mirror of
https://github.com/firestar5683/StarPilot.git
synced 2026-07-14 22:02:09 +08:00
Adeeb Shihadeh
47 lines
1.8 KiB
Python
47 lines
1.8 KiB
Python
import pytest
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import itertools
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from openpilot.common.parameterized import parameterized_class
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from cereal import log
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from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import get_safe_obstacle_distance, get_stopped_equivalence_factor, get_T_FOLLOW
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from openpilot.selfdrive.test.longitudinal_maneuvers.maneuver import Maneuver
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def desired_follow_distance(v_ego, v_lead, t_follow=None):
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if t_follow is None:
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t_follow = get_T_FOLLOW()
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return get_safe_obstacle_distance(v_ego, t_follow) - get_stopped_equivalence_factor(v_lead)
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def run_following_distance_simulation(v_lead, t_end=100.0, e2e=False, personality=0):
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man = Maneuver(
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'',
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duration=t_end,
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initial_speed=float(v_lead),
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lead_relevancy=True,
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initial_distance_lead=100,
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speed_lead_values=[v_lead],
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breakpoints=[0.],
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e2e=e2e,
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personality=personality,
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)
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valid, output = man.evaluate()
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assert valid
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return output[-1,2] - output[-1,1]
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@parameterized_class(("e2e", "personality", "speed"), itertools.product(
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[True, False], # e2e
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[log.LongitudinalPersonality.relaxed, # personality
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log.LongitudinalPersonality.standard,
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log.LongitudinalPersonality.aggressive],
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[0,10,35])) # speed
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class TestFollowingDistance:
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def test_following_distance(self):
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v_lead = float(self.speed)
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simulation_steady_state = run_following_distance_simulation(v_lead, e2e=self.e2e, personality=self.personality)
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correct_steady_state = desired_follow_distance(v_lead, v_lead, get_T_FOLLOW(self.personality))
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err_ratio = 0.2 if self.e2e else 0.1
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abs_err_margin = 0.5 if v_lead > 0.0 else 1.15
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assert simulation_steady_state == pytest.approx(correct_steady_state, abs=err_ratio * correct_steady_state + abs_err_margin)
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