Planning Evaluator#
Purpose#
This package provides nodes that generate metrics to evaluate the quality of planning and control.
Inner-workings / Algorithms#
The evaluation node calculates metrics each time it receives a trajectory T(0)
.
Metrics are calculated using the following information:
- the trajectory
T(0)
itself. - the previous trajectory
T(-1)
. - the reference trajectory assumed to be used as the reference to plan
T(0)
. - the current ego pose.
- the set of objects in the environment.
These information are maintained by an instance of class MetricsCalculator
which is also responsible for calculating metrics.
Stat#
Each metric is calculated using a Stat
instance which contains
the minimum, maximum, and mean values calculated for the metric
as well as the number of values measured.
Metric calculation and adding more metrics#
All possible metrics are defined in the Metric
enumeration defined
include/planning_evaluator/metrics/metric.hpp
.
This file also defines conversions from/to string as well as human readable descriptions
to be used as header of the output file.
The MetricsCalculator
is responsible for calculating metric statistics
through calls to function:
Stat<double> MetricsCalculator::calculate(const Metric metric, const Trajectory & traj) const;
Adding a new metric M
requires the following steps:
metrics/metric.hpp
: addM
to theenum
, to the from/to string conversion maps, and to the description map.metrics_calculator.cpp
: addM
to theswitch/case
statement of thecalculate
function.- Add
M
to theselected_metrics
parameters.
Inputs / Outputs#
Inputs#
Name | Type | Description |
---|---|---|
~/input/trajectory |
autoware_auto_planning_msgs::msg::Trajectory |
Main trajectory to evaluate |
~/input/reference_trajectory |
autoware_auto_planning_msgs::msg::Trajectory |
Reference trajectory to use for deviation metrics |
~/input/objects |
autoware_auto_perception_msgs::msg::PredictedObjects |
Obstacles |
Outputs#
Each metric is published on a topic named after the metric name.
Name | Type | Description |
---|---|---|
~/metrics |
diagnostic_msgs::msg::DiagnosticArray |
DiagnosticArray with a DiagnosticStatus for each metric |
When shut down, the evaluation node writes the values of the metrics measured during its lifetime
to a file as specified by the output_file
parameter.
Parameters#
Name | Type | Description |
---|---|---|
output_file |
string |
file used to write metrics |
ego_frame |
string |
frame used for the ego pose |
selected_metrics |
List | metrics to measure and publish |
trajectory.min_point_dist_m |
double |
minimum distance between two successive points to use for angle calculation |
trajectory.lookahead.max_dist_m |
double |
maximum distance from ego along the trajectory to use for calculation |
trajectory.lookahead.max_time_m |
double |
maximum time ahead of ego along the trajectory to use for calculation |
obstacle.dist_thr_m |
double |
distance between ego and the obstacle below which a collision is considered |
Assumptions / Known limits#
There is a strong assumption that when receiving a trajectory T(0)
,
it has been generated using the last received reference trajectory and objects.
This can be wrong if a new reference trajectory or objects are published while T(0)
is being calculated.
Precision is currently limited by the resolution of the trajectories. It is possible to interpolate the trajectory and reference trajectory to increase precision but would make computation significantly more expensive.
Future extensions / Unimplemented parts#
- Use
Route
orPath
messages as reference trajectory. - RSS metrics (done in another node https://tier4.atlassian.net/browse/AJD-263).
- Add option to publish the
min
andmax
metric values. For now only themean
value is published. motion_evaluator_node
.- Node which constructs a trajectory over time from the real motion of ego.
- Only a proof of concept is currently implemented.