Vehicle Model Creation

Learn how to create a Vehicle Model to access vehicle data or execute remote procedure calls.

A Vehicle Model makes it possible to easily get vehicle data from the KUKSA Data Broker and to execute remote procedure calls over gRPC against Vehicle Services and other Vehicle Apps. It is generated from the underlying semantic models for a concrete programming language as a graph-based, strongly-typed, intellisense-enabled library.

This tutorial will show you how to:

Create a Vehicle Model
Add a Vehicle Service to the Vehicle Model
Distribute your Python Vehicle Model

Note

A Vehicle Model should be defined in its own package. This makes it possible to distribute the Vehicle Model later as a standalone package and to use it in different Vehicle App projects.

The creation of a new vehicle model is only required if the vehicle signals (like sensors and actuators) defined in the current version of the COVESA Vehicle Signal Specification (VSS) is not sufficient for the definition of your vehicle API. Otherwise you could use the default vehicle model we geneated for you, see Python Vehicle Model and C++ Vehicle Model.

Prerequisites

Visual Studio Code with the Python extension installed. For information on how to install extensions on Visual Studio Code, see VS Code Extension Marketplace.

Create a Vehicle Model from VSS specification

A Vehicle Model can be generated from a COVESA Vehicle Signal Specification (VSS). VSS introduces a domain taxonomy for vehicle signals, in the sense of classical attributes, sensors and actuators with the raw data communicated over vehicle buses and data. The Velocitas vehicle-model-generator creates a Vehicle Model from the given specification and generates a package for use in Vehicle App projects.

Follow the steps to generate a Vehicle Model.

Clone the vehicle-model-generator repository in a container volume.
In this container volume, clone the vehicle-signal-specification repository and if required checkout a particular branch:
```
git clone https://github.com/COVESA/vehicle_signal_specification

cd vehicle_signal_specification
git checkout <branch-name>
```
In case the VSS vspec doesn’t contain the required signals, you can create a vspec using the VSS Rule Set.
Execute the command
```
python3 gen_vehicle_model.py -I ./vehicle_signal_specification/spec ./vehicle_signal_specification/spec/VehicleSignalSpecification.vspec -l <lang> -T sdv_model -N sdv_model
```
Depending on the value of lang, which can assume the values python and cpp, this creates a sdv_model directory in the root of repository along with all generated source files for the given programming language.

Here is an overview of what is generated for every available value of lang:

lang output

python python sources and a setup.py ready to be used as python package

cpp c++ sources, headers and a CMakeLists.txt ready to be used as a CMake project

To have a custom model name, refer to README of vehicle-model-generator repository.
For python: Change the version of package in setup.py manually (defaults to 0.1.0).
Now the newly generated sdv_model can be used for distribution. (See Distributing your Vehicle Model)

lang	output
`python`	python sources and a `setup.py` ready to be used as python package
`cpp`	c++ sources, headers and a CMakeLists.txt ready to be used as a CMake project

Create a Vehicle Model Manually

Alternative to the generation from a VSS specification you could create the Vehicle Model manually. The following sections describing the required steps.

Python

Distributing your Vehicle Model

Once you have created your Vehicle Model either manually or via the Vehicle Model Generator, you need to distribute your model to use it in an application. Follow the links below for language specific tutorials on how to distribute your freshly created Vehicle Model.

Python
C++

Further information

Concept: SDK Overview
Tutorial: Setup and Explore Development Enviroment
Tutorial: Create a Vehicle App