### 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.
def generate_run_id(self, *, run_type, logical_date, data_interval, **extra) -> str:
            return "abc"
    dag = DAG(dag_id="test", start_date=DEFAULT_DATE, schedule=CustomRunIdTimetable())
    dag_run = dag.create_dagrun(
        run_type=DagRunType.MANUAL,
        state=DagRunState.QUEUED,
        execution_date=DEFAULT_DATE,
        data_interval=(DEFAULT_DATE, DEFAULT_DATE),
    )
    assert dag_run.run_id == "abc"
@pytest.mark.parametrize(
    "run_id_type",
    [DagRunType.BACKFILL_JOB, DagRunType.SCHEDULED, DagRunType.DATASET_TRIGGERED],
)
def test_create_dagrun_disallow_manual_to_use_automated_run_id(run_id_type: DagRunType) -> None:
    dag = DAG(dag_id="test", start_date=DEFAULT_DATE, schedule="@daily")
    run_id = run_id_type.generate_run_id(DEFAULT_DATE)
    with pytest.raises(ValueError) as ctx:
        dag.create_dagrun(
            run_type=DagRunType.MANUAL,
            run_id=run_id,
            execution_date=DEFAULT_DATE,
            data_interval=(DEFAULT_DATE, DEFAULT_DATE),
            state=DagRunState.QUEUED,
        )
    assert str(ctx.value) == (
        f"A manual DAG run cannot use ID {run_id!r} since it is reserved for {run_id_type.value} runs"
    )