Method of sharing and using sensor data
US-11878711-B2 · Jan 23, 2024 · US
US9104965B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9104965-B2 |
| Application number | US-201313735064-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jan 7, 2013 |
| Priority date | Jan 11, 2012 |
| Publication date | Aug 11, 2015 |
| Grant date | Aug 11, 2015 |
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An anticipatory monitoring and prediction system can include methods for generating effective, accurate predictions of other traffic objects in the vicinity of an ego-car. The invention proposes to combine approximate probability distributions (ADPs) of agent states with Attractor Functions (AFs) for generating distributed probabilistic representations of the potential future states of the observed traffic objects. AFs are selected based on both the current road context, in which the ego-car is situated, and the current states of all participating objects. The generated predictions can be used to filter incoming sensory information for better object state estimations, rate the nature of the behavior of other traffic objects by comparing generated predictions with actual perceived sensor information, or infer accident likelihoods by comparing the predicted state distributions of objects and the ego-car. Warning and information signals or control commands can be issued in a driving assistance system.
Opening claim text (preview).
The invention claimed is: 1. A method for predicting a state of at least one physical traffic object, the method including the steps of: generating sensorial information, based on the sensorial information, computing an approximate probability distribution of a current state of the at least one object represented in the sensorial information, and predicting a future state of the at least one object by updating the approximate probability distribution using standard Bayesian filt…
Operations & Transport · mapped topic
Operations & Transport · mapped topic
Operations & Transport · mapped topic
Operations & Transport · mapped topic
Operations & Transport · mapped topic
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