Can data fusion improve traffic management?
Traffic management is an important tool to relieve congestion problems. For traffic management knowledge about the current traffic situation is essential. Normally, the data that is used to keep traffic operators informed about the current traffic situations, comes from one or more sources, but is not integrated. For example: camera's send their images to the control centre and loop detectors generate data about flows and speeds, but they are shown and used in different ways. The question now is if it is possible to integrate data from different sources (data fusion) in such a way that a better and more complete picture of the current traffic situation is obtained.
Finished reports
- Adaptive ramp metering
- Onderzoek naar de identificatie van kwetsbare wegvakken
- Unbundling of Traffic Flows
- Coordinated signal control for urban networks by using MFD
- Blik op het wegennet
- Congestion minimisation by optimising merging behaviour through Intelligent Transportation Systems
- Percentage of uCAN equipped vehicles needed to estimate traffic speed accurately
- Veiligheid en doorstroming rond incidenten
- Empirical Investigation of Strategy-Based Lane Change Choice
- Multi-objective Traffic Management for Livability
Interested?
If this research question interests you and you want to start an official project, contact ITS Edulab.
Projects in progress
Finished projects
- Dynamic OD matrix estimation using floating car data
- Possibilities of video monitoring
- Incident detection with loop data
- FastLane: modelling and simulation of traffic flow
- Alternative routes A15 Maasvlakte - Vaanplein
- Bottlenecks in road networks due to incidents
- Data fusion of loop detection and travel time measurements
- The relation between traffic flow and lane width
- Real-time capacity estimation for adaptive ramp metering
- Traffic flow and safety during incidents