View source for 18526627. SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY simplified abstract (Huawei Technologies Co., Ltd.)

=SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY=


==Organization Name==

[[:Category:Huawei Technologies Co., Ltd.|Huawei Technologies Co., Ltd.]]


[[Category:Huawei Technologies Co., Ltd.]]

==Inventor(s)==

[[:Category:Yann Koeberle of Boulogne Billancourt (FR)|Yann Koeberle of Boulogne Billancourt (FR)]][[Category:Yann Koeberle of Boulogne Billancourt (FR)]]

[[:Category:Stefano Sabatini of Boulogne Billancourt (FR)|Stefano Sabatini of Boulogne Billancourt (FR)]][[Category:Stefano Sabatini of Boulogne Billancourt (FR)]]

[[:Category:Dzmitry Tsishkou of Boulogne Billancourt (FR)|Dzmitry Tsishkou of Boulogne Billancourt (FR)]][[Category:Dzmitry Tsishkou of Boulogne Billancourt (FR)]]

==SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18526627 titled 'SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY

==Simplified Explanation==

The method described in the abstract updates a target driving policy for an autonomous vehicle at a target location by obtaining vehicle driving data, transmitting the data and current policy to a data center, performing traffic simulations to obtain an updated policy, and transmitting the updated policy back to the vehicle.

* Obtaining vehicle driving data at the target location
* Transmitting data and current target driving policy to a data center
* Performing traffic simulations using the vehicle driving data
* Obtaining an updated target driving policy
* Transmitting the updated policy back to the vehicle

== Potential Applications ==
This technology could be applied in autonomous vehicles, transportation systems, and traffic management systems.

== Problems Solved ==
This technology helps in updating driving policies for autonomous vehicles, improving safety, efficiency, and adaptability in different traffic scenarios.

== Benefits ==
The benefits of this technology include enhanced decision-making capabilities for autonomous vehicles, improved traffic flow, and increased overall safety on the roads.

== Potential Commercial Applications ==
The potential commercial applications of this technology could be in the automotive industry, smart city infrastructure, and transportation services.

== Possible Prior Art ==
One possible prior art could be the use of real-time data analysis in autonomous vehicles for decision-making processes.

=== What are the potential risks associated with updating driving policies remotely? ===

There could be risks related to data security and privacy when transmitting sensitive driving data to a data center for analysis and policy updates. Ensuring secure communication channels and data encryption would be crucial to mitigate these risks.

=== How can this technology be integrated with existing traffic management systems? ===

Integrating this technology with existing traffic management systems would require collaboration between autonomous vehicle manufacturers, data centers, and traffic authorities to ensure seamless communication and coordination for efficient traffic flow and safety.


==Original Abstract Submitted==

A method updates a target driving policy for an autonomous vehicle at a target location. The method includes the steps of obtaining, by the vehicle, vehicle driving data at the target location; transmitting, by the vehicle, the obtained vehicle driving data and a current target driving policy for the target location to a data center; performing, by the data center, traffic simulations for the target location using the vehicle driving data to obtain an updated target driving policy; and transmitting, by the data center, the updated target driving policy to the vehicle.



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