the role of satellite-based navigation (gnss)...
TRANSCRIPT
THE ROLE OF SATELLITE-BASED
NAVIGATION (GNSS) FOR
AUTONOMOUS DRIVING
Fiammetta Diani
Deputy Head of Market Development, European GNSS Agency
This presentation can be interpreted only together with the oral comments accompanying it
Galileo lift off is getting serious !
• 14 Galileo satellites are today in orbit
• Last launch (2 satellites) on 24th May
• Next launch with Ariane (4 satellites) in November • The signal of navigation is already
transmitted and the initial operational services will start later this year
Analysis of the receivers’ capabilities shows Galileo
encouraging position within multi-constellation
Capability assessment of more
than 300 receivers, chipsets
and modules, currently
available on the market (2014)
…and in 2016? All the leaders support Galileo
Automotive and smartphones
Professional (e.g. surveying)
The multi-constellation and multi-frequency concepts
Multi-constellation: When buildings block the signal and reduce the number of visible satellites, the availability of more constellations ensures a much more accurate final position
Multi-frequency: Galileo, as well as GPS, is providing a second frequency on the Open Service, the E5/L5: much increased accuracy (elimintation of iono error and quick transition form code phase to carrier phase navigation) and increased resistance to multipath (also respect to L2C, the other second frequency of GPS…)
The multipath problem and Galileo
Contribution
The strength of Galileo signal, together with an advanced code modulation, makes Galileo better mitigating multipath effects (especially in E5, but also E1)
• CS - Galileo Commercial Service
• OS - Galileo Open Service
• SCE - Security Encrypted keys in the E6c signal
• NMA - Navigation Message Authentication in the E1b signal
(Cyber) Security is becoming a major concern in automotive industry
Increasing need to get robust GNSS modules provide an efficient, resilient and low-cost solution against jamming or spoofing attacks
2018
Galileo unique differentiator: signal authentication
• The “classic” integrity (aviation-born) is affected by conceptual and
practical limitations for its applicability in a vehicular context
1) Conventional aeronautical GNSS signal models
(assuming open-sky satellite visibility and
diffuse ground multipath) may be no more consistent
for automotive urban scenarios
(space- and time-varying impairments)
2) Typical requirements/specifications (i.e. integrity risk)
associated to aviation operations could be
too conservative for the vehicular applications,
especially in non-Safety-of-Life cases,
(leading to too conservative Protection Levels)
3) Autonomous integrity approaches (e.g. RAIM) do not exploit the
possible added value of GNSS information exchanged by
collaborative receivers,
e.g. in a Vehicular Ad-hoc Network (VANET)
Integrity: interesting concept for connected/autonomous
vehicles, but the classic concept has limitations
30/06/2016 GLOVE - joint GaliLeo Optimization and VANET
Enhancement
Intended to overcome the limitations of classic integrity
– Cars as sensors for GNSS signal quality assessment
– GNSS observations shared by means of Vehicular Ad Hoc Networks (VANET) communications
– Collaborative monitoring of GNSS signals in urban scenarios
• Spatial/temporal characterization of local signal degradations
Computation of “Local Protection Levels” ellipses
– Defined on Along-Track (AT) and Cross-Track (CT) directions
– Suitable to vehicular applications
The “Local Integrity” approach
AT
CT Source: http://www.glove-fp7.net/
Declaration of Amsterdam
Development of a shared European strategy on connected and automated driving
Adaptation of EU regulatory framework
Coordination in Research and Innovation
Contribution of EGNOS and Galileo
EU Presidency initiative paper to stimulate uptake of Space Data in autonomous driving
Infrastructure Do not need infrastructure to operate (e.g.
pavement streets in segregated areas)
Circulation Like a bus, they follow a route, which can be dynamically modified to account for
higher demand in specific spots
Capacity Up to 15 passengers per vehicle(2)
Personal Rapid Transit or “Podcar” was the first attempt to change mobility habits
• AKKA: Enhanced vehicle-location capability with simultaneous localisation and mapping and robust GNSS systems
• EASY MILE: Hybrid sensing approach combining localisation through vision, laser and differential GNSS.
European examples (*)
(*) Navigation solutions developed in TAXISAT project, funded by the GSA under the FP7 programme
13
14 Groups 55 Brands
Share of produced vehicles worldwide
(2013)
Car Manufacturer Group
13.49% Volkswagen
12.47% Toyota
10.06% Hyundai 9.81% General Motors
6.21% Honda 5.96% Nissan 4.83% Ford
3.56% Groupe PSA 3.42% Renault
3.15% Fiat Chrysler Automobiles
2.92% BMW
2.38% Daimler 1.55% Tata
1.41% Geely 0.03% Tesla
14 groups 80% of the produced vehicles worldwide
Source: Business Insider
Source: OICA, International Organization of Motor Vehicle Manufacturers
Survey on GNSS in autonomous vehicles
14
Car Brand Commercial Name Galileo
Audi Piloted Driving TBC
BMW Active Assist TBC
Chevrolet --- TBC
Chrysler (*) (With Google) TBC
Citroen and Peugeot Highway Chauffer TBC
Fiat ---
Ford --- TBC
Honda Automated Drive TBC
Hyundai ---
Jaguar Land Rover --- TBC
Kia Drive Wise
Mercedez Benz --- TBC
Nissan Intelligent Driving TBC
Renault Next Two TBC
Tesla (**) Autopilot TBC
Toyota and Lexus --- TBC
Volkswagen --- TBC
Volvo (***) Drive Me/Intellisafe Autopilot
(*) Recent partnership between Google and FCA (Chrysler) (**) Commercially available: Model S latest software upgrade includes autonomous driving functions (***) Tests with volunteer customers starting in 2017 in Sweden and UK
All 14 car maker groups are developing Autonomous Driving
pilots with GNSS
4 brands already confirmed readiness
for Galileo
GNSS is the preferred technology
Early results of the survey on GNSS and Galileo utilisation in Autonomous Driving pilots
INDRIVE: Automotive European GNSS Receiver for High Integrity Applications
Full potential of advanced satellite positioning to develop integrated solution starting from low-level signal processing to high-level data fusion
The innovation of this project stands in the adoption of a robust European GNSS for automated manoeuvres in automotive applications: the robust positioning will be used to estimate the level of confidence of the position
The solution will guarantee the compliance of the use cases in terms of false alarm rates and accuracy
INLANE: from road-level navigation towards Highly Automated Driving
Sensor Fusion is essential: no sole positioning sensor covers all performance requirements
Combination of computer vision, 3D Maps and GNSS technologies are fostering new solutions not only for driving assistance but for unmanned vehicles
The enhanced mapping information gives (autonomous) drivers the opportunity to select the optimal road lane, even in dense traffic situations.
H2020 next funding opportunity for Galileo is approaching
Type of Action
Topic Budget (EUR mln)
Funding rate Indirect costs
IA EGNSS Transport Applications 14.50
70% (except for non-profit legal entities, where
a rate of 100% applies)
25% of the total eligible costs excluding: • Subcontracting • Costs of resources
made available by 3rd parties
• Financial support to 3rd parties
IA EGNSS Mass Market Applications 9.00
IA EGNSS Professional Applications 8.00
CSA EGNSS Awareness raising and capacity building
1.50 100%
Total budget: 33.00 Opening: 08 November 2016 Deadline: 01 March 2017
THANK YOU
The present presentation can be interpreted only together with the oral comment accompanying it