevant literature, this paper provides an analysis framework that evaluates the performance of SSA in spatial and temporal aspects simultaneously. Specifically, this paper provides a closed-form probability distribution for the length of time taken for constitution of a SSA among a group of connected vehicles. This paper extends the calculation to investigation of feasibility of SSA in supporting various types of safety messages defined by the SAE J2735.

Original language	English
Title of host publication	35th IEEE Intelligent Vehicles Symposium, IV 2024
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2303-2308
Number of pages	6
ISBN (Electronic)	9798350348811
DOIs	https://doi.org/10.1109/IV55156.2024.10588469
State	Published - 2024
Event	35th IEEE Intelligent Vehicles Symposium, IV 2024 - Jeju Island, Korea, Republic of Duration: Jun 2 2024 → Jun 5 2024

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings
ISSN (Print)	1931-0587
ISSN (Electronic)	2642-7214

Conference

Conference	35th IEEE Intelligent Vehicles Symposium, IV 2024
Country/Territory	Korea, Republic of
City	Jeju Island
Period	06/2/24 → 06/5/24

Keywords

Connected vehicles
Shared situation awareness
Vehicle-to-everything network

Access to Document

10.1109/IV55156.2024.10588469

Cite this

@inproceedings{f390c80dfa0e45f5aec3ab5f04acb396,

title = "Spatiotemporal Analysis of Shared Situation Awareness among Connected Vehicles",

abstract = "Shared situation awareness (SSA) has been garnering explosive interest in various applications for intelligent transportation systems (ITS). In addition, the delay-constrained nature of supporting vehicular networks makes it critical to precisely analyze the performance of a SSA procedure. Extending the relevant literature, this paper provides an analysis framework that evaluates the performance of SSA in spatial and temporal aspects simultaneously. Specifically, this paper provides a closed-form probability distribution for the length of time taken for constitution of a SSA among a group of connected vehicles. This paper extends the calculation to investigation of feasibility of SSA in supporting various types of safety messages defined by the SAE J2735.",

keywords = "Connected vehicles, Shared situation awareness, Vehicle-to-everything network",

author = "Seungmo Kim",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 35th IEEE Intelligent Vehicles Symposium, IV 2024 ; Conference date: 02-06-2024 Through 05-06-2024",

year = "2024",

doi = "10.1109/IV55156.2024.10588469",

language = "English",

series = "IEEE Intelligent Vehicles Symposium, Proceedings",

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

pages = "2303--2308",

booktitle = "35th IEEE Intelligent Vehicles Symposium, IV 2024",

address = "United States",

}

Kim, S 2024, Spatiotemporal Analysis of Shared Situation Awareness among Connected Vehicles. in 35th IEEE Intelligent Vehicles Symposium, IV 2024. IEEE Intelligent Vehicles Symposium, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 2303-2308, 35th IEEE Intelligent Vehicles Symposium, IV 2024, Jeju Island, Korea, Republic of, 06/2/24. https://doi.org/10.1109/IV55156.2024.10588469

TY - GEN

T1 - Spatiotemporal Analysis of Shared Situation Awareness among Connected Vehicles

AU - Kim, Seungmo

PY - 2024

Y1 - 2024

N2 - Shared situation awareness (SSA) has been garnering explosive interest in various applications for intelligent transportation systems (ITS). In addition, the delay-constrained nature of supporting vehicular networks makes it critical to precisely analyze the performance of a SSA procedure. Extending the relevant literature, this paper provides an analysis framework that evaluates the performance of SSA in spatial and temporal aspects simultaneously. Specifically, this paper provides a closed-form probability distribution for the length of time taken for constitution of a SSA among a group of connected vehicles. This paper extends the calculation to investigation of feasibility of SSA in supporting various types of safety messages defined by the SAE J2735.

AB - Shared situation awareness (SSA) has been garnering explosive interest in various applications for intelligent transportation systems (ITS). In addition, the delay-constrained nature of supporting vehicular networks makes it critical to precisely analyze the performance of a SSA procedure. Extending the relevant literature, this paper provides an analysis framework that evaluates the performance of SSA in spatial and temporal aspects simultaneously. Specifically, this paper provides a closed-form probability distribution for the length of time taken for constitution of a SSA among a group of connected vehicles. This paper extends the calculation to investigation of feasibility of SSA in supporting various types of safety messages defined by the SAE J2735.

KW - Connected vehicles

KW - Shared situation awareness

KW - Vehicle-to-everything network

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U2 - 10.1109/IV55156.2024.10588469

DO - 10.1109/IV55156.2024.10588469

M3 - Conference article

AN - SCOPUS:85199784229

T3 - IEEE Intelligent Vehicles Symposium, Proceedings

SP - 2303

EP - 2308

BT - 35th IEEE Intelligent Vehicles Symposium, IV 2024

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 35th IEEE Intelligent Vehicles Symposium, IV 2024

Y2 - 2 June 2024 through 5 June 2024

ER -

Spatiotemporal Analysis of Shared Situation Awareness among Connected Vehicles

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Keywords

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