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350. Oncoming Vehicle evaluation scenario

In the oncoming_vehicle evaluation scenario, the vehicle_actor drives in the oncoming lane adjacent to the Ego in the outgoing lane.

Scenario location: $FTX/logiq/scenario_library_post_match/oncoming_vehicles/oncoming_vehicle

350.1 Actors

The actors associated with this scenario are as follows:

Actor Description Type Depiction
ego Vehicle under test vehicle
vehicle_actor Oncoming vehicle vehicle
Figure 1: Oncoming Vehicle

350.2 Scenario phases

The phase descriptions are as follows:

350.2.1 oncoming_phase

Ego: The Ego drives in the outgoing lane.

vehicle_actor: The vehicle_actor drives in the oncoming lane adjacent to the Ego, and maintains a distance of at least max_distance_from_ego from the Ego.

350.3 Parameters

Use these parameters to constrain the scenario. If you do not set a specific value, the default value will be used.

Parameter Type Description Default value
min_distance_from_ego length Minimal geometric distance from the Ego to the oncoming vehicle during the entire scenario 0m
max_distance_from_ego length Maximal geometric distance from the Ego to the oncoming vehicle during the entire scenario 80m
min_oncoming_phase_duration time The minimal duration of the oncoming_phase phase 0.5s
max_oncoming_phase_duration time The maximal duration of the oncoming_phase phase 8s

The input items inherited from the sut.logiq_base_vehicle_scenario scenario are as follows:

Parameter Type Description Default value
kinds list of evaluation_object_kind The possible kinds of vehicle_actor in the scenario No default value

350.4 Metrics

350.4.1 Coverage

[Click] The coverage items inherited from the sut.logiq_base_vehicle_scenario scenario are as follows:
Item Description Range Unit/Type
vehicle_speed_at_start Speed of the agent at the start of the scenario [0..150), every: 10.0 mph
[Click] The coverage items inherited from the sut.logiq_base_scenario scenario are as follows:
Item Description Range Unit/Type
ego_speed_at_start Longitudinal speed of the Ego at the start of the scenario [0..160), every: 10.0 mph

350.4.2 KPI

[Click] The KPIs inherited from the sut.logiq_base_vehicle_scenario scenario are as follows:
Item Description Range Unit/Type
vehicle_object_kind Object kind as derived from Foretify object, person, cyclist, vehicle, truck, trailer, fod, animal, sign, bus, motorcycle, emergency_vehicle, stationary_vehicle evaluation_object_kind
vehicle_tracking_id The tracking id of the agent as described in the object list data. If the data comes from a generative run, the UID will be used string
vehicle_avg_speed Average longitudinal speed of the agent throughout the scenario mph
vehicle_max_speed Maximum speed of the agent throughout the scenario mph
vehicle_min_speed Minimum speed of the agent throughout the scenario mph
vehicle_max_lon_acceleration Maximum longitudinal acceleration of the agent throughout the scenario mpsps
vehicle_min_lon_acceleration Minimum longitudinal acceleration of the agent throughout the scenario mpsps
ego_min_ttc_to_vehicle Minimal time to collision with the reference vehicle throughout the scenario s
ego_min_mttc_to_vehicle Minimal modified time to collision with the reference vehicle throughout the scenario s
[Click] The KPIs inherited from the sut.logiq_base_scenario scenario are as follows:
Item Description Range Unit/Type
ego_max_lon_acceleration Maximum acceleration of the Ego throughout the scenario mpsps
ego_min_lon_acceleration Minimum acceleration of the Ego throughout the scenario mpsps
ego_min_speed Minimum longitudinal speed of the Ego throughout the scenario mph
ego_avg_speed Average longitudinal speed of the Ego throughout the scenario mph
ego_max_speed Maximum longitudinal speed of the Ego throughout the scenario mph
interval_duration Interval duration of the scenario s