View source for 17455853. Managing Vehicle Behavior Based On Predicted Behavior Of Other Vehicles simplified abstract (QUALCOMM Incorporated)

=Managing Vehicle Behavior Based On Predicted Behavior Of Other Vehicles=


==Organization Name==

[[:Category:QUALCOMM Incorporated|QUALCOMM Incorporated]]


[[Category:QUALCOMM Incorporated]]

==Inventor(s)==

[[:Category:Gopi Krishna Tummala of San Diego CA (US)|Gopi Krishna Tummala of San Diego CA (US)]][[Category:Gopi Krishna Tummala of San Diego CA (US)]]

[[:Category:Tianqi Ye of San Diego CA (US)|Tianqi Ye of San Diego CA (US)]][[Category:Tianqi Ye of San Diego CA (US)]]

[[:Category:Avdhut Joshi of San Marcos CA (US)|Avdhut Joshi of San Marcos CA (US)]][[Category:Avdhut Joshi of San Marcos CA (US)]]

[[:Category:Monu Surana of San Diego CA (US)|Monu Surana of San Diego CA (US)]][[Category:Monu Surana of San Diego CA (US)]]

==Managing Vehicle Behavior Based On Predicted Behavior Of Other Vehicles - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17455853 titled 'Managing Vehicle Behavior Based On Predicted Behavior Of Other Vehicles

==Simplified Explanation==

The patent application describes methods and systems for managing vehicle behavior. Here are the key points:

* The system involves a vehicle processor in the first vehicle that receives information about the dynamic traffic flow features of a second vehicle nearby.
* Based on this information, the processor determines the probabilities of various potential behaviors of the second vehicle.
* The processor then predicts the future path of the second vehicle and uses this prediction in controlling the first vehicle.
* Additionally, the processor can predict the behavior of a third vehicle based on intention information about the second vehicle and adjust the behavior of the first vehicle accordingly.

Potential applications of this technology:

* Autonomous driving systems: The technology can be used in autonomous vehicles to improve their ability to predict and respond to the behavior of other vehicles on the road.
* Traffic management: By accurately predicting the behavior of nearby vehicles, this technology can help optimize traffic flow and reduce congestion.
* Collision avoidance: The system can assist in avoiding collisions by predicting the future paths of other vehicles and adjusting the behavior of the host vehicle accordingly.

Problems solved by this technology:

* Uncertainty in traffic behavior: By using dynamic traffic flow feature information, the system can better predict the behavior of other vehicles, reducing uncertainty and improving safety.
* Limited visibility: The system can compensate for limited visibility by predicting the future paths of nearby vehicles, even if they are not directly visible to the driver or sensors of the host vehicle.

Benefits of this technology:

* Improved safety: By accurately predicting the behavior of other vehicles, the system can help the host vehicle make safer decisions and avoid potential collisions.
* Enhanced traffic flow: By optimizing the behavior of the host vehicle based on predictions of other vehicles, the system can contribute to smoother traffic flow and reduced congestion.
* Increased efficiency: The technology can improve the efficiency of autonomous driving systems by enabling them to better anticipate and respond to the behavior of other vehicles on the road.


==Original Abstract Submitted==

Various embodiments include methods and systems for managing vehicle behavior. In some embodiments, a vehicle processor of the first vehicle may receive dynamic traffic flow feature information relevant to movements of a second vehicle within a predetermined proximity to the host vehicle, determine probabilities of a plurality of potential behaviors of the second vehicle based on the received dynamic traffic flow feature information, predict a future path of the second vehicle, and use the predicted future path of the second vehicle in a vehicle control function. In some embodiments, the vehicle processor of the first vehicle may predict a behavior of a third vehicle based on received intention information about the second vehicle, and may adjust a behavior of the first vehicle based on the predicted behavior of the third vehicle.



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