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Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-1A Traffic Monitoring Jan Breeman Lecture presented at the International.

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Presentation on theme: "Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-1A Traffic Monitoring Jan Breeman Lecture presented at the International."— Presentation transcript:

1 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-1A Traffic Monitoring Jan Breeman Lecture presented at the International GMES-Workshop “The Future of Remote Sensing” Mol, Belgium March 2003

2 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-2A l Introduction to NLR l Traffic monitoring –Traffic monitoring in the Netherlands –Current requirements –Application of Synthetic Aperture Radar l Road pricing –Description –Checking and enforcement –Application of airborne platform l Conclusions Contents

3 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-3A Introduction to NLR l Central institute for aerospace in the Netherlands l Involved in many international research projects l Staff of ~900 (of which ~700 scientists and engineers) l Technical assets –large windtunnels –research simulators –research aircraft –supercomputers –test facilities –calibration facilities

4 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-4A Information and Communication Technology Division activities l information systems for physics simulation, dynamics of multi-body systems, control engineering l command, control, communication and intelligence systems l information (sub)systems for air traffic management l knowledge engineering and computer-based training l computer networking and co-operative environments l end-to-end data processing systems l software for spacecraft development and operations

5 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-5A Why Traffic Monitoring? l Less traffic accidents (2001, all roads) –993 deaths –11,029 injured l Less time lost in traffic (2002) –number of traffic jams: –length of traffic jams: 104,000 km l Less environmental pollution  Better travel information promises 40% improvement in total trip time based on choice of route, modality, time of departure

6 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-6A Goals l Collision warning l Incident detection and object control l Information gathering for policy decisions l Traffic information for drivers l Route planning and multimodal traffic advisory l Dynamic traffic management evolution

7 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-7A Current organisation l Roadside equipment and sensors along all main roads (~ 1100 km) l Regional traffic centres l Central traffic information centre l Information providers (private enterprise)

8 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-8A Organisation in the Netherlands

9 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-9A Current requirements l Speed  1% accuracy l Vehicle flow  1% accuracy l Sample rate  once per minute, every 500m l Vehicle type  3 length categories l Information per lane l Timeliness  maximum three minutes l Availability  ~ 99.9%  all-weather operation! Note: requirements are strongly dependent on specific application!

10 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-10A Traffic monitoring using Synthetic Aperture Radar Example: PHARUS SAR l co-operation between FEL-TNO, NLR, TUD l 5.3 GHz coherent pulse radar l 48 dual polarised patches l 3m x 3m resolution l full polarimetric Reference: van Rossum, van Halsema, Otten, Visser, Pouwels, “The PHARUS familiarisation program”, 4th international airborne remote sensing conference, Ottawa, 1999.

11 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-11A l Zoetermeer A12 west l Moving Target processing: –doppler processing based on nominal traffic speed to focus moving vehicles –deviation from known track yields velocity component lateral to flight vector –transformation to road axes gives vehicle speed l Accuracy speed ~ 1% l Accuracy vehicle detection seemed reasonable, but was not verified

12 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-12A Evaluation  Accuracy vehicle speed is sufficient  Accuracy vehicle detection is promisingmotorcycles?  All-weather operation is possible  Per lane information is a problemincidents!  Timeliness is a problem depending on flight pattern (only lateral velocity component)  Availability could be a problem

13 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-13A l TU Delft Civil Engineering sponsored by Adviesdienst Verkeer en Vervoer l 95% detection and tracking rate l UAV is considered for follow-up Research into driving behaviour from a helicopter

14 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-14A Road pricing l Toll plazas l Electronic toll collection –fixed lane –multi-lane l Kilometre charging –charge per kilometre driven –tariff differentiation based on time and place –issues: privacy and fraud evolution

15 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-15A Kilometre charging

16 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-16A Checking and enforcement l Checking –set-up communication with vehicle On-Board Unit via secure DSRC link –check correct operation based on: OBU status history comparison of reported position with known position check of speed –in case of discrepancy notify back-office l Enforcement –register license plate of offending vehicle

17 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-17A Issues l Checking at fixed locations can be avoided by driver –by using alternate routes –by sending faked information during check l Checking at varying locations can be detected and the location can be broadcast via Internet or GSM/GPRS l Checking from moving vehicles in traffic is inefficient Needed  the element of surprise Solution  a low-flying airborne platform ! (manned/unmanned) Reference: Prof. Wiebren de Jonge (Vrije Universiteit Amsterdam)

18 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-18A Example: FlyCAM l Small unmanned helicopter with gimballed camera l Co-operation between RDM- NLR-TUD l Specifications: –Endurance ~3-4 hours –Gyro Stabilised Sphere –Length: 1.80 m –Height: 0.75 m –Engine: 60 cc –Rotor diameter: 2.14 m –Weight: 9.0 kg –Payload+fuel: 10 kg

19 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-19A Problem areas  Power needed for DSRC transmitter –infrared communication needs less power  Short range of DSRC radio communication (~30 m) –range of infrared communication is larger (~300 m)  Short range is also required for license plate readout –lighting could be a problem  Environmental concerns  noise!  Collision risk at low altitude  Protection of privacy  real and perceived!

20 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-20A Conclusions l Traffic Monitoring –High/medium altitude UAV/SAR for traffic monitoring is technically feasible –It does not add significantly to existing infrastructure on main roads, but could be a viable solution for secondary roads l Road Pricing –Low altitude UAV with DSRC and camera could be a good solution for checking and enforcement for Road Pricing –Several problems remain to be solved

21 Nationaal Lucht- en Ruimtevaartlaboratorium National Aerospace Laboratory NLR DXXX-21A Further reading


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