VEHICLE WITH COMPUTING MEANS FOR MONITORING AND PREDICTING TRAFFIC PARTICIPANT OBJECTS
First Claim
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 filtering concepts,the method being characterized byusing at least one attractor function to modify the predicting step,wherein each attractor function represents a potential state trajectory from the current state to a potential future state determined according to context information.
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Abstract
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.
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Citations
11 Claims
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1. A method for predicting a state of at least one physical traffic object, the method including the steps of:
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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 filtering concepts, the method being characterized by using at least one attractor function to modify the predicting step, wherein each attractor function represents a potential state trajectory from the current state to a potential future state determined according to context information. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A device for predicting a state of at least one object, wherein the device comprises:
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Sensor means, preferably camera means, means, functionally connected to be supplied with signals from the sensor means, for determining an approximate probability distribution of a current state of the at least one object sensed by the sensor means, and means for predicting a future state of the at least one object by updating the approximate probability distribution using standard Bayesian filtering concepts, the device being characterized by being adapted to use at least one attractor function to modify the predicting step, wherein each attractor function represents a potential state trajectory from the current state to a potential future state determined according to context information. - View Dependent Claims (11)
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Specification