Scenario Analysis & Data Fusion Specification Panagiotis Lytrivis ICCS
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Transcript of Scenario Analysis & Data Fusion Specification Panagiotis Lytrivis ICCS
1SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Scenario Analysis & Data Fusion Specification
Panagiotis Lytrivis
ICCS
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2SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Scenario Analysis
Scenario 13
“Ego-vehicle starts braking very hard while other vehicle is following”
• Simulations based on a backward looking mounting sensor (LRR, Laserscanner, vision)
3SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Scenario Analysis (2)
Scenario 14
“Ego-vehicle overtakes a vehicle changing lane and entering into a collision path with another oncoming vehicle”
We used 2 LRRs for forward sensing
• FOV 40o
• Range 60m
4SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Task 1.3.2 - Environment Data Acquisition Specification
• Interfaces and protocols are defined in SP3-SINTECH
• In this task we analyze the “data packet” specs
• Important issues:
– Data flow between V2V or V2I
– Time management & time-stamping
– Data storage management
Output: A complete protocol for data acquisition and storage,
before processing and data fusion
5SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Task 1.3.3 - Cooperative Data Fusion Specification
We have changed this task and “Task 1.3.1 – Internal Data Fusion Specification” (according to JDL model) into
• Object refinement and • Situation refinement
The same idea is followed in ProFusion
Change the Technical Annex?• Yes → Do it the right way and not just replace the task titles• No → The distinction between the 2 tasks will be vague,
but the necessary will definitely get done
One proposal: Change it together with some other changes that had already been discussed in the Core Group
6SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Object refinement
Key functions:• Feature extraction (Segmentation, contour extraction etc.)
• Object tracking
• Observation-to-track-association
• Track maintenance
• Object classification
The output of the object refinement consists of a list of objects with specific parameters or attributes (i.e. position, velocity)
Object refinement aims at the representation of the environment through the LDM (vehicles, pedestrians, road borders etc.)
Object tracking & data fusion from distributed sensor nodes (cooperative fusion) for a common state estimation of the objects
Data association problem
7SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Situation refinement
It is more a relational matter between the detected objects
• how they interact,
• what scenario they represent etc.
The most common problem is the path or trajectory prediction:
We take the history of an object’s state (its position and respective speed in the past) and we try to predict the object’s state in the near term future
Outputs of all distributed sensors are fused to create an overall situational understanding (environmental model), which is then available to any applications running on the vehicle
8SAFESPOT Project SP1 Plenary Meeting January 31th 2007 CRF, Orbassano
Situation refinement (2)
• We have experience in situation refinement, especially in maneuver detection (detection of the intention of the driver and lane assignment of the detected object)
• We are involved in ProFusion (PReVENT SP)
Hard task because it is a relational matter between objects and we need advanced machine intelligence
Example: “Object vehicle in left lane is in the process of overtaking and passing a preceding vehicle”
For the situation refinement:
• What scenarios should the system be aware of?
• What’s the level of difficulty of the implementation?
To do that we need input from scenario analysis and from applications
Also from side of architecture which queries should we answer?