Delco Electronics Corporation

Aptiv Technologies Limited

Delphi Technologies, Inc.

Aptiv Technologies Ag

Walter Kirk Kosiak

Guoguang Zhang

Mark C Hansen

Ehsan Samiei

Kevin J Hawes

Robert J Cashler

Mohamed A Moawad

Douglas R Schnabel

Jack D Parrish

Jonathan D Mann

Paul R Rowlands, Iii

Morgan Daniel Murphy

Gregory J Manlove

Mark Russell Keyse

Charles A Cluff

Matthew R Smith

Tanto Sugiarto

Kai Zhang

Michael I Chia

Junqiang Shen

Jiyao Liu

Richard Joseph Ravas

Thomas D Cook

Russell L Simpson

Michael L Whitehorn

Roger D Allison

Evasive steering assist (ESA) systems and methods for a vehicle utilize a set of vehicle perception systems configured to detect an object in a path of the vehicle, a driver interface configured to receive steering input from a driver of the vehicle via a steering system of the vehicle, a set of steering sensors configured to measure a set of steering parameters, and a controller configured to determine a set of driver-specific threshold values for the set of steering parameters, compare the measured set of steering parameters and the set of driver-specific threshold values to determine whether to engage/enable an ESA feature of the vehicle, and in response to engaging/enabling the ESA feature of the vehicle, command the steering system to assist the driver in avoiding a collision with the detected object.

Self-learning-based interpretation of driver's intent for evasive steering

A method of providing evasive steering assist (ESA) includes storing yaw rate data related to a host vehicle, wherein yaw rate data includes a yaw rate stored at each time step from an initial time step [0] to a current time step [n]. The method further includes determining whether to initiate ESA, wherein in response to a determination to initiate ESA, the method includes calculating a current position, a current heading angle, a destination position, and a destination heading angle, wherein the stored yaw rate data is utilized to determine the current heading angle and the destination heading angle. The method further includes generating an evasive steering assist (ESA) output based on the current position, the current heading angle, the destination position, and the destination heading angle.

System and method of providing evasive steering assist

A windshield-wiper system includes a precipitation-detector, a windshield-wiper actuator, an object-detector, and a controller. The precipitation-detector detects precipitation proximate to a host-vehicle. The windshield-wiper actuator clears the precipitation from a windshield of the host-vehicle. The object-detector detects a distance of an object to the host-vehicle. The controller is in communication with the precipitation-detector, the windshield-wiper actuator, and the object-detector. The controller determines when the precipitation is present based on the precipitation-detector, determines the distance from the object to the host-vehicle based on the object-detector, and adjusts a speed of the windshield-wiper actuator when the precipitation is detected and the object is less than a distance-threshold away from the host-vehicle.

Predictive windshield wiper system

This document describes change detection criteria for updating sensor-based maps. Based on an indication that a registered object is detected near a vehicle, a processor determines differences between features of the registered object and features of a sensor-based reference map. A machine-learned model is trained using self-supervised learning to identify change detections from inputs. This model is executed to determine whether the differences satisfy change detection criteria for updating the sensor-based reference map. If the change detection criteria is satisfied, the processor causes the sensor-based reference map to be updated to reduce the differences, which enables the vehicle to safely operate in an autonomous mode using the updated reference map for navigating the vehicle in proximity to the coordinate location of the registered object. The map can be updated contemporaneously as changes occur in the environment and without hindering performance, thereby enabling real-time awareness to support controls and to improve driving-safety.

Change detection criteria for updating sensor-based reference maps

Techniques and systems are described that enable evasive steering assist (ESA) with a pre-active phase. An ESA system predicts that a collision with an object is imminent and enters a pre-active phase. The pre-active phase causes a required drop in steering force to occur prior to determining that the collision is imminent. At a later time, the ESA system determines that the collision is imminent and enacts an active phase. The active phase causes a steering force effective to avoid the collision. By enacting the pre-active phase prior to the determination of the imminent collision, the ESA system may provide the additional steering force needed to avoid the collision without delay while simultaneously shielding a driver of vehicle from feeling the drop in steering force.

Evasive steering assist with a pre-active phase

A camera adjustment system includes a camera, an actuator, an inertial-measurement-unit, and one or more controller-circuits. The camera renders an image of lane-markings of a roadway traveled by a host-vehicle. The actuator is operable for controlling an aim-direction of the camera. The inertial-measurement-unit detects relative-movement of the host-vehicle. The one or more controller-circuits are in communication with the camera, the actuator, and the inertial-measurement-unit. The one or more controller-circuits determine whether a range-of-detection of the lane-markings in the image is less than a detection-threshold and adjust the aim-direction based on the relative-movement.

Camera adjustment system

A lane keeping system for a vehicle includes a first roll angle sensor configured to provide a first signal indicative of dynamic vehicle body roll. A second roll angle sensor is configured to provide a second signal indicative of an angle between vehicle sprung and unsprung masses. A lane keeping system (LKS) controller is in communication with the first and second roll angle sensors. The LKS controller is configured to discern a vehicle roll angle in response to the first and second signals based upon effects of a lateral wind force on the vehicle. The LKS controller is configured to produce a correction in response to the determined lateral wind force effects to maintain the vehicle along a desired path.

Lane keeping system for autonomous vehicle in wind conditions using vehicle roll

A cross-traffic detection system suitable for use on an automated vehicle includes an object-detector and a controller. The object-detector is used to determine locations of a moving-object relative to a host-vehicle. Each of the locations is indicated by a lateral-distance and a longitudinal-distance of the moving-object from the host-vehicle. The controller is in communication with the object-detector. The controller is configured to accumulate a plurality of first-longitudinal-distances of a first-vehicle at a plurality of predetermined-lateral-distances, and determine a path-history of the first-vehicle based on linear-interpolation between successive instances of the plurality of first-longitudinal-distances at corresponding instances of the plurality of predetermined-lateral-distances. The controller is also configured to determine that a second-vehicle is following the path-history of the first-vehicle when the second-vehicle passes within an offset-distance to the path-history that is less than an offset-threshold, and estimate a crossing-distance from the host-vehicle based on the path-history and the offset-distance.

Automated vehicle cross-traffic detection system

A radar object detection system includes a radar sensor and a controller. The radar sensor is configured to emit a radar signal toward a defined area proximate to the vehicle, and output a reflection signal indicative of a detected target present in the defined area. The controller is configured to receive the reflection signal from the radar sensor, determine if the detected target corresponds to a trailer towed by the vehicle, and define an exclusion zone characterized as occupied by the trailer and thereby excluded from the defined area where objects can be detected.

Vehicle radar system with trailer detection

A switch-based sensor apparatus is disposed between the bottom cushion and frame of a seat. The sensor apparatus includes upper and lower rigid and generally parallel force translation plates biased apart by a set of springs, and a switch assembly. The force translation plates are joined so as to pre-load the springs while permitting closing movement between the upper and lower force translation plates in response to occupant seat force that exceeds the pre-load force of the springs. The switch assembly includes a circuit board and elastomeric switch pad defining one or more switch elements that are actuated by a prescribed closing movement between the upper and lower force translation plates for electrically detecting the presence of a seat occupant.

Switch-based seat sensor for occupant presence detection

A supplemental restraint deployment method utilizes measured vehicle speed and acceleration and the output of a closing velocity sensor that detects the presence and closing rate of an approaching object prior to contact with the vehicle. The closing velocity and vehicle speed are utilized for classification of an impending crash event, where the deployment options vary depending on the crash classification. In the ensuing crash event, a classification-dependent algorithm is executed to determine if, when and what level of restraint deployment is warranted based on measures of actual crash severity. Additionally, the algorithm is reset when the calculated change in vehicle velocity reaches the initial closing velocity.

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Kokomo, IN, United States of America

Walter Kirk Kosiak