Apple Inc.

Sandip Aine

Martin Levihn

Jamie R Lesser

Ujjwal Das Gupta

Trevor P Barron

Moritz Niendorf

Implementations described and claimed herein provide systems and methods for controlling an autonomous vehicle. In one implementation, the autonomous vehicle is navigated towards a flow of traffic with a first gap between first and second vehicles and a second gap following the second vehicle. A motion plan for directing the autonomous vehicle into the flow of traffic at an interaction zone is generated based on whether an ability of the autonomous vehicle to enter the interaction zone at the second gap exceeds a confidence threshold. The autonomous vehicle is autonomously navigated into the flow of traffic at the first gap when the confidence threshold is exceeded. The motion plan forgoes navigation of the autonomous vehicle into the flow of traffic at the first and second gaps when the ability of the autonomous vehicle to enter the interaction zone at the second gap does not exceed the confidence threshold.

Systems and methods for hedging for different gaps in an interaction zone

Systems and methods for vehicle lane change control are described. Some implementations may include determining a kinematic state of a vehicle moving in an origin lane; detecting, based on data from one or more sensors of the vehicle, objects that are moving in a target lane of the road; determining a headway constraint in terms of a preparation time, a preparation acceleration to be applied to the vehicle during the preparation time, and an execution time during which the vehicle is to transition from the origin lane to the target lane; determining values of the preparation time, the execution time, and the preparation acceleration subject to a set of constraints including the headway constraint; and determining a motion plan that will transition the vehicle from the origin lane to the target lane based at least in part on the preparation time, the execution time, and the preparation acceleration.

Vehicle lane change

Systems and methods for automated control of vehicle lane change maneuvers are disclosed. Some implementations may include detecting, based on data from a sensor in the first vehicle, one or more other vehicles that are moving in a target lane of the road. Some implementations may include determining, based on the kinematic state of the vehicle and a prediction of motion of the one or more other vehicles in the target lane, estimates of headway in relation to at least one of the one or more other vehicles in the target lane. Some implementations may include determining, based at least in part on the estimates of headway, overtake decisions for the one or more other vehicles traveling in the target lane. Some implementations may include determining a motion plan that will transition the first vehicle from the current lane to the target lane based the overtake decisions.

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Sunnyvale, CA, United States of America

Sandip Aine