EP4565995A4 - Verfahren, vorrichtung und system zur vorhersage von verkehrsparametern eines strassennetzes - Google Patents

Verfahren, vorrichtung und system zur vorhersage von verkehrsparametern eines strassennetzes

Info

Publication number
EP4565995A4
EP4565995A4 EP23850535.8A EP23850535A EP4565995A4 EP 4565995 A4 EP4565995 A4 EP 4565995A4 EP 23850535 A EP23850535 A EP 23850535A EP 4565995 A4 EP4565995 A4 EP 4565995A4
Authority
EP
European Patent Office
Prior art keywords
road network
traffic parameters
predicting traffic
predicting
parameters
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP23850535.8A
Other languages
English (en)
French (fr)
Other versions
EP4565995A1 (de
Inventor
Suriyanarayanan Venkatesan
Padarn George Wilson
Chen Liang
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Grabtaxi Holdings Pte Ltd
Original Assignee
Grabtaxi Holdings Pte Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Grabtaxi Holdings Pte Ltd filed Critical Grabtaxi Holdings Pte Ltd
Publication of EP4565995A1 publication Critical patent/EP4565995A1/de
Publication of EP4565995A4 publication Critical patent/EP4565995A4/de
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/04—Traffic conditions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/042—Knowledge-based neural networks; Logical representations of neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/0895—Weakly supervised learning, e.g. semi-supervised or self-supervised learning
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/012—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/05—Type of road, e.g. motorways, local streets, paved or unpaved roads
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/10—Number of lanes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Biomedical Technology (AREA)
  • Computational Linguistics (AREA)
  • Analytical Chemistry (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Chemical & Material Sciences (AREA)
  • Biophysics (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Automation & Control Theory (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Traffic Control Systems (AREA)
EP23850535.8A 2022-08-05 2023-07-28 Verfahren, vorrichtung und system zur vorhersage von verkehrsparametern eines strassennetzes Pending EP4565995A4 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
SG10202250678H 2022-08-05
PCT/SG2023/050529 WO2024030077A1 (en) 2022-08-05 2023-07-28 Method, device and system for predicting traffic parameters of a road network

Publications (2)

Publication Number Publication Date
EP4565995A1 EP4565995A1 (de) 2025-06-11
EP4565995A4 true EP4565995A4 (de) 2025-11-26

Family

ID=89849966

Family Applications (1)

Application Number Title Priority Date Filing Date
EP23850535.8A Pending EP4565995A4 (de) 2022-08-05 2023-07-28 Verfahren, vorrichtung und system zur vorhersage von verkehrsparametern eines strassennetzes

Country Status (2)

Country Link
EP (1) EP4565995A4 (de)
WO (1) WO2024030077A1 (de)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118297775B (zh) * 2024-04-12 2024-09-27 中南大学 基于数字孪生技术的城市规划管控系统
CN118735292A (zh) * 2024-06-05 2024-10-01 西南交通大学 基于gcn的城市分级模型的构建方法
CN119514145B (zh) * 2024-10-23 2025-09-30 鹏城实验室 仿真路网生成方法、设备及存储介质

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022129421A1 (en) * 2020-12-18 2022-06-23 Imec Vzw Traffic prediction

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7706964B2 (en) * 2006-06-30 2010-04-27 Microsoft Corporation Inferring road speeds for context-sensitive routing
CN112541638B (zh) * 2020-12-21 2022-07-12 北京邮电大学 一种网联车车辆行程时间估计方法
CN113807578B (zh) * 2021-09-01 2023-12-08 南京航空航天大学 一种基于gcn与强化学习的智能路径推荐方法

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022129421A1 (en) * 2020-12-18 2022-06-23 Imec Vzw Traffic prediction

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
ALI MUHAMMAD AFIF ET AL: "TEST-GCN: Topologically Enhanced Spatial-Temporal Graph Convolutional Networks for Traffic Forecasting", 2021 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), IEEE, 7 December 2021 (2021-12-07), pages 982 - 987, XP034045092, [retrieved on 20220111], DOI: 10.1109/ICDM51629.2021.00110 *
See also references of WO2024030077A1 *
ZHONG WEIDA ET AL: "Heterogeneous Spatio-Temporal Graph Convolution Network for Traffic Forecasting with Missing Values", 2021 IEEE 41ST INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS), IEEE, 7 July 2021 (2021-07-07), pages 707 - 717, XP033982507, [retrieved on 20210921], DOI: 10.1109/ICDCS51616.2021.00073 *

Also Published As

Publication number Publication date
EP4565995A1 (de) 2025-06-11
WO2024030077A1 (en) 2024-02-08

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