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Grant Award View - GA28763-V2
Data-driven simulation of large traffic networks using trajectory data
GA ID:
GA28763-V2
Agency:
Australian Research Council
Approval Date:
27-Nov-2018
Variation Publish Date:
3-Sep-2019
Variation Date:
3-Sep-2019
Category:
Humanities, Arts and Social Sciences (HASS) Research
Grant Term:
1-Jun-2019 to 29-Nov-2022
Value (AUD):
$385,085.00
(GST inclusive where applicable)
Varies:
GA28763
- Data-driven simulation of large traffic networks using trajectory data
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 18/19 Discovery
Grant Program:
Discovery Early Career Researcher Award
Grant Activity:
Data-driven simulation of large traffic networks using trajectory data
Purpose:
This project aims to develop a low-cost, data-driven framework that builds a traffic simulation model automatically and directly from vehicle trajectory data to enable rapid and reliable analysis of large-scale traffic networks. The project expects to generate new knowledge in the area of transport engineering using an innovative approach to inferring travel behaviours, movement patterns and traffic dynamics from increasingly available urban trajectory data. Expected outcomes include improved decision support for urban planners and traffic operators and enhanced traffic management and incident response capabilities, providing significant social, economic and environment benefits through optimised road use and urban flow.
GO ID:
GO Title:
Discovery Early Career Researcher Award commencing in 2019
Internal Reference ID:
DE19 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The University of Queensland
Recipient ABN:
63 942 912 684
Grant Recipient Location
Suburb:
ST LUCIA
Town/City:
ST LUCIA
Postcode:
4067
State/Territory:
QLD
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
QLD
Postcode:
4067
Country:
AUSTRALIA