TRAFFIC ACCIDENT PREDICTION SYSTEMS AND METHODS

David Yang; Chaojie Li; Mansoor Al-Thani

TRAFFIC ACCIDENT PREDICTION SYSTEMS AND METHODS

David Yang (Inventor)
, Chaojie Li (Inventor)
, Mansoor Al-Thani (Inventor)

HBKU College of Science and Engineering

Qatar Foundation for Education, Science, and Community Development

Research output: Patent

Abstract

Traffic accident prediction systems and methods are provided. The traffic accident prediction systems and methods include an accident prediction model that utilizes a spatiotemporal attention-based multi-graph convolution neural network to predict the number of traffic accidents in a predetermined region over a predetermined period of time in order to assist with the efficient dispatch of public safety resources to respond to traffic accidents.

Original language	English
Patent number	US2023140289
IPC	G08G 1/ 01 A I
Priority date	2/11/22
Publication status	Published - 4 May 2023

Cite this

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title = "TRAFFIC ACCIDENT PREDICTION SYSTEMS AND METHODS",

abstract = "Traffic accident prediction systems and methods are provided. The traffic accident prediction systems and methods include an accident prediction model that utilizes a spatiotemporal attention-based multi-graph convolution neural network to predict the number of traffic accidents in a predetermined region over a predetermined period of time in order to assist with the efficient dispatch of public safety resources to respond to traffic accidents.",

author = "David Yang and Chaojie Li and Mansoor Al-Thani",

year = "2023",

month = may,

day = "4",

language = "English",

type = "Patent",

note = "US2023140289; G08G 1/ 01 A I",

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TY - PAT

T1 - TRAFFIC ACCIDENT PREDICTION SYSTEMS AND METHODS

AU - Yang, David

AU - Li, Chaojie

AU - Al-Thani, Mansoor

PY - 2023/5/4

Y1 - 2023/5/4

N2 - Traffic accident prediction systems and methods are provided. The traffic accident prediction systems and methods include an accident prediction model that utilizes a spatiotemporal attention-based multi-graph convolution neural network to predict the number of traffic accidents in a predetermined region over a predetermined period of time in order to assist with the efficient dispatch of public safety resources to respond to traffic accidents.

AB - Traffic accident prediction systems and methods are provided. The traffic accident prediction systems and methods include an accident prediction model that utilizes a spatiotemporal attention-based multi-graph convolution neural network to predict the number of traffic accidents in a predetermined region over a predetermined period of time in order to assist with the efficient dispatch of public safety resources to respond to traffic accidents.

M3 - Patent

M1 - US2023140289

ER -

TRAFFIC ACCIDENT PREDICTION SYSTEMS AND METHODS

Abstract

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