integrated project co-operative systems for road safety “smart vehicles on smart roads”
DESCRIPTION
Integrated Project Co-operative Systems for Road Safety “Smart Vehicles on Smart Roads” Tobias Schendzielorz TUM (Germany) [email protected]. SAFESPOT. T2.3.3 Data Fusion. Objective and Overview Status Further Steps for T2.3.3. Partners involved:. - PowerPoint PPT PresentationTRANSCRIPT
1SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
Integrated ProjectIntegrated Project
Co-operative Systems for Road Safety Co-operative Systems for Road Safety
““Smart Vehicles on Smart Roads”Smart Vehicles on Smart Roads”
Tobias Schendzielorz
TUM (Germany)
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2SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion
Objective and Overview
Status
Further Steps for T2.3.3
Partners involved:
TUM, NAVTEQ, MIZAR, CRF, CSST, SODIT, PTV AG, IBEO
3SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion
4SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion - Objective
General Objective of Data Fusion…
…is the combination of data from multiple sensors (roadside and in-vehicle) as well as from external sources...
…in order to perform interferences that may not be possible from a single sensor or source alone.
5SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion – Main Goals
Increasing the quality of data in terms of Reliability, Accuracy , and Consistency.
Providing information which can not be measured directly by a sensor.
Prioritising information.
Closing gaps of detection. The impact of a potential breakdown of single sensor can be mitigated.
Increasing the quality of data in terms of Reliability, Accuracy , and Consistency.
Providing information which can not be measured directly by a sensor.
Prioritising information.
Closing gaps of detection. The impact of a potential breakdown of single sensor can be mitigated.
6SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion - Status
5.3.1. Definition and Goals of Data Fusion
5.3.2. Review on Models and Architectures of Data Fusion(based on the U.S. Joint Directors of Laboratories (JDL) Data Fusion Group)
5.3.3. Lessons Learned from Other ITS Projects(PReVENT ProFusion 1&2, PAROTO, INVENT)
5.3.4. Proposed Levels of Data Fusion
5.3.5. Further Steps within the Data Fusion
5.3.1. Definition and Goals of Data Fusion
5.3.2. Review on Models and Architectures of Data Fusion(based on the U.S. Joint Directors of Laboratories (JDL) Data Fusion Group)
5.3.3. Lessons Learned from Other ITS Projects(PReVENT ProFusion 1&2, PAROTO, INVENT)
5.3.4. Proposed Levels of Data Fusion
5.3.5. Further Steps within the Data Fusion
7SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion - Status
Infrastructure-based Sensor 1
Infrastructure-based Sensor N…
Local Dynamic Map
External DataVANET
Communication
LEVEL 0
LEVEL 1
LEVEL 2
Infrastructure-based Sensor 2
Static Map …
Proposed Model
8SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion - Status
Kinds of Data Fusion:
Complementarythe information or data covers not the same area, objects or object attributes
Competitivesame entities are detected by different types of sensors or information sources.
Co-operativedata is achieved which is not possible to be detected by a sensors or because there is no sensor available
9SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion – Further Steps
Basic Work
Description of specific interests of the partners.
Check RQs of the SP5 Application and figure out which data / information is needed.
Check which data / information can be stored within the LDM.
Check which data / information is available from the infrastructure sensors.
Specifications of algorithms and data processing
Working out the level 0 / description of used methods.
Working out the level 1 / description of used methods.
Working out the level 2 / description of used methods.
Architecture and data flow.
Map Matching Algorithms.
Data management and process monitoring of the fusion domain.
Overall Architecture within SP2
Data exchange between Detection Algorithms and Data Fusion.
Hardware Specifications for the Fusion Processes
???
Further Software Specification
Interface to VANET, LDM and Sensors.
10SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
T2.3.3 Data Fusion – Further Steps
TUM will provided an detailed work plan.
Open Topics:
Will T2.3.3 be responsible for the specification of the RSU / MFO? (Hardware specifications, power supply…)
11SAFESPOT: SP2 – 5th INFRASENS Progress Meeting_T2.3.3 Data Fusion31 January 2007, Turin
Thank you for your attention!Thank you for your attention!
Tobias Schendzielorz
TUM (Germany)
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