Traffic Monitoring

Nationaal Lucht- en RuimtevaartlaboratoriumNational Aerospace Laboratory NLR

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Traffic Monitoring

Jan Breeman

Lecture presented at the International GMES-Workshop

“The Future of Remote Sensing”

Mol, Belgium

17-18 March 2003


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Introduction to NLR

Traffic monitoring– Traffic monitoring in the Netherlands– Current requirements– Application of Synthetic Aperture Radar

Road pricing– Description– Checking and enforcement– Application of airborne platform

Conclusions

Contents


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Introduction to NLR

Central institute for aerospace in the Netherlands

Involved in many international research projects

Staff of ~900 (of which ~700 scientists and engineers)

Technical assets– large windtunnels– research simulators– research aircraft– supercomputers– test facilities– calibration facilities


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Information and Communication Technology Division activities

information systems for physics simulation, dynamics of multi-body systems, control engineering

command, control, communication and intelligence systems

information (sub)systems for air traffic management

knowledge engineering and computer-based training

computer networking and co-operative environments

end-to-end data processing systems

software for spacecraft development and operations


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Why Traffic Monitoring?

Less traffic accidents (2001, all roads)– 993 deaths– 11,029 injured

Less time lost in traffic (2002)– number of traffic jams: 32.897– length of traffic jams: 104,000 km

Less environmental pollution

Better travel information promises 40% improvement in total trip time based on choice of route, modality, time of departure


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Goals

Collision warning

Incident detection and object control

Information gathering for policy decisions

Traffic information for drivers

Route planning and multimodal traffic advisory

Dynamic traffic management

evol

utio

n


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Current organisation

Roadside equipment and sensors along all main roads (~ 1100 km)

Regional traffic centres

Central traffic information centre

Information providers (private enterprise)


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V e h ic led e te c to rs

(in d u c tiv e lo o p s )

N ation alT raffic

In form ationC en tre(T IC )

In te rn e t

R D S /T M C

R ad ioB ro ad c as t

V id e oC am e ras

M e te oS e n s o rs

R o ad C o n d itio nS e n s o rs

R eg ion al T rafficC en tres

(5 )

G S M /G P R S

A lp h an u m e ricD is p lay P an e l

S pe e dA dv is o ry Pa n e l

O b je c t C o n tro l(b rid g e s , ram p s )

In form ationP rov id ers

Organisation in the Netherlands


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Current requirements Speed 1% accuracy

Vehicle flow 1% accuracy

Sample rate once per minute, every 500m

Vehicle type 3 length categories

Information per lane

Timeliness maximum three minutes

Availability ~ 99.9% all-weather operation!

Note: requirements are strongly dependent on specific application!


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Traffic monitoring using Synthetic Aperture Radar

Example: PHARUS SAR

co-operation between FEL-TNO, NLR, TUD

5.3 GHz coherent pulse radar

48 dual polarised patches

3m x 3m resolution

full polarimetric

Reference: van Rossum, van Halsema, Otten, Visser, Pouwels, “The PHARUS familiarisation program”, 4th international airborne remote sensing conference, Ottawa, 1999.


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Zoetermeer A12 west

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

Accuracy speed ~ 1%

Accuracy vehicle detection seemed reasonable, but was not verified


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Evaluation

Accuracy vehicle speed is sufficient

Accuracy vehicle detection is promising motorcycles?

All-weather operation is possible

Per lane information is a problem incidents!

Timeliness is a problem depending on flight pattern (only lateral velocity component)

Availability could be a problem


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TU Delft Civil Engineering sponsored by Adviesdienst Verkeer en Vervoer

95% detection and tracking rate

UAV is considered for follow-up

Research into driving behaviour from a helicopter


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Road pricing

Toll plazas

Electronic toll collection– fixed lane– multi-lane

Kilometre charging– charge per kilometre driven– tariff differentiation based on time and place– issues: privacy and fraud

evol

utio

n


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Kilometre charging

G S MN etw ork

G P S S a tellites

A ssis tan ce D a ta

P osit ion E stim ate

R oa dsideC heck ing

P osit ion E stim

ate

O n-B o a rd U nit(O B U )

D ed ica ted S h ort Ran ge

C om m un ication

(D S R C )

G S M /G P R S /U M T S

C h a llen ge

K ilom eter D eclara tionT ariffR esp on se


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Checking and enforcement

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

Enforcement– register license plate of offending vehicle


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Issues

Checking at fixed locations can be avoided by driver– by using alternate routes– by sending faked information during check

Checking at varying locations can be detected and the location can be broadcast via Internet or GSM/GPRS

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)


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Example: FlyCAM

Small unmanned helicopter with gimballed camera

Co-operation between RDM-NLR-TUD

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


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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!


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Conclusions

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

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


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Further readingTraffic Management: http://www.rws-avv.nl/testcentrum/

http://www.minvenw.nl/rws/mdi/home/index.htmhttp://www.tic-nl.org

PHARUS: http://www.tno.nl/instit/fel/os/fac/ra_fac_pharus.htmlhttp://www.nlr.nlhttp://irctr.its.tudelft.nl/

Driving Behaviour: http://www.rws-avv.nlhttp://www.citg.tudelft.nl

Road Pricing: http://wwww.ertico.com/activiti/projects/rci/rci_con.htmhttp://www.cs.vu.nl/~wiebren/TIP/

FlyCam: http://www.flycam.tudelft.nlhttp://www.rdmt.nl/index.html

Documents

Traffic Monitoring