Signal to software interface management

1 . A system, comprising:

one or more computing devices configured to implement a hardware software interface management system configured to:

provide as input, to a trained machine learning model, a sample vehicle signal comprising data related to a vehicle component of a vehicle, wherein the machine learning model has been trained using training signals comprising a plurality of types of vehicle signals, and wherein the machine learning model has been trained for one or more vehicle specifications;

generate, based on the sample vehicle signal provided, software code to implement a hardware signal to software interface to be deployed in the vehicle, wherein the hardware signal to software interface is configured to:

map a vehicle component signal directed to, or received from, the vehicle component to a schema key associated with the vehicle component, wherein the schema key is used to represent one or more attributes of the vehicle component signal in a communication used by a given vehicle software for the vehicle; and

format the vehicle component signal for use by the vehicle software according to a schema associated with the schema key; and

provide the generated software code to a deployment location in the vehicle to implement the hardware signal to software interface.

2 . The system of claim 1 , wherein the one or more computing devices that implement the hardware software interface management system are part of a cloud provider network, wherein the hardware software interface management system is configured to:

receive the sample vehicle signal from the vehicle; and

provide the generated software code to the vehicle for deployment to the deployment location in the vehicle.

3 . The system of claim 1 , wherein the one or more computing devices that implement the hardware software interface management system are part of the vehicle, wherein the hardware software interface management system is configured to:

deploy the generated software code to the deployment location in the vehicle.

4 . The system of claim 1 , wherein the hardware software interface management system is configured to:

receive another sample vehicle signal comprising updated data related to a same type of vehicle component as the vehicle component;

provide the other sample vehicle signal to the trained machine learning model;

determine, based on the other sample vehicle signal, that the software code to implement the hardware signal to software interface is to be updated; and

generate, based on the other sample vehicle signal, an updated software code to update the hardware signal to software interface, wherein the updated hardware signal to software interface is configured to map the vehicle component signal generated by the vehicle component of the same type as the vehicle component to the schema key associated with the vehicle component.

5 . A method, comprising:

providing as input, to a trained machine learning model for a signal software interface management system, a sample vehicle system signal comprising data related to a vehicle system component of a vehicle, wherein the machine learning model has been trained using training signals comprising a plurality of types of vehicle signals, and wherein the machine learning model has been trained for one or more vehicle system specifications;

generating, based on the sample vehicle system signal provided, software code to implement a signal to software interface to be deployed in the vehicle, wherein the signal to software interface is configured to:

map a vehicle system component signal directed to, or received from, the vehicle system component to a schema key associated with the vehicle system component, wherein the schema key is used to represent one or more attributes of the vehicle system component signal in a communication used by a given vehicle software for the vehicle; and

format the vehicle system component signal for use by the vehicle software according to a schema associated with the schema key; and

providing the generated software code to a deployment location in the vehicle to implement the signal to software interface.

6 . The method of claim 5 , further comprises:

receiving, using the signal software interface management system, the training signals, wherein:

the plurality of types of vehicle signals of the training signals are associated with a plurality of vehicle system components for a plurality of different vehicle systems; and

receiving, a plurality of vehicle system specifications for the plurality of different vehicle systems; and

to generate the trained machine learning model, training the machine learning model using the training signals associated with the plurality of vehicle system components for the plurality of different vehicle systems.

7 . The method of claim 6 , wherein the method further comprises:

providing as input, to the trained machine learning model, another sample vehicle system signal associated with another vehicle system component, wherein:

the vehicle system component is associated with a vehicle model;

the other vehicle system component is associated with a different vehicle model; and

generating, based on the other sample vehicle system signal, another software code to implement another signal to software interface to be deployed to the other vehicle system component associated with the different vehicle model.

8 . The method of claim 5 , wherein:

the vehicle system component is another signal to software interface;

the sample vehicle system signal is a processed vehicle system signal generated by the other signal to software interface; and

the signal to software interface is configured to format the vehicle system component signal from another schema associated with another schema key of the other signal to software interface to conform to the schema.

9 . The method of claim 5 , wherein the signal to software interface management system is implemented as part of a cloud provider network, and

wherein the method further comprises:

receiving the sample vehicle system signal from a vehicle; and

providing the generated software code to the vehicle for deployment to the deployment location in the vehicle.

10 . The method of claim 9 , further comprising:

receiving at a deployment orchestrator of the vehicle, the generated software code; and

deploying using the deployment orchestrator the generated software code to the deployment location in the vehicle, wherein the deployment location is a component in the vehicle.

11 . The method of claim 5 , wherein the signal to software interface management system, including the trained machine learning model, is implemented as part of a vehicle, and wherein the method further comprises:

deploying the generated software code to the deployment location in the vehicle.

12 . The method of claim 5 , wherein the vehicle system component signal conforms to:

a Controller Area Network (CAN) protocol;

a Controller Area Network Flexible Data-rate (CAN FD) protocol; or

a service-Oriented MiddlewarE over IP (SOME/IP) protocol.

13 . The method of claim 5 , wherein the vehicle system component signal is a compressed signal, wherein the compressed signal conforms to:

a binary format; or

a protocol buffer format.

14 . The method of claim 5 , further comprising:

receiving another sample vehicle system signal comprising updated data related to a same type of vehicle system component as the vehicle system component;

providing the other sample system vehicle signal to the trained machine learning model;

determining, based on the other sample vehicle system signal, that the software code to implement the signal to software interface is to be updated; and

generating, based on the other sample vehicle system signal, an updated software code to update the signal to software interface, wherein the updated signal to software interface is configured to map the vehicle system component signal generated by the vehicle system component of the same type as the vehicle system component to the schema key associated with the vehicle system component.

15 . One or more non-transitory, computer-readable storage media, storing program instructions that when executed on or across one or more computing devices cause the one or more computing devices to implement:

providing as input, to a trained machine learning model for a signal software interface management system, a sample vehicle system signal comprising data related to a vehicle system component of a vehicle, wherein the machine learning model has been trained using training signals comprising a plurality of types of vehicle signals, and wherein the machine learning model has been trained for one or more vehicle system specifications;

generating, based on the sample vehicle system signal provided, software code to implement a signal to software interface to be deployed in the vehicle, wherein the signal to software interface is configured to:

map a vehicle system component signal directed to, or received from, the vehicle system component to a schema key associated with the vehicle system component, wherein the schema key is used to represent one or more attributes of the vehicle system component signal in a communication used by a given vehicle software for the vehicle; and

format the vehicle system component signal for use by the vehicle software according to a schema associated with the schema key; and

providing the generated software code to a deployment location in the vehicle to implement the signal to software interface.

16 . The one or more non-transitory, computer-readable, storage media of claim 15 , wherein the signal to software interface management system are implemented as part of a cloud provider network, and wherein the instructions cause the one or more computing devices to implement:

receiving the sample vehicle system signal from a vehicle; and

providing the generated software code to the vehicle for deployment to the deployment location in the vehicle.

17 . The one or more non-transitory, computer-readable, storage media of claim 16 , wherein the instructions cause the one or more computing devices to implement:

receiving at a deployment orchestrator of the vehicle, the generated software code; and

deploying using the deployment orchestrator the generated software code to the deployment location in the vehicle, wherein the deployment location is a component in the vehicle.

18 . The one or more non-transitory, computer-readable, storage media of claim 15 , wherein the signal to software interface management system, including the trained machine learning model, is implemented as part of a vehicle, and wherein the instructions cause the one or more computing devices to implement:

deploying the generated software code to the deployment location in the vehicle.

19 . The one or more non-transitory, computer-readable, storage media of claim 15 , wherein the instructions cause the one or more computing devices to implement:

receiving, using the signal software interface management system, the training signals, wherein:

the plurality of types of vehicle signals of the training signals are associated with a plurality of vehicle system components for a plurality of different vehicle systems; and

receiving, a plurality of vehicle system specifications for the plurality of different vehicle systems; and

to generate the trained machine learning model, training the machine learning model using the training signals associated with the plurality of vehicle system components for the plurality of different vehicle systems.

20 . The one or more non-transitory, computer-readable, storage media of claim 19 , wherein the instructions cause the one or more computing devices to implement:

providing as input, to the trained machine learning model, another sample vehicle system signal associated with another vehicle system component, wherein:

the vehicle system component is associated with a vehicle model; and

the other vehicle system component is associated with a different vehicle model;

generating, based on the other sample vehicle system signal, another software code to implement another signal to software interface to be deployed to the other vehicle system component associated with the different vehicle model.