Motional Ad LLC

Delphi Technologies, Inc.

Aptiv Technologies Limited

Wenda Xu

Junqing Wei

Jarrod M Snider

Jong Ho Lee

Gaurav Bhatia

Yimu Wang

Yifan Yang

Guchan Ozbilgin

Junsung Kim

Serge Lambermont

Shu-Kai Lin

Xiaojun Sun

Mochan Shrestha

Baxter Smith

The subject matter described in this specification is directed to a system and techniques for operating an autonomous vehicle (AV) at a multi-way stop intersection. After detecting the AV is at a primary stopline of the multi-way stop intersection, a planned travel path though the multi-way stop intersection is obtained. If the planned travel path of the AV through the multi-way stop intersection satisfies a set of one or more clearance criteria, the AV proceeds past the primary stopline. The clearance criteria include a criterion that is satisfied in response to detecting the AV is clear to safely merge into a travel lane corresponding to the planned travel path.

Navigating multi-way stop intersections with an autonomous vehicle

A sensor data fusion system for a vehicle with multiple sensors includes a first-sensor, a second-sensor, and a controller-circuit. The first-sensor is configured to output a first-frame of data and a subsequent-frame of data indicative of objects present in a first-field-of-view. The first-frame is characterized by a first-time-stamp, the subsequent-frame of data characterized by a subsequent-time-stamp different from the first-time-stamp. The second-sensor is configured to output a second-frame of data indicative of objects present in a second-field-of-view that overlaps the first-field-of-view. The second-frame is characterized by a second-time-stamp temporally located between the first-time-stamp and the subsequent-time-stamp. The controller-circuit is configured to synthesize an interpolated-frame from the first-frame and the subsequent-frame. The interpolated-frame is characterized by an interpolated-time-stamp that corresponds to the second-time-stamp. The controller-circuit fuses the interpolated-frame with the second-frame to provide a fused-frame of data characterized by the interpolated-time-stamp, and operates the host-vehicle in accordance with the fused-frame.

Data fusion system for a vehicle equipped with unsynchronized perception sensors

A scenario aware perception system () suitable for use on an automated vehicle includes a traffic-scenario detector (), an object-detection device (), and a controller (). The traffic-scenario detector () is used to detect a present-scenario () experienced by a host-vehicle (). The object-detection device () is used to detect an object () proximate to the host-vehicle (). The controller () is in communication with the traffic-scenario detector () and the object-detection device (). The controller () configured to determine a preferred-algorithm () used to identify the object (). The preferred-algorithm () is determined based on the present-scenario ().

Scenario aware perception system for an automated vehicle

A detection system includes a first-sensor, a second-sensor, and a controller. The first-sensor is mounted on a host-vehicle. The first-sensor detects objects in a first-field-of-view. The second-sensor is positioned at a second-location different than the first-location. The second-sensor detects objects in a second-field-of-view that at least partially overlaps the first-field of view. The controller is in communication with the first-sensor and the second-sensor. The controller selects the second-sensor to detect an object-of-interest in accordance with a determination that an obstruction blocks a first-line-of-sight between the first-sensor and the object-of-interest.

Detection system and method

A steering-system for an automated vehicle is provided. The system includes an object-detector and a controller. The object-detector indicates a height and/or a width of an object approached by a host-vehicle. The controller is configured to steer the host-vehicle and is in communication with the object-detector. The controller steers the host-vehicle to straddle the object when the height of the object is less than a ground-clearance of the host-vehicle, and/or the width of the object is less than a track-width of the host-vehicle.

Object height determination for automated vehicle steering control system

A radar system for an automated vehicle includes a digital-map, a radar, and a controller. The digital-map indicates a characteristic of a roadway traveled by a host-vehicle. The radar detects objects proximate to the host-vehicle. The radar is equipped with a range-setting that is selectively variable. The controller is in communication with the digital-map and the radar. The controller is configured to select the range-setting of the radar based on the characteristic of the roadway. The characteristic may be based on speed-limit, road-shape (e.g. curve-radius), a horizon-distance, and/or an obstruction (e.g. hill, sign, or building). The radar may be equipped with a frame-rate-setting (i.e. pulse repetition frequency or PRF) that is selectively variable, and the controller may be further configured to select the frame-rate-setting based on the characteristic of the roadway.

Variable range and frame-rate radar operation for automated vehicle

A system for operating an autonomous vehicle includes a passenger-detector and a controller-circuit. The passenger-detector is operable to determine a passenger-count of passengers present in a host-vehicle. The controller-circuit is in communication with the passenger-detector and vehicle-controls of the host-vehicle. The controller-circuit is configured to operate the host-vehicle in an autonomous-mode and in accordance with a parameter. The parameter is set to an empty-value when passenger-count is equal to zero, and the parameter is set to an occupied-value different from the empty-value when the passenger count is greater than zero.

Autonomous vehicle operation based on passenger-count

A system for operating an automated vehicle in a crowd of pedestrians includes an object-detector, optionally, a signal detector, and a controller. The object-detector detects pedestrians proximate to a host-vehicle. The signal-detector detects a signal-state displayed by a traffic-signal that displays a stop-state that indicates when the host-vehicle should stop so the pedestrians can cross in front of the host-vehicle, and displays a go-state that indicates when the pedestrians should stop passing in front of the host-vehicle so that the host-vehicle can go forward. The controller is in control of movement of the host-vehicle and in communication with the object-detector and the signal-detector. The controller operates the host-vehicle to stop the host-vehicle when the stop-state is displayed, and operates the host-vehicle to creep-forward after a wait-interval after the traffic-signal changes to the go-state when the pedestrians fail to stop passing in front of the host-vehicle.

Automated vehicle control strategy for pedestrian crowds

A safe-to-proceed system () for operating an automated vehicle proximate to an intersection () includes an intersection-detector (), a vehicle-detector (), and a controller (). The intersection-detector () is suitable for use on a host-vehicle (). The intersection-detector () is used to determine when a host-vehicle () is proximate to an intersection (). The vehicle-detector () is also suitable for use on the host-vehicle (). The vehicle-detector () is used to estimate a stopping-distance () of an other-vehicle () approaching the intersection (). The controller () is in communication with the intersection-detector () and the vehicle-detector (). The controller () is configured to prevent the host-vehicle () from entering the intersection () when the stopping-distance () indicates that the other-vehicle () will enter the intersection () before stopping.

Safe-to-proceed system for an automated vehicle

A driving-rule system () suitable to operate an automated includes a vehicle-detector () and a controller (). The vehicle-detector () is suitable for use on a host-vehicle (). The vehicle-detector () is used to detect movement of an other-vehicle () proximate to the host-vehicle (). The controller () is in communication with the vehicle-detector (). The controller () is configured to operate the host-vehicle () in accordance with a driving-rule (), detect an observed-deviation () of the driving-rule () by the other-vehicle (), and modify the driving-rule () based on the observed-deviation ().

Automated vehicle operating system with driving-rule modification based on observation of another vehicle

An operating system for an automated vehicle equipped with limited field-of-view sensors is provided. The system includes an object-detector and a controller. The object-detector detects objects proximate to a host-vehicle. A field-of-view of the object-detector is characterized by a preferred-portion of the field-of-view, where the preferred-portion is characterized as preferred for using the object-detector. The controller is in communication with the object-detector. The controller steers the host-vehicle to align the preferred-portion with a detected-object. The system optionally includes an intersecting-road-indicator that indicates an intersecting-road connected to an intersection approached by the host-vehicle, and the controller is in communication with the intersecting-road-indicator. The controller designates an intersecting-road as the detected-object, and steers the host-vehicle to align the preferred-portion of the object-detector with the intersecting-road when the host-vehicle approaches the intersection.

Automated vehicle operation to compensate for sensor field-of-view limitations

An object-classification system for an automated vehicle includes an object-detector and a controller. The object-detector may be a camera, radar, lidar or any combination thereof. The object-detector detects an object proximate to a host-vehicle. The controller is in communication with the object-detector. The controller is configured to determine a density of the object based on a motion-characteristic of the object caused by air-movement proximate to the object, and operate the host-vehicle to avoid striking the object with the host-vehicle when the density of the object is classified as dense.

Motion-characteristic based object classification for automated vehicle

A vehicle perception sensor adjustment system includes a perception-sensor, a digital-map, and controller-circuit. The perception-sensor is configured to detect an object proximate to a host-vehicle. The perception-sensor is characterized as having a field-of-view that is adjustable. The digital-map indicates a contour of a roadway traveled by the host-vehicle. The controller-circuit in communication with the perception-sensor and the digital-map. The controller-circuit determines the field-of-view of the perception-sensor in accordance with the contour of the roadway indicated by the digital-map, and outputs a control-signal to the perception-sensor that adjusts the field-of-view of the perception-sensor.

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Pittsburgh, PA, United States of America

Wenda Xu