Huawei technologies co., ltd. (20240132088). SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY simplified abstract
Contents
- 1 SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY
Organization Name
Inventor(s)
Yann Koeberle of Boulogne Billancourt (FR)
Stefano Sabatini of Boulogne Billancourt (FR)
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 20240132088 titled 'SIMULATION BASED METHOD AND DATA CENTER TO OBTAIN GEO-FENCED DRIVING POLICY
Simplified Explanation
The abstract describes a method for updating a target driving policy for an autonomous vehicle at a target location. The steps include obtaining vehicle driving data at the target location, transmitting the data and current target driving policy to a data center, performing traffic simulations to update the 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 to update the target driving policy
- Transmitting the updated policy back to the vehicle
Potential Applications
This technology could be applied in autonomous vehicles, transportation systems, and smart city infrastructure.
Problems Solved
This technology solves the problem of updating driving policies for autonomous vehicles in real-time based on current data and simulations.
Benefits
The benefits of this technology include improved safety, efficiency, and adaptability of autonomous vehicles in various driving conditions.
Potential Commercial Applications
Potential commercial applications of this technology include autonomous vehicle companies, transportation agencies, and smart city developers.
Possible Prior Art
One possible prior art could be the use of real-time data and simulations to update driving policies for autonomous vehicles, but the specific method described in the abstract may be novel.
What are the potential environmental impacts of implementing this technology?
Implementing this technology could potentially reduce traffic congestion, improve fuel efficiency, and decrease emissions by optimizing driving policies for autonomous vehicles.
How does this technology compare to traditional methods of updating driving policies for autonomous vehicles?
This technology offers a more dynamic and data-driven approach to updating driving policies compared to traditional methods, which may rely on pre-set rules or manual adjustments.
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.
