co-operative systems for road safety “smart vehicles on smart roads”

Ljubljana, Slovenia 22 April 2008

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

Giulio VivoCentro Ricerche Fiat

SP4 - SCOVA

SAFESPOT Integrated Project


INTELLIGENTVEHICLE

INTELLIGENTROAD

INTELLIGENT VEHICLEADVANTAGES

INTELLIGENT ROADADVANTAGESINTEGRATED WITH

REDUCTION OF INFRASTRUCTURE COST AND COMPLEXITY

sustainable deployment increased safety

REDUCTION OF VEHICLE SYSTEM COST AND COMPLEXITY

COOPERATIVE SYSTEMS FOR ROAD SAFETY:

“SMART VEHICLES” ON “SMART ROADS”

The SAFESPOT CONCEPT


The SAFESPOT CONCEPT: from the autonomous intelligent vehicle…


The SAFESPOT CONCEPT: … to intelligent Cooperative Systems


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 OPERATORSSUPPLIERS

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 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.

SAFESPOT Integrated Project Cooperative Systems for Road Safety

“Smart Vehicles on Smart Roads”


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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.


2006Requirements

2007Specs&development

2008Development&test

2009Test&evaluation

Core architecture requirement

Requirements

Specifications&architecture

TechnologicalProto&demo

Vehicles

Applications

ValidationOn Test site

Integration with CVIS

architecture

Test sites in Europe: France, Germany, Italy, Spain,

Sweden, the Netherlands

Results’Analysis

SAFESPOT TIME FRAME


Actual phase Early integration


VEHICLE TO VEHICLE (V2V)

INFRASTRUCTURE TO VEHICLE (I2V)

VEHICLE TO INFRASTRUCTURE (V2I)

DYNAMIC LOCAL COMMUNICATION NETWORKthe communication enables the cooperation among intelligent vehicles and

intelligent roads to produce a breakthrough for road safety

SAFESPOT KEY TECHNOLOGICAL CHALLENGES – THE VANET


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


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

ALGORITHMSDGPSVehicle sensors’ dataLandmarksOther vehicles’ positions

DATA FUSION

ALGORITHMS

DGPSVehicle sensors’ dataLandmarksOther vehicles’ positions

ACCURATE POSITIONING


LOCAL DYNAMIC MAPS

Map fromprovider

Landmarks for referencing

TunnelTunnel

Output of cooperative sensing/processing

Temporaryregional info

!

Current concept to be refined during the project

Accident (just occurred)

Accident (just occurred)

Fog bankFog bank

Slippery road surface (ice)

Slippery road surface (ice)

Ego Vehicle – speed, position, status, etc

Ego Vehicle – speed, position, status, etc

Signalling phases

Signalling phases

Vehicles in queue

Vehicles in queueAim: to represent the vehicle’s

surroundings with all static and dynamic safety-relevant elements


SP4 – SCOVA – Vehicle centered applications


SP4 – SCOVA – Communication constraints


SP4 – SCOVA – Communication constraints

Control channel usage limits (US WAVE 802.11.p)

rOBU = 3 Mbit/s * 580 μs / 750 ms = 2320 bit/srRSU = 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 relatedto the poor usage of the communication channel.


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.


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.


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


At the end, four applicative tasks are running in order to support the cooperative applications:

1. An Application Manager, running on the primary actor;2. A Driver Assistance Application, running on the primary actor;3. A Message Manager, running on each secondary actor;4. A Cooperative Assistance Application, running on the secondary actors.

Application Manager +Driver Assistance Application

Message Manager +Cooperative Assistance Application


•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.

Conclusions


REFERENCES

IP web site www.safespot-eu.org

IP Coordinator Roberto Brignolo, Centro Ricerche Fiat Tel. +39 011 9080 534 [email protected]

Core Group Centro Ricerche Fiat, Renault, Volvo, DaimlerChrysler,Magneti Marelli, Bosch, COFIROUTE, ANAS, TNO

Sub-Projects Leaders

SP1 – SAFEPROBE Christian Zott, Robert Bosch GmbH, [email protected] SP2 – INFRASENS Angela Spence, MIZAR Automazione, [email protected] SP3 – SINTECH Achim Brakemeier, DaimlerChrysler, [email protected] SP4 – SCOVA Giulio Vivo, Centro Ricerche Fiat, [email protected] SP5 – COSSIB Guy Fremont, Cofiroute, [email protected] SP6 – BLADE Han Zwijnenberg, TNO, [email protected] SP7 – SCORE Abdelkader Mokaddem, Renault, [email protected]

Quality&Dissemination, Angelos Amditis, ICCS, [email protected]

co-operative systems for road safety “smart vehicles on smart roads”

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