Abstract: 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.

Abstract: An object classification system for an automated vehicle includes a lidar and/or a camera, and a controller. The controller determines a lidar-outline and/or a camera-outline of an object. Using the lidar, the controller determines a transparency-characteristic of the object based on instances of spot-distances from within the lidar-outline of the object that correspond to a backdrop-distance. Using the camera, the controller determines a transparency-characteristic of the object based on instances of pixel-color within the camera-outline that correspond to a backdrop-color. The transparency-characteristic may also be determined based on a combination of information from the lidar and the camera. The controller operates the host-vehicle to avoid the object when the transparency-characteristic is less than a transparency-threshold.

Abstract: 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.

Abstract: A driving-rule system (10) suitable to operate an automated includes a vehicle-detector (16) and a controller (20). The vehicle-detector (16) is suitable for use on a host-vehicle (12). The vehicle-detector (16) is used to detect movement of an other-vehicle (14) proximate to the host-vehicle (12). The controller (20) is in communication with the vehicle-detector (16). The controller (20) is configured to operate the host-vehicle (12) in accordance with a driving-rule (22), detect an observed-deviation (24) of the driving-rule (22) by the other-vehicle (14), and modify the driving-rule (22) based on the observed-deviation (24).

Abstract: 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.

Abstract: 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.

Abstract: A tracking system for semi-autonomous or autonomous operation of a host vehicle is configured to detect and monitor an object. The tracking system includes an object detection device and a controller. The object detection device is mounted to the host vehicle, and is configured to detect and monitor the object, output a first detection signal indicative of the object being detected, and output a second detection signal indicative of the object not being detected. The controller is configured to receive and associate the first detection signal to a terrain slope in a common moment in time, and receive and associate the second detection signal to a change in terrain slope in a succeeding moment in time. The controller outputs a command signal causing the host vehicle to slow down upon receipt of the second signal and the change in terrain slope, both occurring in the succeeding moment in time.

Abstract: A sensor failure compensation system for an automated vehicle includes a forward sensor, at least one side sensor, and a controller. The forward sensor is configured to monitor a forward scene and output a forward signal. The side sensor is configured to monitor a side scene and output a side signal associated with the side scene. The controller is configured to receive and process the forward signal to selectively establish a forward task in association with the forward scene, and receive and process the side signal to selectively establish a side task in association with the side scene. The controller selects the side task if the forward sensor is not functional, or selects the forward task if the side sensor is not functional.

Abstract: A sensor failure compensation system for an automated vehicle includes first and second sensors, and a controller. The first sensor is configured to monitor a first condition and output a first signal associated with the first condition. The second sensor is configured to monitor a second condition and output a second signal associated with the second condition. The controller is configured to receive and process the first signal to establish a first reaction relative to the first condition and toward reaching a goal, receive and process the second signal to establish a second reaction relative to the second condition and toward reaching the goal, and establish a third reaction relative to the second condition and toward reaching the goal if the first sensor is malfunctioning.

Abstract: A scenario aware perception system (10) suitable for use on an automated vehicle includes a traffic-scenario detector (14), an object-detection device (24), and a controller (32). The traffic-scenario detector (14) is used to detect a present-scenario (16) experienced by a host-vehicle (12). The object-detection device (24) is used to detect an object (26) proximate to the host-vehicle (12). The controller (32) is in communication with the traffic-scenario detector (14) and the object-detection device (24). The controller (32) configured to determine a preferred-algorithm (36) used to identify the object (26). The preferred-algorithm (36) is determined based on the present-scenario (16).

Abstract: 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.

Abstract: 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.

Abstract: A system for semi-autonomous, or autonomous, operation of a host vehicle includes an object detector and a controller. The object detector is configured to detect an object proximate to a lane boundary and output an object signal. The controller is configured to process the object signal and direct the host vehicle away from the lane boundary upon detection of the object.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A data-fusion system that fuses lidar-data and camera-data for an automated vehicle includes a camera, a lidar, and a controller. The camera renders an image of an object proximate to a host-vehicle. The lidar detects a distance and a direction to the object based on a reflected-signal of light reflected by the object. The controller is in communication with the camera and the lidar. The controller is configured to determine a reflectivity-characteristic of the object based on the image and the reflected-signal, and adjust a detection-characteristic of the lidar when the reflectivity-characteristic of the object makes it difficult for the lidar to detect the distance and the direction to the object.

Abstract: 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.

Abstract: 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.

Abstract: An open-loop brake control system for an automated vehicle includes a brake-unit and a controller. The brake-unit varies brake-pressure to operate brakes of a host-vehicle. The controller is in communication with the brake-unit. The controller operates the brake-unit to an initial-pressure to initiate braking of the host-vehicle in accordance with a brake-model that characterizes vehicle-deceleration versus the initial-pressure based on a time-of-operation of the brakes.