Motional Ad LLC

Delphi Technologies, Inc.

Aptiv Technologies Limited

Ludong Sun

Zachary Thomas Batts

Junqing Wei

Jarrod M Snider

Michael H Laur

Qian Wang

Yiming Zhao

Stephanie Lee

Ky Woodard

Lin Zhao

Junsung Kim

Serge Lambermont

Indu Vijayan

Ryan S Middleton

Brian R Hilnbrand

Jonathan L Wieskamp

Miao Yan

Among other things, systems and methods are described for brake arbitration. Safe stop requests are obtained. A safe stop request is associated with a deceleration value of a vehicle in motion. Safe stop activations associated with the safe stop request are determined, wherein the safe stop activations are associated with predetermined deceleration values. An automated emergency (AEB) system deceleration command is calculated. Arbitration is performed between the deceleration values associated with the safe stop request, predetermined deceleration values associated with the safe stop activations, and the deceleration value calculated from data captured by the AEB system to determine a final deceleration output.

Brake arbitration

Among other things, we describe techniques for implementing a vehicle response to sensor failure. In general, one innovative aspect of the subject matter described in this specification can be embodied in methods that include receiving information from a plurality of sensors coupled to a vehicle, determining that a level of confidence of the received information from at least one sensor of a first subset of sensors of the plurality of sensors is less than a first threshold, comparing a number of sensors in the first subset of sensors to a second threshold, and adjusting the driving capability of the vehicle to rely on information received from a second subset of sensors of the plurality of sensors, wherein the second subset of sensors excludes the at least one sensor of the first subset of sensors.

Systems and methods for implementing an autonomous vehicle response to sensor failure

An operating system for an automated vehicle includes a failure-detector and a controller. The failure-detector detects a component-failure on a host-vehicle. Examples of the component-failure include a flat-tire and engine trouble that reduces engine-power. The controller operates the host-vehicle based on a dynamic-model. The dynamic-model is varied based on the component-failure detected by the failure-detector.

Adaptive dynamic model for automated vehicle

A system includes one or more sensor systems, a controller-circuit, a first module, and a second module. The sensor systems are configured to determine position relationship data between a roadway and a host vehicle. The sensor system includes at least one of a computer-vision system, a radar system, and a LIDAR system. The controller-circuit is configured to receive and transform the position relationship data to effect steering control of the host vehicle. The first module is controlled by the controller-circuit to effect the steering control when the steering control transitions from a manual-mode to an automated mode. The second module is controlled by the controller-circuit to effect steering control of the host vehicle after control by the first module and upon meeting a prescribed condition.

Automated vehicle steering control for transitioning from manual mode to automated mode

An apparatus is provided which includes a processing circuit and a plurality of sensors connected to a vehicle, where at least one of the plurality of sensors is positioned on an undercarriage of the vehicle. The plurality of sensors can detect variations in a road on which the vehicle is traveling. The plurality of sensors can also generate information corresponding to the variations of the road. The plurality of sensors can also transmit the information corresponding to the variations in the road to the processing circuit. The information collected by the plurality of sensors may then be used to augment a driving capability of the vehicle.

Detecting road anomalies

A rumble-strip following system for automated vehicle steering includes a vibration-detector, a steering-device, and a controller-circuit. The vibration-detector is configured to detect vibration experienced by a host-vehicle traveling a roadway. The steering-device is configured to steer the host-vehicle. The controller-circuit is in communication with the vibration-detector and the steering-device. The controller-circuit is configured to determine that the vibration is indicative of a tire of the host-vehicle contacting a rumble-strip arranged parallel to a heading of the roadway, and operate the steering-device so the tire follows the rumble-strip.

Rumble strip following for automated vehicle steering

An intent communication system includes one or more sensors, a controller-circuit, and a broadcast device. The sensors may include one or more of a Light Detection and Ranging (LiDAR), a radar, and a computer vision system. The controller-circuit is disposed in a host vehicle. The controller-circuit is configured to determine, based one or more signals from the one or more sensors, an impending vehicle maneuver. The broadcast device is located in the host vehicle, and is configured to broadcast a broadcast signal containing information directed to the impending vehicle maneuver to at least one vehicle determined to be in a vicinity of the impending vehicle maneuver.

Vehicle intent communication system

A tire-wear detection system for an automated vehicle includes a steering-angle-sensor, a vehicle-path-detector, and a controller. The steering-angle-sensor indicates a steering-angle of a host-vehicle. The vehicle-path-detector indicates a turning-radius of the host-vehicle. The controller is in communication with the steering-angle-sensor and the vehicle-path-detector. The controller determines a wear-status of a tire of the host-vehicle based on the turning-radius and the steering-angle.

Tire wear detection system for automated vehicle

A brake control system for operating brakes of an automated vehicle at slow speed includes a motion-detector and a controller. The motion-detector detects relative-movement of a host-vehicle relative to a stationary-feature located apart from the host-vehicle. The controller is configured to operate brakes of the host-vehicle. The controller determines a vehicle-speed of the host-vehicle based on the relative-movement when the vehicle-speed is less than a speed-threshold, and regulates brake-pressure of the brakes based on the vehicle-speed.

Slow speed automated vehicle brake pressure control system

A rear-wheel steering system suitable for use on an automated vehicle includes an object-detector, and actuator, and a controller. The object-detector is used to detect an object proximate to a host-vehicle. The actuator is used to adjust a rear-steering-angle of rear-wheels of the host-vehicle. The controller is in communication with the object-detector and the actuator. The controller is configured to determine a location of the object relative to the host-vehicle based on information from the object-detector, and operate the actuator to avoid the object when the host-vehicle moves.

Automated vehicle rear-wheel steering system

A humanized steering system for an automated vehicle includes one or more steering-wheels operable to steer a vehicle, an angle-sensor configured to determine a steering-angle of the steering-wheels, a hand-wheel used by an operator of the vehicle to influence the steering-angle and thereby manually steer the vehicle, a steering-actuator operable to influence the steering-angle thereby steer the vehicle when the operator does not manually steer the vehicle, a position-sensor operable to indicate a relative-position an object proximate to the vehicle, and a controller. The controller is configured to receive the steering-angle and the relative-position, determine, using deep-learning techniques, a steering-model based on the steering-angle and the relative-position, and operate the steering-actuator when the operator does not manually steer the vehicle to steer the vehicle in accordance with the steering-model, whereby the vehicle is steered in a manner similar to how the operator manually steers the vehicle.

Humanized steering model for automated vehicles

A system for changing a control-mode of an automated vehicle from automated-control to manual-control includes an operator-detection device and a controller. The operator-detection device is operable to detect a readiness-state of an operator of a vehicle while a control-mode of the vehicle is automated-control. The controller is configured to forecast a future-time when the control-mode of the vehicle should change from automated-control to manual-control and determine a take-over-interval for an operator to assume manual-control of the vehicle once notified. The take-over-interval is determined based on the readiness-state. The controller is also configured to notify the operator that the control-mode of the vehicle should change from automated-control to manual-control no later than the take-over-interval prior to the future-time.

Automated vehicle control with time to take-over compensation

A system for automated operation of a host-vehicle includes a sensor, a data-source, and a controller. The sensor is installed in a host-vehicle. The sensor is operable to determine a state-of-awareness of an operator of the host-vehicle. The data-source provides route-data used for automated operation of the host-vehicle. The route-data includes a map and a control-rule for navigating the map. The controller is in communication with the sensor and the data-source. The controller is configured to operate the host-vehicle during automated operation of the host-vehicle in accordance with the route-data. The controller is also configured to modify the control-rule based on the state-of-awareness of the operator.

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Pittsburgh, PA, United States of America

Ludong Sun