### 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.
dag = DAG("test_schedule_interval_arg", schedule_interval="*/5 * * * *")
        assert dag.timetable == cron_timetable("*/5 * * * *")
        assert dag.schedule_interval == "*/5 * * * *"
        assert dag.timetable.description == "Every 5 minutes"
    def test_timetable_still_works(self):
        dag = DAG("test_schedule_interval_arg", timetable=cron_timetable("*/6 * * * *"))
        assert dag.timetable == cron_timetable("*/6 * * * *")
        assert dag.schedule_interval == "*/6 * * * *"
        assert dag.timetable.description == "Every 6 minutes"
    @pytest.mark.parametrize(
        "timetable, expected_description",
        [
            (NullTimetable(), "Never, external triggers only"),
            (cron_timetable("0 0 * * *"), "At 00:00"),
            (cron_timetable("@daily"), "At 00:00"),
            (cron_timetable("0 0 * * 0"), "At 00:00, only on Sunday"),
            (cron_timetable("@weekly"), "At 00:00, only on Sunday"),
            (cron_timetable("0 0 1 * *"), "At 00:00, on day 1 of the month"),
            (cron_timetable("@monthly"), "At 00:00, on day 1 of the month"),
            (cron_timetable("0 0 1 */3 *"), "At 00:00, on day 1 of the month, every 3 months"),
            (cron_timetable("@quarterly"), "At 00:00, on day 1 of the month, every 3 months"),
            (cron_timetable("0 0 1 1 *"), "At 00:00, on day 1 of the month, only in January"),
            (cron_timetable("@yearly"), "At 00:00, on day 1 of the month, only in January"),
            (cron_timetable("5 0 * 8 *"), "At 00:05, only in August"),
            (OnceTimetable(), "Once, as soon as possible"),
            (delta_timetable(datetime.timedelta(days=1)), ""),
            (cron_timetable("30 21 * * 5 1"), ""),
        ],
    )
    def test_description_from_timetable(self, timetable, expected_description):