### 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.
from airflow.timetables.interval import _DataIntervalTimetable
        warnings.warn(
            "`DAG.previous_schedule()` is deprecated.",
            category=RemovedInAirflow3Warning,
            stacklevel=2,
        )
        if not isinstance(self.timetable, _DataIntervalTimetable):
            return None
        return self.timetable._get_prev(timezone.coerce_datetime(dttm))
    def get_next_data_interval(self, dag_model: DagModel) -> DataInterval | None:
        """Get the data interval of the next scheduled run.
        For compatibility, this method infers the data interval from the DAG's
        schedule if the run does not have an explicit one set, which is possible
        for runs created prior to AIP-39.
        This function is private to Airflow core and should not be depended on as a
        part of the Python API.
        :meta private:
        """
        if self.dag_id != dag_model.dag_id:
            raise ValueError(f"Arguments refer to different DAGs: {self.dag_id} != {dag_model.dag_id}")
        if dag_model.next_dagrun is None:  
            return None
        data_interval = dag_model.next_dagrun_data_interval
        if data_interval is not None:
            return data_interval
        
        
        
        return self.infer_automated_data_interval(dag_model.next_dagrun)
    def get_run_data_interval(self, run: DagRun) -> DataInterval: