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Co-operative Systems for Road Safety “Smart Vehicles on Smart Roads”

SAFESPOT Integrated Project. Co-operative Systems for Road Safety “Smart Vehicles on Smart Roads”. Giulio Vivo Centro Ricerche Fiat SP4 - SCOVA. The SAFESPOT CONCEPT. COOPERATIVE SYSTEMS FOR ROAD SAFETY: “SMART VEHICLES” ON “SMART ROADS”. INTELLIGENT VEHICLE ADVANTAGES.

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Co-operative Systems for Road Safety “Smart Vehicles on Smart Roads”

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  1. SAFESPOT Integrated Project Co-operative Systems for Road Safety “Smart Vehicles on Smart Roads” Giulio Vivo Centro Ricerche Fiat SP4 - SCOVA

  2. The SAFESPOT CONCEPT COOPERATIVE SYSTEMS FOR ROAD SAFETY: “SMART VEHICLES” ON “SMART ROADS” INTELLIGENT VEHICLE ADVANTAGES INTELLIGENT ROAD ADVANTAGES INTEGRATED WITH REDUCTION OF VEHICLE SYSTEM COST AND COMPLEXITY REDUCTION OF INFRASTRUCTURE COST AND COMPLEXITY INTELLIGENT ROAD INTELLIGENT VEHICLE sustainable deployment increased safety

  3. The SAFESPOT CONCEPT: from the autonomous intelligent vehicle…

  4. The SAFESPOT CONCEPT: … to intelligent Cooperative Systems

  5. Project type: Integrated Project (IP) • Co-funded by the European Commission Information Society and Media in the • 6th Framework Programme • Consortium: 51 partners from 12 European countries: • OEM ( trucks, cars, motorcycles) • ROAD OPERATORS • SUPPLIERS • RESEARCH INSTITUTES • UNIVERSITIES • Promoted by: EUCAR • Timeframe: Feb. 2006 – Jan. 2010 • Overall Cost Budget: 38 M€ • (European Commission funding 20.5M€) • IP coordinator : Roberto Brignolo • C.R.F. Centro Ricerche Fiat (Italy) SAFESPOT Integrated Project Cooperative Systems for Road Safety “Smart Vehicles on Smart Roads” SAFESPOT is working to design intelligent cooperative systems based on vehicle to vehicle and vehicle to infrastructure communication to produce a breakthrough for road safety. SAFESPOT will prevent road accidents developing a: “SAFETY MARGIN ASSISTANT” to detect in advance potentially dangerous situations and extend, in space and time, drivers’ awareness of the surroundings.

  6. SAFESPOT Consortium

  7. SAFESPOT SPECIFIC OBJECTIVES • To use the infrastructure and the vehicles as sources (and destinations) of safety-related information and develop an open, flexible and modular architecture and communication platform. • To develop the key enabling technologies: • ad-hoc dynamic networking, accurate relative localisation, dynamic local traffic maps. • To develop a new generation of infrastructure-based sensing techniques. • To develop and test scenario-based applications to evaluate the impacts and the end-user acceptance. • To define the practical implementation of such systems, especially in the initial period when not all vehicles will be equipped. • To evaluate the liability aspects, regulations and standardisation issues which can affect the implementation.

  8. SAFESPOT TIME FRAME Test sites in Europe: France, Germany, Italy, Spain, Sweden, the Netherlands Technological Proto&demo Vehicles Validation On Test site Requirements 2006 Requirements 2007 Specs&development 2008 Development&test 2009 Test&evaluation Core architecture requirement Specifications &architecture Results’ Analysis Applications Integration with CVIS architecture

  9. Actual phase  Early integration

  10. SAFESPOT KEY TECHNOLOGICAL CHALLENGES – THE VANET VEHICLE TO INFRASTRUCTURE (V2I) INFRASTRUCTURE TO VEHICLE (I2V) DYNAMIC LOCAL COMMUNICATION NETWORK the communication enables the cooperation among intelligent vehicles and intelligent roads to produce a breakthrough for road safety VEHICLE TO VEHICLE (V2V)

  11. SAFESPOT KEY TECHNOLOGICAL CHALLENGES • Reliable, fast, secure, potentially low cost protocols for local V2V and V2I • communication • Candidate radio technology: IEEE 802.11p • Need for dedicated frequency band for secure V2V and V2I, avoiding interference with existing consumer links • Aligned to C2C-C and CALM standardisation groups • A reliable, very accurate, real-time relative positioning • A real time updateable Local Dynamic Map

  12. ACCURATE POSITIONING • A reliable, very accurate, real-time relative positioning: • Satellite raw data (pseudo-ranges) enhancing the proven differential procedures (DGPS). • Use of landmarks registered on digital maps. DATA FUSION ALGORITHMS DGPS Vehicle sensors’ data Landmarks Other vehicles’ positions DATA FUSION ALGORITHMS DGPS Vehicle sensors’ data Landmarks Other vehicles’ positions

  13. Map fromprovider ! LOCAL DYNAMIC MAPS Vehicles in queue Aim: to represent the vehicle’s surroundings with all static and dynamic safety-relevant elements Signalling phases Ego Vehicle – speed, position, status, etc Output of cooperative sensing/processing Slippery road surface (ice) Temporaryregional info Tunnel Fog bank Landmarks for referencing Accident (just occurred) Current concept to be refined during the project

  14. SP4 – SCOVA – Vehicle centered applications

  15. SP4 – SCOVA – Communication constraints

  16. SP4 – SCOVA – Communication constraints Control channel usage limits (US WAVE 802.11.p) rOBU = 3 Mbit/s * 580 μs / 750 ms = 2320 bit/s rRSU = 3 Mbit/s * 750 μs / 100 ms = 22500 bit/s Applicative models where “actor a ask actor b for…” can not be adopted due to the implications related to the poor usage of the communication channel.

  17. This implies that a rigid synchronization between the world representation (LDM content) of the different vehicular nodes of the VANET can not be achieved. The single parameter enforcing the coherence between the different representation is the time, which is common and shared. So, dedicated tasks (both at the network level and at the applicative level) should be implemented for achieving a good “alignment” between the different LDMs.

  18. An example of the reference model that has been specified is related to the Speed limitation & safety distance application. Let’s say that actor 2 needs to know the status of the brake pedal of actor 1. This parameter is easily available on the CAN bus of 1, but this information should be transmitted only after becoming aware of belonging (with a passive participation) to an applicative scenario where the assistance effects - warnings - are exclusively for the benefit of 2.

  19. The two state machines running on the primary actor and on the secondary actors of any given scenario are based on the VANET beacons; this should allow to build up a similar representation of the surrounding scenario

  20. At the end, four applicative tasks are running in order to support the cooperative applications: • An Application Manager, running on the primary actor; • A Driver Assistance Application, running on the primary actor; • A Message Manager, running on each secondary actor; • A Cooperative Assistance Application, running on the secondary actors. Message Manager + Cooperative Assistance Application Application Manager + Driver Assistance Application

  21. Conclusions • An overview of the SAFESPOT project has been presented. • Benefits of the cooperative approach are ranging from the sharing low-level data to the usage of integrated information for implementing a novel Safety Assistance for the users of the equipped vehicles. • At the applicative level the advantages of using a cooperative approach are also significant; the complete situation around the vehicle can be described within a local dynamic database (the LDM) where some safety critical parameters (as the minimum positions and dynamics of the VANET actors) are shared by all vehicles in the surrounding. • Vehicles can exchange their reciprocal position and negotiate for lane changes; dynamic hot spots information can be propagated among the co-operating vehicles. This level of information would be especially useful for the lesser equipped vehicles that do not carry full ADAS equipment but only have available some basic intercommunicating SAFESPOT unit. • Finally, unequipped vehicles may also benefit as some information can be transferred from other SAFESPOT actors to traffic control centers and distributed by means of traditional medias such as information on the public radio or Variable Message Signs.

  22. REFERENCES IP web site www.safespot-eu.org IP Coordinator Roberto Brignolo, Centro Ricerche Fiat Tel. +39 011 9080 534 safespot@crf.it Core Group Centro Ricerche Fiat, Renault, Volvo, DaimlerChrysler, Magneti Marelli, Bosch, COFIROUTE, ANAS, TNO Sub-Projects Leaders SP1 – SAFEPROBE Christian Zott, Robert Bosch GmbH, christian.zott@de.bosch.com SP2 – INFRASENS Angela Spence, MIZAR Automazione, angela.spence@torino.miz.it SP3 – SINTECH Achim Brakemeier, DaimlerChrysler, achim.brakemeier@daimlerchrysler.com SP4 – SCOVA Giulio Vivo, Centro Ricerche Fiat, giulio.vivo@crf.it SP5 – COSSIB Guy Fremont, Cofiroute, guy.fremont@cofiroute.fr SP6 – BLADE Han Zwijnenberg, TNO, han.zwijnenberg@tno.nl SP7 – SCORE Abdelkader Mokaddem, Renault, abdelkader.mokaddem@renault.com Quality&Dissemination, Angelos Amditis, ICCS, a.amditis@iccs.gr

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