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
- Multi-objective Traffic Management for Livability
- Design of a Subnetwork Controller Based on MFD’s and Perimeter Flows
- Application of MFDs to Dynamic Traffic Management
- Evaluating Multi-Class Model Predictive Control
- Blik op het wegennet
- HOT lanes - Implementation considerations and assessment
- Modelling merging behaviour on freeway on-ramps
- A Framework for the Modeling and Ex-Ante Evaluation of Coordinated Network Management
- Active platoon formation in congestion with Dynamic Dedicated Lane Sections
- Concept Design and Evaluation of Traffic Management in Beijing
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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