### Body

There are some use cases where users want to trigger new DAG run as soon as one finished. This is a request I've seen several times with some variations (for example like this [Stackoverflow question](https://stackoverflow.com/q/75623153/14624409)) but the basic request is the same.

The workaround users do to get such functionality is place `TriggerDagRunOperator` as last task of their DAG invoking the same DAG:

```
from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule=None,
) as dag:
    task = EmptyOperator(task_id="first")
    trigger = TriggerDagRunOperator(
        task_id="trigger",
        trigger_dag_id="example",
    )

    task >> trigger

```

As you can see this works nicely:
![Screenshot 2023-03-03 at 14 20 51](https://user-images.githubusercontent.com/45845474/222718862-dfde8a41-24b6-4991-b318-b7f9784514f6.png)

My suggestion is to add first class support for this use case, so the above example will be changed to:

```

from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule="@continues",
) as dag:
    task = EmptyOperator(task_id="first")
```

I guess it won't exactly be `"@continues"` but more likely new [ScheduleArg](https://github.com/apache/airflow/blob/8b8552f5c4111fe0732067d7af06aa5285498a79/airflow/models/dag.py#L127) type but I show it like that just for simplification of the idea.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
"""
        Test that when 'params' exists as a key passed to the default_args dict
        in addition to params being passed explicitly as an argument to the
        dag, that the 'params' key of the default_args dict is merged with the
        dict of the params argument.
        """
        params1 = {"parameter1": 1}
        params2 = {"parameter2": 2}
        dag = models.DAG("test-dag", default_args={"params": params1}, params=params2)
        assert params1["parameter1"] == dag.params["parameter1"]
        assert params2["parameter2"] == dag.params["parameter2"]
    def test_not_none_schedule_with_non_default_params(self):
        """
        Test if there is a DAG with not None schedule_interval and have some params that
        don't have a default value raise a error while DAG parsing
        """
        params = {"param1": Param(type="string")}
        with pytest.raises(AirflowException):
            models.DAG("dummy-dag", params=params)
    def test_dag_invalid_default_view(self):
        """
        Test invalid `default_view` of DAG initialization
        """
        with pytest.raises(AirflowException, match="Invalid values of dag.default_view: only support"):
            models.DAG(dag_id="test-invalid-default_view", default_view="airflow")
    def test_dag_default_view_default_value(self):