自动驾驶云服务 OCTOPUS-逻辑场景 Logical scenario

时间：2023-12-19 19:10:35

逻辑场景 Logical scenario

逻辑场景的参数声明通过：范围型[最小值..最大值] 和枚举型[值1, 值2] 的方式来实现泛化:

范围型支持float和scalar类型
枚举型支持int, float, bool, str, enum和scalar类型，且需要保证枚举列表中的元素均为相同类型.

例1：范围型

m_value: float = [2.0..3.0]
v: speed = [5mps..10mps]
delay: time = [40s..60s]
m_a: acceleration = [0.00mpss..0.03mpss]

例2：枚举型

m_ id: int = [-1, 2]
m_value: float = [2.0, 3.0]
m_on_road: bool = [true, false]
Ego_name: string = ["Audi_A3_2009_black", "Audi_A3_2009_red"]
m_shape: dynamics_shape = [linear, sinusoidal]
m_side: side_left_right = [left, right]
v: speed = [5mps, 7mps, 10mps]
m_a: acceleration = [0.01mpss, 0.03mpss]
delay: time = [40s, 60s, 100s]

通过泛化参数，可以实现实体entity 、动作act ，以及修饰器modifier 的泛化.
Struct类型不能直接泛化，而是通过泛化参数来进行泛化.

例1：entity泛化

Ego_name: string = ["Audi_A3_2009_black", "Audi_A3_2009_red"]
Ego_controller: string = "DefaultDriver"
Ego: vehicle with:
    keep(it.name == Ego_name)
    keep(it.initial_bm == Ego_controller)

例2：act泛化

m_lateral: bool = [true, false]
m_speed: speed = [5mps..15mps]
m_rate_profile: dynamics_shape = linear
Ego.activate_controller(m_lateral, true)
Ego.change_speed(target: m_speed, rate_peak: 0.0mpss, rate_profile: m_rate_profile)

例3：modifier泛化

m_speed: speed = [5mps..15mps]
Ego.assign_init_speed() with:
    speed(speed: m_speed)

例4：Struct类型泛化

m_lane_id: int = [-1, 2]
m_odr: odr_point = map.create_odr_point(road_id: '0', lane_id:m_lane_id, s: 5.0m, t: 0.0m)

m_x: distance = [2m..7.5m]
m_position_3d: position_3d = map.create_xyz_point(x: m_x, y: 10.0m ,z: 0.0m)

m_pose_3d: pose_3d with:
    keep(it.odr_point == m_odr)

父主题： 参数声明 Parameter Declarations

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