### 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 __future__ import annotations
import operator
from typing import TYPE_CHECKING, Any, Collection
from airflow.timetables.base import DagRunInfo, DataInterval, TimeRestriction, Timetable
if TYPE_CHECKING:
    from pendulum import DateTime
    from sqlalchemy import Session
    from airflow.models.dataset import DatasetEvent
    from airflow.utils.types import DagRunType
class _TrivialTimetable(Timetable):
    """Some code reuse for "trivial" timetables that has nothing complex."""
    periodic = False
    can_run = False
    run_ordering = ("execution_date",)
    @classmethod
    def deserialize(cls, data: dict[str, Any]) -> Timetable:
        return cls()
    def __eq__(self, other: Any) -> bool:
        """As long as *other* is of the same type.
        This is only for testing purposes and should not be relied on otherwise.
        """
        if not isinstance(other, type(self)):
            return NotImplemented
        return True
    def serialize(self) -> dict[str, Any]: