Graph representation of road and traffic for autonomous driving

Jianglin Qiao; Dongmo Zhang; Dave de Jonge

doi:10.1007/978-3-030-29894-4_31

Graph representation of road and traffic for autonomous driving

Jianglin Qiao, Dongmo Zhang, Dave de Jonge

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

1 Citation (Scopus)

Abstract

Autonomous driving has the potential to radically change the way vehicles interact each other. This paper aims to develop a formal method to model high level interaction between autonomous vehicles. We introduce a concept of road graph to represent complex road situations such as intersections, road merging, unmarked roads, and traffic hazards. We then extend the concept to further represent status of vehicles, dynamics of traffic and protocols of traffic control. Specifically, we formalise two categories of traffic control protocols, time-based protocols and priority-based protocols.

Original language	English
Title of host publication	PRICAI 2019: Trends in Artificial Intelligence: 16th Pacific Rim International Conference on Artificial Intelligence, Cuvu, Yanuca Island, Fiji, August 26-30, 2019, Proceedings, Part III
Publisher	Springer
Pages	377-384
Number of pages	7
ISBN (Print)	9783030298937
DOIs	https://doi.org/10.1007/978-3-030-29894-4_31
Publication status	Published - 2019
Event	Pacific Rim International Conference on Artificial Intelligence - Duration: 13 Sept 2019 → …

Publication series

Name
ISSN (Print)	0302-9743

Conference

Conference	Pacific Rim International Conference on Artificial Intelligence
Period	13/09/19 → …

Keywords

artificial intelligence
automated vehicles
graphic methods

Access to Document

10.1007/978-3-030-29894-4_31

Cite this

@inproceedings{442cc7458a7e4687953e8a5408027429,

title = "Graph representation of road and traffic for autonomous driving",

abstract = "Autonomous driving has the potential to radically change the way vehicles interact each other. This paper aims to develop a formal method to model high level interaction between autonomous vehicles. We introduce a concept of road graph to represent complex road situations such as intersections, road merging, unmarked roads, and traffic hazards. We then extend the concept to further represent status of vehicles, dynamics of traffic and protocols of traffic control. Specifically, we formalise two categories of traffic control protocols, time-based protocols and priority-based protocols.",

keywords = "artificial intelligence, automated vehicles, graphic methods",

author = "Jianglin Qiao and Dongmo Zhang and Jonge, {Dave de}",

year = "2019",

doi = "10.1007/978-3-030-29894-4_31",

language = "English",

isbn = "9783030298937",

publisher = "Springer",

pages = "377--384",

booktitle = "PRICAI 2019: Trends in Artificial Intelligence: 16th Pacific Rim International Conference on Artificial Intelligence, Cuvu, Yanuca Island, Fiji, August 26-30, 2019, Proceedings, Part III",

note = "Pacific Rim International Conference on Artificial Intelligence ; Conference date: 13-09-2019",

}

Qiao, J, Zhang, D & Jonge, DD 2019, Graph representation of road and traffic for autonomous driving. in PRICAI 2019: Trends in Artificial Intelligence: 16th Pacific Rim International Conference on Artificial Intelligence, Cuvu, Yanuca Island, Fiji, August 26-30, 2019, Proceedings, Part III. Springer, pp. 377-384, Pacific Rim International Conference on Artificial Intelligence, 13/09/19. https://doi.org/10.1007/978-3-030-29894-4_31

Graph representation of road and traffic for autonomous driving. / Qiao, Jianglin; Zhang, Dongmo; Jonge, Dave de.
PRICAI 2019: Trends in Artificial Intelligence: 16th Pacific Rim International Conference on Artificial Intelligence, Cuvu, Yanuca Island, Fiji, August 26-30, 2019, Proceedings, Part III. Springer, 2019. p. 377-384.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Graph representation of road and traffic for autonomous driving

AU - Qiao, Jianglin

AU - Zhang, Dongmo

AU - Jonge, Dave de

PY - 2019

Y1 - 2019

N2 - Autonomous driving has the potential to radically change the way vehicles interact each other. This paper aims to develop a formal method to model high level interaction between autonomous vehicles. We introduce a concept of road graph to represent complex road situations such as intersections, road merging, unmarked roads, and traffic hazards. We then extend the concept to further represent status of vehicles, dynamics of traffic and protocols of traffic control. Specifically, we formalise two categories of traffic control protocols, time-based protocols and priority-based protocols.

AB - Autonomous driving has the potential to radically change the way vehicles interact each other. This paper aims to develop a formal method to model high level interaction between autonomous vehicles. We introduce a concept of road graph to represent complex road situations such as intersections, road merging, unmarked roads, and traffic hazards. We then extend the concept to further represent status of vehicles, dynamics of traffic and protocols of traffic control. Specifically, we formalise two categories of traffic control protocols, time-based protocols and priority-based protocols.

KW - artificial intelligence

KW - automated vehicles

KW - graphic methods

UR - https://hdl.handle.net/1959.7/uws:53623

U2 - 10.1007/978-3-030-29894-4_31

DO - 10.1007/978-3-030-29894-4_31

M3 - Conference Paper

SN - 9783030298937

SP - 377

EP - 384

BT - PRICAI 2019: Trends in Artificial Intelligence: 16th Pacific Rim International Conference on Artificial Intelligence, Cuvu, Yanuca Island, Fiji, August 26-30, 2019, Proceedings, Part III

PB - Springer

T2 - Pacific Rim International Conference on Artificial Intelligence

Y2 - 13 September 2019

ER -

Graph representation of road and traffic for autonomous driving

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