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Velocity Planning Problem

VelocityPlanningProblem dataclass

Transforms planning problem in velocity planning problem

Source code in commonroad_velocity_planner/velocity_planning_problem.py 
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@dataclass
class VelocityPlanningProblem:
    """
    Transforms planning problem in velocity planning problem
    """

    planning_problem: PlanningProblem

    sampled_ref_path: np.ndarray

    sampled_start_idx: int
    sampled_goal_idx: int

    interpoint_distance: float
    path_length_per_point: np.ndarray
    path_curvature: np.ndarray
    speed_limits: np.ndarray

    v_initial: float
    v_stop: float
    a_initial: float
    a_stop: float

    def __post_init__(self):
        _ = self.sanity_check()

    def debug_print(self):
        _logger = logging.getLogger(
            name="IVelocityPlanner.velocity_planning_problem.VelocityPlanningProblem"
        )
        _logger.info(f"VPP: a={self.a_initial}")
        _logger.info(f"VPP: v={self.v_initial}")

    def sanity_check(self) -> bool:
        """
        Sanity check for velocity problem dimensions
        :return: true, if correct, else false
        """

        if not (
            self.sampled_ref_path.shape[0]
            == self.path_length_per_point.shape[0]
            == self.path_curvature.shape[0]
            == self.speed_limits.shape[0]
        ):
            _logger = logging.getLogger(
                name="IVelocityPlanner.velocity_planning_problem.VelocityPlanningProblem"
            )
            _logger.warning(
                "\n \n sanity check for velcoty planning problem failed! \n\n"
                f"len sampled refpath: {self.sampled_ref_path.shape[0]} \n"
                f"len sampled path length per proint: {self.path_length_per_point.shape[0]} \n"
                f"len sampled path curvature per proint: {self.path_curvature.shape[0]} \n"
                f"len sampled speed limits: {self.speed_limits.shape[0]} \n"
            )
            retval = False
        else:
            retval = True

        return retval

sanity_check()

Sanity check for velocity problem dimensions

Returns:

Type Description
bool

true, if correct, else false
Source code in commonroad_velocity_planner/velocity_planning_problem.py 
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def sanity_check(self) -> bool:
    """
    Sanity check for velocity problem dimensions
    :return: true, if correct, else false
    """

    if not (
        self.sampled_ref_path.shape[0]
        == self.path_length_per_point.shape[0]
        == self.path_curvature.shape[0]
        == self.speed_limits.shape[0]
    ):
        _logger = logging.getLogger(
            name="IVelocityPlanner.velocity_planning_problem.VelocityPlanningProblem"
        )
        _logger.warning(
            "\n \n sanity check for velcoty planning problem failed! \n\n"
            f"len sampled refpath: {self.sampled_ref_path.shape[0]} \n"
            f"len sampled path length per proint: {self.path_length_per_point.shape[0]} \n"
            f"len sampled path curvature per proint: {self.path_curvature.shape[0]} \n"
            f"len sampled speed limits: {self.speed_limits.shape[0]} \n"
        )
        retval = False
    else:
        retval = True

    return retval

VppBuilder

Builds the velocity planning problem, smoothes and downsamples reference path.

Source code in commonroad_velocity_planner/velocity_planning_problem.py 
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class VppBuilder:
    """
    Builds the velocity planning problem, smoothes and downsamples reference path.
    """

    @staticmethod
    def build_vpp(
        reference_path: ReferencePath,
        planning_problem: PlanningProblem,
        resampling_distance: float = 2,
        smoothing_strategy: SmoothingStrategy = SmoothingStrategy.ELASTIC_BAND,
        default_goal_velocity: float = 0.0,
        default_goal_acceleration: float = 0.0,
        offset_start_idx: int = 2,
        offset_end_idx: int = 2,
    ) -> VelocityPlanningProblem:
        """
        Build velocity planning problem by downsampling and smoothing the reference path first
        :param reference_path: cr reference_path object
        :param planning_problem: cr planning problem
        :param resampling_distance: resampling distance
        :param planning_horizon: planning horizon
        :param smoothing_strategy: smoothing strategy
        :param default_goal_velocity: default goal velocity if problem does not contain one
        :param default_goal_acceleration: default goal velocity, if problem does not contain one.
        :return: velocity planning problem object
        """
        if resampling_distance is None:
            interpoint_distance = reference_path.average_interpoint_distance
        else:
            interpoint_distance = resampling_distance

        start_index = np.argmin(
            np.linalg.norm(
                reference_path.reference_path - reference_path.initial_state.position,
                axis=1,
            )
        )

        # get start and stop index of initial reference path
        start_distance = reference_path.path_length_per_point[start_index]
        stop_distance = reference_path.length_reference_path

        # resample before smoothing
        resampled_reference_path, path_length_per_point = (
            cubic_spline_arc_interpolation_2D(
                polyline=reference_path.reference_path,
                start_distance=start_distance,
                stop_distance=stop_distance,
                resampling_distance=resampling_distance,
            )
        )

        # smooth reference path
        smoothing_interface = ICurvatureSmoother()
        smoothed_reference_path = smoothing_interface.smooth(
            smoothing_strategy=smoothing_strategy,
            reference_path=resampled_reference_path,
            path_length_per_point=path_length_per_point,
        )

        # resample after smoothing
        resampled_reference_path, path_length_per_point = (
            cubic_spline_arc_interpolation_2D(polyline=smoothed_reference_path)
        )
        resampled_curvature = compute_scalar_curvature_from_polyline(
            resampled_reference_path
        )

        # curvature
        curvature_spline = CubicSpline(path_length_per_point, resampled_curvature)
        path_curvature = curvature_spline(path_length_per_point)

        # get speed limits
        speed_limits = get_speed_limits_from_lanelet_network(
            resampled_reference_path, reference_path.lanelet_network
        )
        initial_idx = project_initial_state_on_ref_path(
            resampled_reference_path, planning_problem.initial_state
        )
        goal_idx = project_goal_on_ref_path(
            resampled_reference_path, planning_problem.goal
        )

        if initial_idx >= goal_idx:
            _logger = logging.getLogger(
                name="IVelocityPlanner.velocity_planning_problem.VppBuilder"
            )
            _logger.warning(
                "The planning problem is malformed, choosing last point of reference path as goal idx"
            )
            goal_idx = resampled_reference_path.shape[0] - 1

        if initial_idx + offset_start_idx >= goal_idx - offset_end_idx:
            _logger = logging.getLogger(
                name="IVelocityPlanner.velocity_planning_problem.VppBuilder"
            )
            _logger.warning(
                "Accounting for offsets, v_min constraint: initial_idx + offset_start >= goal_idx - offset_end cannot be computed"
            )

        return VelocityPlanningProblem(
            planning_problem=planning_problem,
            sampled_ref_path=resampled_reference_path,
            sampled_start_idx=initial_idx,
            sampled_goal_idx=goal_idx,
            interpoint_distance=interpoint_distance,
            path_length_per_point=path_length_per_point,
            path_curvature=path_curvature,
            speed_limits=speed_limits,
            v_initial=reference_path.initial_state.velocity,
            v_stop=get_goal_velocity(
                goal_region=planning_problem.goal,
                default_velocity=default_goal_velocity,
            ),
            a_initial=reference_path.initial_state.acceleration,
            a_stop=get_goal_acceleration(
                goal_region=planning_problem.goal,
                default_acceleration=default_goal_acceleration,
            ),
        )

build_vpp(reference_path, planning_problem, resampling_distance=2, smoothing_strategy=SmoothingStrategy.ELASTIC_BAND, default_goal_velocity=0.0, default_goal_acceleration=0.0, offset_start_idx=2, offset_end_idx=2) staticmethod

Build velocity planning problem by downsampling and smoothing the reference path first

Parameters:

Name Type Description Default
reference_path ReferencePath

cr reference_path object

 required
planning_problem PlanningProblem

cr planning problem

 required
resampling_distance float

resampling distance

 2
planning_horizon

planning horizon

 required
smoothing_strategy SmoothingStrategy

smoothing strategy

 ELASTIC_BAND
default_goal_velocity float

default goal velocity if problem does not contain one

 0.0
default_goal_acceleration float

default goal velocity, if problem does not contain one.

 0.0

Returns:

Type Description
VelocityPlanningProblem

velocity planning problem object
Source code in commonroad_velocity_planner/velocity_planning_problem.py 
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@staticmethod
def build_vpp(
    reference_path: ReferencePath,
    planning_problem: PlanningProblem,
    resampling_distance: float = 2,
    smoothing_strategy: SmoothingStrategy = SmoothingStrategy.ELASTIC_BAND,
    default_goal_velocity: float = 0.0,
    default_goal_acceleration: float = 0.0,
    offset_start_idx: int = 2,
    offset_end_idx: int = 2,
) -> VelocityPlanningProblem:
    """
    Build velocity planning problem by downsampling and smoothing the reference path first
    :param reference_path: cr reference_path object
    :param planning_problem: cr planning problem
    :param resampling_distance: resampling distance
    :param planning_horizon: planning horizon
    :param smoothing_strategy: smoothing strategy
    :param default_goal_velocity: default goal velocity if problem does not contain one
    :param default_goal_acceleration: default goal velocity, if problem does not contain one.
    :return: velocity planning problem object
    """
    if resampling_distance is None:
        interpoint_distance = reference_path.average_interpoint_distance
    else:
        interpoint_distance = resampling_distance

    start_index = np.argmin(
        np.linalg.norm(
            reference_path.reference_path - reference_path.initial_state.position,
            axis=1,
        )
    )

    # get start and stop index of initial reference path
    start_distance = reference_path.path_length_per_point[start_index]
    stop_distance = reference_path.length_reference_path

    # resample before smoothing
    resampled_reference_path, path_length_per_point = (
        cubic_spline_arc_interpolation_2D(
            polyline=reference_path.reference_path,
            start_distance=start_distance,
            stop_distance=stop_distance,
            resampling_distance=resampling_distance,
        )
    )

    # smooth reference path
    smoothing_interface = ICurvatureSmoother()
    smoothed_reference_path = smoothing_interface.smooth(
        smoothing_strategy=smoothing_strategy,
        reference_path=resampled_reference_path,
        path_length_per_point=path_length_per_point,
    )

    # resample after smoothing
    resampled_reference_path, path_length_per_point = (
        cubic_spline_arc_interpolation_2D(polyline=smoothed_reference_path)
    )
    resampled_curvature = compute_scalar_curvature_from_polyline(
        resampled_reference_path
    )

    # curvature
    curvature_spline = CubicSpline(path_length_per_point, resampled_curvature)
    path_curvature = curvature_spline(path_length_per_point)

    # get speed limits
    speed_limits = get_speed_limits_from_lanelet_network(
        resampled_reference_path, reference_path.lanelet_network
    )
    initial_idx = project_initial_state_on_ref_path(
        resampled_reference_path, planning_problem.initial_state
    )
    goal_idx = project_goal_on_ref_path(
        resampled_reference_path, planning_problem.goal
    )

    if initial_idx >= goal_idx:
        _logger = logging.getLogger(
            name="IVelocityPlanner.velocity_planning_problem.VppBuilder"
        )
        _logger.warning(
            "The planning problem is malformed, choosing last point of reference path as goal idx"
        )
        goal_idx = resampled_reference_path.shape[0] - 1

    if initial_idx + offset_start_idx >= goal_idx - offset_end_idx:
        _logger = logging.getLogger(
            name="IVelocityPlanner.velocity_planning_problem.VppBuilder"
        )
        _logger.warning(
            "Accounting for offsets, v_min constraint: initial_idx + offset_start >= goal_idx - offset_end cannot be computed"
        )

    return VelocityPlanningProblem(
        planning_problem=planning_problem,
        sampled_ref_path=resampled_reference_path,
        sampled_start_idx=initial_idx,
        sampled_goal_idx=goal_idx,
        interpoint_distance=interpoint_distance,
        path_length_per_point=path_length_per_point,
        path_curvature=path_curvature,
        speed_limits=speed_limits,
        v_initial=reference_path.initial_state.velocity,
        v_stop=get_goal_velocity(
            goal_region=planning_problem.goal,
            default_velocity=default_goal_velocity,
        ),
        a_initial=reference_path.initial_state.acceleration,
        a_stop=get_goal_acceleration(
            goal_region=planning_problem.goal,
            default_acceleration=default_goal_acceleration,
        ),
    )