### 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.
"Param `timetable` is deprecated and will be removed in a future release. "
                "Please use `schedule` instead. ",
                RemovedInAirflow3Warning,
                stacklevel=2,
            )
        self.timetable: Timetable
        self.schedule_interval: ScheduleInterval
        self.dataset_triggers: Collection[Dataset] = []
        if isinstance(schedule, Collection) and not isinstance(schedule, str):
            from airflow.datasets import Dataset
            if not all(isinstance(x, Dataset) for x in schedule):
                raise ValueError("All elements in 'schedule' should be datasets")
            self.dataset_triggers = list(schedule)
        elif isinstance(schedule, Timetable):
            timetable = schedule
        elif schedule is not NOTSET:
            schedule_interval = schedule
        if self.dataset_triggers:
            self.timetable = DatasetTriggeredTimetable()
            self.schedule_interval = self.timetable.summary
        elif timetable:
            self.timetable = timetable
            self.schedule_interval = self.timetable.summary
        else:
            if isinstance(schedule_interval, ArgNotSet):
                schedule_interval = DEFAULT_SCHEDULE_INTERVAL
            self.schedule_interval = schedule_interval
            self.timetable = create_timetable(schedule_interval, self.timezone)
        if isinstance(template_searchpath, str):
            template_searchpath = [template_searchpath]