Electronic Toll Collection Technologies for Road PricingWorld class In - PDF document

1 Page 1 Electronic Toll Collection Techno
Page 1 Electronic Toll Collection Technologies for Road PricingWorld class Intelligent Transport Systems for Road User Charging and Traffic Surveillance Furnes, Per Jarle, Q-Free ASARuja, Sascha, Q-Free ASAVoss, Stefan, University of HamburgTCL workshop -Asilomar –27. –29. June 2011 Congestion Charging on R

2 oadsCongestion Charging is not newDupuit
oadsCongestion Charging is not newDupuit (Fr, 1849), Pigou (1920), Knight (1924), Walters (1961), Vickery (1969)Newbery (1990), Lindsey & Verhoef (2001), Lawphongpanich et al. (2006), Small & Verhoef (2007), Tsekeris & Voß (2009)Economic argumentsTechnology choices Conceptual Approaches to Managing Congesti

3 onMaximize Flows: (can lead to inherent
onMaximize Flows: (can lead to inherent instability and heighten the risk of unpredictable congestion)Optimize flows taking into account the balance between supply and demand for road sready to pay in order to use the road [and for better Technical vs. economical optimization –need new hybrid Static vs Dyn

4 amic Charging(flat toll) Determined a pr
amic Charging(flat toll) Determined a priori, constant over given (scheduled) Determined a common peak vs off peak(Responsive) vary in real prevailing traffic conditionsTypes of Congestion ChargingRoads, tunnels, bridges, Single or multiple points[TDP based] De Palma and Lindsey (2009) Integrated framework

5 for the evaluation of road pricing sche
for the evaluation of road pricing schemes Theodore Tsekeris & Stefan Voß (2009)Choosing technology as a function Technology alternatives -GNSS/DSRC and VIDEO Technology Alternatives Tech-Physical Vehicle Weather Vehicle Reg. YesHighNoYesNo limitNot sensitiveNoYesHighLow-MediumYesYesHighNot sensitiveNoV

6 ideoNoMediumMediumYesNoHighSensitiveYesY
ideoNoMediumMediumYesNoHighSensitiveYesYesHighLowYesYesSensitiveNoNoMediumHighYesNoStopNot sensitiveNo Key questions related to Total Cost of Ownership ModellingCan TCO modeling explain customers’ technology preferences ?Can TCO figures be accurately quantified to advise on a certain technology ?Can TCO cal

7 culations predict certain strategies?Doe
culations predict certain strategies?Does TCO really matter for our customers investment phase ? Total Cost of Ownership Model OPEX System magnitude (Front ends, mobile enforcement, tags) Traffic volume Tag ALPR hit rate Unreadable License PlateTotal cost Enforcement Back Office Total cost of Ownership

8 validation based on empirical data•Empi
validation based on empirical data•Empirical data•Amdal & Welde (2004)–Sensitivity analysis on Norway’s toll collection projects –Findings: OPEX ranging from 7-25% relative to income, tag proliferation sensitivity, system magnitude sensitivity•Oslo: OPEX :8% relative to income in 2006 (75% hit rate, 85% ta

9 gs)•Stockholm: OPEX 25% relative to inc
gs)•Stockholm: OPEX 25% relative to income in �2008 (95% hit rate, 0% tags) •London: OPEX 67% relative to income in 2003 [Levinson and Odlyzko 2008]•Validation of Model•Identified same effects as (Amdahl & Welde 2004) when using Norwegian manual labor •Identified same OPEX levels as in Oslo, Stockho

10 lm and London when same ALPR hit rates
lm and London when same ALPR hit rates and tag proliferation levels were used.•Major model limitations (same for both ALPR, DSRC, GNSS)•Maintenance is linear to the system magnitude, 15%•Translating scheme rules and enforcement procedures into a unified model for back office operating costs is highly chal

11 lenging Page 11Technology Choice –Crossi
lenging Page 11Technology Choice –Crossing Point GNSS/DSRC Number of roads to cover gives must be As for Road systems it is having a high number of cars for a small number of roads in a city.Crossing point where GNSS or technology, based on number of road segments and applicable for tolls Vehicles : equal M

12 odeling results: DSRC versus ALPR 92%10
odeling results: DSRC versus ALPR 92%100% Scenario Investigations and Details ChargingTollingVehicle ChargingCharging principlePointDistanceContinuousVehicles to charged (pr 400000800000850000Road Infrastructure Size 100250012500Chargeable Road 555Usage frequency pr day0.728Enforcement operationStationary

13 OfflineStationary OfflineProof verificat
OfflineStationary OfflineProof verificationMandatoryMandatorySpotPayment ModeMixedMixedMixedCharging Fee pr km0.070.030.07Parameterization of ETC charging scenarios Technology Parameter Settings Video DSRC GNSSOBU proliferation0%90% (unequipped through Video)OBU acquisition and distribution cost €015350OBU

14 transaction unit000.03Read Rate/Error r
transaction unit000.03Read Rate/Error rate97%99%99%detection coverage (ratio of chargeable segments)100%100%20% Mobile Enforcement (ratio of chargeable segments)0%0%10%Back office stationary cost 500000500000500000Back Office fee pr 0.20.20.2Parameterization of Implementation strategies The Scenario –Strat

15 egy map, summary of TCO modeling VideoD
egy map, summary of TCO modeling VideoDSRCGNSSCityZoneCongestionCharging9,507,3017,30MotorwayFinancing9,809,4012,40TruckTolling378,0039,9038,50 Technology grid based on the ratio between TCO and revenues.The latter is given in percentages. Cell values are highlighted in Page 16Modelling Results TechnologyV

16 ideoDSRCGNSSChargingAutomatedbillingthro
ideoDSRCGNSSChargingAutomatedbillingthroughaccuratevideoandALPRLowcostOBUHighOBUCAPEXandOPEX.VulnerabletolargeamountofunregisteredusersandmanualhandlingcostsBestfitasOBUcostsarelowforahighnumberofusers.HighOBUCAPEXandOPEX.frequencyincreasingwithnumberofusersVehicle ChargingHighfrontendinfrastructurecostsand

17 operationcosts(andlossfromforeignusers)H
operationcosts(andlossfromforeignusers)HighfrontendinfrastructurecostswhentherearefewusersandlargeroadBestfitwithmanysegmentsandfewusersbutwhicharefrequentlybeingchargedThe Scenario –Strategy map, summary of TCO modeling Page 17 Multi Lane Free Flow Traffic Back Office Truck TollingVideo Tolling Thank you!