gina –gnss for innnovative road applications-

GINA –GNSS FOR INNNOVATIVE ROAD APPLICATIONS-

The adoption of EGNOS/GALILEO for RUC and VAS for the Road Sector

ITS World Congress, Busan 20101st October 2010

Brussels

CONTENTS

1. GINA concept

2. GINA exhaustive trial findings:

Context and general description Charging related performances Distance and position performances Key-findings

3. GINA end-to-end trial status

4. Conclusions

20/04/23 PREPARATORY MEETING FOR WORKSHOP#1

GNSS for Innovative road Applications

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THE GINA PROJECT

GINA – GNSS FOR INNOVATIVE ROAD APPLICATIONS

FP7 project, co-financed by EC under 1st Galileo Call

FP7 GALILEO Call 1, Topic GALILEO-2007-1.1-01 Innovative GNSS-based Road Applications

Not another proof of concept: large scale demonstrator of a GNSS-based RUC & VAS scheme using the Dutch ABvM system and requirements defined by real end users as a reference

Project schedule: 24 months

GINA main OBJECTIVES:Analysis of context of a nation-wide GNSS-based RUC (and VAS) with especial emphasis on market and business potential

Trials: Dutch ABvM as a reference

A solid dissemination strategy


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THE GINA CONSORTIUM

GINA - GNSS FOR INNOVATIVE ROAD APPLICATIONS

Consortium covering the whole value chain


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THE USE OF POSITION INTEGRITY IN ROAD PRICINGUse of Geo-fencing process based on POSITION INTEGRITY to ensure reliability of Road User Charging scheme) (concept introduced for Civil Aviation SoL for which EGNOS is designed)

27/10/2010

GINA - GNSS FOR INNOVATIVE ROAD APPLICATIONS

1. Computation of position + bounding of position error (with a very high probability ~99.99%)

2. Vehicle charged only when 1 or more PLs (=error boundaries) totally inside the geo-object=> geo-fencing based on PLs (not just on calculated position).

Highly reliable geo-fencing process precluding wrong identifications

Error


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GINA TRIALS OVERVIEW


Large-scale demonstrator at national scale (in the Netherlands) for RUC and VAS

OBJECTIVE: Demonstrate how and with what performance European GNSS infrastructure (e.g. EGNOS) and other innovative GNSS-based technologies (e.g. use of position integrity) can enhance RUC schemes based on satellite positioning.

2 trials levels:

No. VEHICLES

PERIODVEHICLES&DRIVERS

VASREFERENCE

SYSTEMCANBUS EVALUATION SCENARIOS

24

weeksControlled by project

NO YES YESGNSS

performanceRoutes defined by

project

100 6 monthsVolunteers

(ARVAL customers)

YES NO NOApplication

levelUncontrolled, not fixed


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CONTENTS

1. GINA concept




4. Conclusions

20/04/23 GINA – GNSS FOR INNOVATIVE ROAD APPLICATIONS


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3 configurations of OBUs to assess performance (all of them implementing the described “GINA solution”):

Assessment of performances by comparing system outputs and truth (thanks to a highly sophisticated trajectography system):Charging

Performance of distance measurement

Performance of Geo-Objects identification (wrong /mis- ID, distance accuracy within geo-objects)

GNSS positioning performance (accuracy, integrity, availability)

2 campaigns: GMV vehicle (main source of data) Navteq vehicle (a different approach)

EXHAUSTIVE TRIALS CONTEXT (I)


Configuration

GPS only

GPS+CANBUS (odometer)

GPS+CANBUS (odometer)+EGNOS

CANBUS (odometer) is only used for distance calculation and is not part of the positioning solution


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EXHAUSTIVE TRIALS CONTEXT (II)

20/04/23

Route 1 – Motorway, urban Route 2 – Urban Route 3 – Urban, motorway

Amsterdam The Hague Rotterdam

Large number of narrow streets and numerous turns in urban roads

Large motorway section with some small roads in urban environment. Some tunnels

Urban roads. Some tall buildings and urban canyons. Some tunnels


Campaign: 5th March 2010 to 5th April 2010

3 test routes: realistic and challenging for GNSS

≥20 repetitions per route => statistically significant results

Fully operational smart OBU with real time capabilities

For better analysis flexibility (3 configurations) raw data registered in OBU and post-processed


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EXHAUSTIVE TRIALS CONTEXT (III)

Performances in a non-urban environment have been also evaluated, analyzing a highway segment of 10 km.

A huge amount of data has been collected. Additional specific cases of interest for RUC can be isolated and further analyses possible.

Highway scenario

GINA – GNSS FOR INNOVATIVE ROAD APPLICATIONS 20/04/23


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EXHAUSTIVE TRIALS CONTEXT (IV)

All anticipated routes completed the required number of times

Some routes performed additional times where possible

Large amount of data generated

All data successfully recorded and stored

20/04/23

Trial Plan Actual

Number of Journeys

60 (at least 20 on each route)

68 (Den Haag + 5, Rotterdam +3)

Number of Routes 3 3

Total driving time (hours)

90 122

Number of position points

obtained

324,000(for analysis this

figure x4)

438,861 (for analysis this

figure x4)

Approximate distance driven

(km)

Amsterdam 1640Den Haag 694Rotterdam 1158

---Total 3492

Amsterdam 1504Den Haag 923Rotterdam 1294

---Total 3721

Number of Geo-objects

49 51


Some figures


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CONTENTS

1. GINA concept




4. Conclusions



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OFFICIAL Geo-Objects (very similar to the ones used in ABvM trials)

Cordon areas Highway segments

(Challenging scenarios, such as parallel roads were part of the geo-objects list included in the routes)

CHALLENGING Geo-Objects Small Geo-Objects, especially

inside urban areas, tunnels

Area Geo-Objects (e.g. nested geo-objects of different sizes in order to determine geo-object identification performance as a function of the geo-object size)


GEO-OBJECTS DETECTION (1/2)


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Metric Calculation

Mis-detection

Incorrect Geoobject Identification,

Where GEOOBJECT_X = 0 TRUTH_GEOOBJECT_X = 1 or

Where GEOOBJECT_X = 1 TRUTH_GEOOBJECT_X = 0

A discrete variable: Correct detectionor Mis-detection (i.e. undetected although it actually took place) Wrong detection (i.e. detected although it actually did not take

place).

GEO-OBJECTS DETECTION (2/2)

100% Official Geo-Objects detected by all OBU configurations0% wrong identification of ALL Geo-Objects (official &

challenging) thanks to the use of GINA geofencing technique, based on position integrity => key to protect users against overcharging!

Key perform

ance for a

ny

charging scheme

In a discrete RUC system this would imply 0% charging error



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DISTANCE-BASED CHARGING PERFORMANCE. HIGHWAY SCENARIO.

20/04/23

Charging error (%) density function

Charging error (%) cumulative distribution

Mean charging deviation between -0.07% and -0. 15% over all journeys.

Maximum overcharging (for 99% of journeys) smaller than:

0.39% for GPS only solution 0.22% for EGNOS + CANBUS solution



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DISTANCE-BASED CHARGING PERFORMANCE. ALL JOURNEYS.

20/04/23 PRESENTATION TITLE VERDANA (9)

Mean charging deviation between -0.44% and -0.57% over all journeys.

Overcharging (for 95% of journeys) smaller than:

1.01% for GPS only solution 0.23% for EGNOS+CANBUS solution


Charging error (%) density function

Charging error (%) cumulative distribution

In addition, 0% of overcharging can be guaranteed with very high probability if applying integrity techniques to the distance measurement but at the expenses of increasing the average charging error to about -1% (in line with ABvM specs).


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CONTENTS

1. GINA concept




4. Conclusions



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DISTANCE ACCURACY

20/04/23

Metric Description Calculation

Relative Distance Deviation

Relative deviation in the overall calculated length of the journey between the truth and test devices.

(OBU distance– reference distance) / reference distance * 100%


Distance error (%) density function

Distance error (%) cumulative distribution

CANBUS odometer improves distance performance Mean distance error (either absolute or journey-

based) is below 0.3% for all solutions (0.05% with CANBUS)

A Distance-based Charging scheme could benefit from a connection to a CANBUS although “GNSS only” solution provides satisfactory performances


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GNSS POSITIONING PERFORMANCE. HIGHWAY SCENARIO.

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Horizontal position error cumulative distribution

Horizontal protection level cumulative distribution

Position errors much smaller 3m position error (at 95%) with

EGNOS. EGNOS provides substantial

accuracy improvement in “clean environments” (reduced multipath)

All Protection levels less than 7m 50% of the time

EGNOS based PL smaller than 15 m 99% of the time

EGNOS improves integrity performances in “clean environments”

EGNOS integrity risk 3x10-4 in clean environments (RAIM integrity risk 1x10-3 in all scenarios)

GINA – GNSS FOR INNOVATIVE ROAD APPLICATIONS 20/04/23 Page 19


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CONTENTS

1. GINA concept




4. Conclusions



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KEY FINDINGS OF EXHAUSTIVE TRIALS (1/4)

CHARGING PERFORMANCES

100% Official Geo-Objects detected

0% wrong identification of ALL Geo-Objects (official & challenging) thanks to the use of GINA geo-fencing technique, based on position integrity

For a discrete RUC system this would imply 0% charging error Distance based mean charging deviation in line with expected

performances based on ABvM in all scenarios; much better in highway scenario



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KEY FINDINGS OF EXHAUSTIVE TRIALS (2/4) POSITIONING PERFORMANCE

ACCURACY: The configuration using EGNOS was the most accurate for the 99th percentile and also had the lowest maximum position error. In addition, in highway scenario EGNOS improves susbtantially accuracy (from 6 to 3 m at 95%).

RAIM techniques: Urban environments introduce large errors due to local effects. GNSS can benefit from RAIM techniques. In particular, RAIM integrity is the most suitable for the GINA proposed solution (geofencing based on position integrity).

GINA – GNSS FOR INNOVATIVE ROAD APPLICAITONS


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KEY FINDINGS OF EXHAUSTIVE TRIALS (3/4)

ENVIRONMENT (urban/highway) substantially affects performance but good results can be achieved in all scenarios.

GINA SOLUTION (geofencing based on integrity) plays a key role for a reliable (protecting the user) detection of Geo-objects

CANBUS (odometer) role: decrease distance errors by a factor of 5 to 10 but GNSS only solutions seem enough for foreseable requirements

Appropriate definition of Geo-objects is relevant for optimising charging performances

Proposed technology provides a valid solution for road/urban and different charging schemes (continuous/discrete) fulfilling the expected performances



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CONTENTS

1. GINA concept




4. Conclusions



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GINA. END2END TRIALSNo. Vehicles

Period Vehicles&drivers

VAS Reference Systems

CANBUS Evaluation Scenarios

1006

months

Volunteers (ARVAL

customers)YES NO NO

Application level

Uncontrolled, not fixed

OBJECTIVES

1. Functionality/usage analysis: Overall assessment of capabilities of the system from different perspectives

Capability to generate invoices, Evaluation of drivers reaction and feedback, Provisioning of added-value services (PAYD, traffic information

generation…) Mobility-related issues etc.

2. Data analysis: exhaustive performance analysis for those variables with no need of a reference system

Capability of getting repeatable results for same conditions Variability of average cost per km in different geo-objects and

circumstances Etc.



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GINA. END2END TRIALS

The DRIVERS => 100 volunteers

Automatic downloading of data recorded to Palview GMV’s platform, making data available for analysis

No post-processing: geo-objects defined considering driving habits of drivers and programmed into OBUs (cordons + segments)

On-going. Until December 2010



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Geo-object type approximate size Description Pros Cons Type of analysis charge rate

Currently defined end2end geo-objects - small to medium road segments

~500m (length)

Road segments of known length (map data) with only one possible entrance and one possible exit

Length knownToo small to gather sufficient charging data

Geo object identification (based on size of protection levels)

Distance measurement analysisLimited analysis of accuracy of charging

High

Larger Zones/cordons

~5km (radius)

Area encompassing a city e.g. Amsterdam, Hague, Rotterdam and Utrecht

May gather large amount of data inside the geo-object

No "truth" available for comparison

Driver reaction based on derived charges and bills

low

4 Municipalities identified as charging zones – large geo-objects

Utrecht Den Haag Rotterdam Nijmegen



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The TOOLS



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CONTENTS

1. GINA concept




4. Conclusions

20/04/23 GINA – GNSS FOR INNOVATIVE ROAD APPLICAITONS


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CONCLUSIONS (1/2)

GINA: a step beyond in introduction of EGNOS / GALILEO in RUC and VAS

The GNSS technology is subject to intrinsic errors and requires specific mechanisms to ensure a reliable charging.

GINA proposes the use of position integrity as the way to ensure charging reliability.

Not another proof-of-concept: Large scale demonstrator

Trials:

– Exhaustive trials: GNSS performance analysis

– End2End trials: overall assessment from service perspective

Great amount of data. Realistic scenario, realistic conditions and valuable feedback from drivers experimenting system in operational conditions

27/10/2010GINA: GNSS FOR INNOVATIVE ROAD APPLICATIONS


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CONCLUSIONS 2/2

Exhaustive trial results confirmed that GNSS is a

reliable tool for different RUC schemes.

GINA proposed technology allows distance charging

with good performances and a simple, affordable solution.

European GNSS (e.g. EGNOS) and other GNSS centered

techniques improve performances and reliability

Additional analyses are in progress for E2E trial results.

They will be presented in next GINA workshop (Q1 2011)


Thank you!

Fiammetta Diani GSA - [email protected]

gina –gnss for innnovative road applications-

Documents

gina project gina gnss

gina consortium gina

gina trials overview

road sector

brussels gina workshop

nationwide gnssbased

gnssbased ruc vas scheme

described gina solution