### 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 the dag file processor creates multiple dagruns
        if a dag is scheduled with 'timedelta' and catchup=True
        """
        dag = DAG(
            "test_scheduler_dagrun_once_with_timedelta_and_catchup_true",
            start_date=timezone.datetime(2020, 5, 1),
            schedule=timedelta(days=1),
            catchup=True,
        )
        next_info = dag.next_dagrun_info(None)
        assert next_info and next_info.logical_date == timezone.datetime(2020, 5, 1)
        next_info = dag.next_dagrun_info(next_info.data_interval)
        assert next_info and next_info.logical_date == timezone.datetime(2020, 5, 2)
        next_info = dag.next_dagrun_info(next_info.data_interval)
        assert next_info and next_info.logical_date == timezone.datetime(2020, 5, 3)
        
        next_info = dag.next_dagrun_info(next_info.data_interval)
        assert next_info and next_info.logical_date == timezone.datetime(2020, 5, 4)
    def test_next_dagrun_info_timetable_exception(self, caplog):
        """Test the DAG does not crash the scheduler if the timetable raises an exception."""
        class FailingTimetable(Timetable):