Research Grant
[Cite as https://purl.org/au-research/grants/arc/LP200301389]
Researchers:
Egemen Tanin
(Chief Investigator)
,
Mohsen Ramezani
(Chief Investigator)
,
Neema Nassir
(Chief Investigator)
,
Prof Majid Sarvi
(Chief Investigator)
,
Saeed Asadi Bagloee
(Chief Investigator)
View all 8 related researchers
Brief description Predictive Analytics and Real-time Traffic Control for Urban Corridors. This project aims to develop predictive data analytics and real-time traffic control and safety models for multimodal management of urban corridors, serving two salient objectives: (1) optimising person-throughput of multimodal traffic; while (2) minimising safety risks for all modes. The outcome will be an automated, sensor-based platform to monitor traffic flows from all modes and make proactive and coordinated control decisions in real-time. The expected benefits are profound; the developed algorithms and platform will significantly reduce traffic congestion, travel delays and safety risks for all modes of transport, especially for vulnerable road users (e.g. pedestrians and cyclists).
Funding Amount $746,657
Funding Scheme Linkage Projects
- PURL : https://purl.org/au-research/grants/arc/LP200301389
- ARC : LP200301389