Veoneer Us, Inc.

Autoliv Asp, Incorporated

Shan Cong

Ramesh Veerabhadra Pantulu Baladandayu Thapani

Debra Rice

Kapil Gupta

Junru Di

Joe Attard

Bei Yan

Juan Roca

Malakeh Sivako

Cross traffic alert system for a host vehicle engaged in a forward or reverse gear position, includes an object detection sensor configured to detect relative positions of a plurality of target objects present in a coverage zone proximate the vehicle, and a processor for receiving the target positional data, detecting established environmental states based on the received data, and classifying a driving environment (e.g., road, parking lot, etc.) based on the detection or not of established environmental states. Threshold alert areas are dynamically adjustable in the coverage zones based on the classified driving environment, where indications of targets in the alert areas may be generated.

Traffic environment adaptive thresholds

Systems and methods for lane change prediction, detection, and/or confirmation. In some embodiments, a vehicle yaw rate associated with a vehicle may be detected and a set of vehicle yaw rate data may be generated. A steering angle associated with the vehicle may also be detected and a set of vehicle steering angle data generated. A first filter model may be used to process the vehicle yaw rate data. The vehicle steering angle data may be used to confirm a suspected lane change. A parameter threshold may be applied to the processed vehicle yaw rate data and, upon exceeding the parameter threshold and upon confirmation of the suspected lane change from the vehicle steering angle date, a parameter of a lane change assist system of the vehicle may be adjusted.

Vehicle lane change assist improvements

Methods and systems for detecting lane changes using vehicle path data. In some implementations, one or more environmental sensors, such as RADAR modules, may be used to generate a first data set associated with a trajectory of a host vehicle. The first data set may be representative of a curve on a graph. Points of inflection may be sought in the curve. An identification of a point of inflection in the curve may then be used to confirm a lane change of the host vehicle.

Systems and methods for vehicle lane change detection

A system and method for determining when a trailer is located behind a vehicle includes at least one detection device configured to detect objects located behind the vehicle and a processor. The processor is in communication with the at least one detection device and a plurality of signals generated by the vehicle. The processor receives data from the at least one detection device. The data includes a plurality of targets detected by the at least one detection device. Next, the processor determines if one or more clusters exists and clusters the targets into at least one cluster to form cluster features when one or more clusters exist. The processor determines vehicle state based on the vehicle dynamic features from the plurality of signals generated by the vehicle as well as global features from data from the at least one detection device and determines when the trailer is located behind the vehicle based on the cluster features, the vehicle state, and/or the global features.

System and method for automatic trailer detection

Systems and methods are presented herein for improved cross-path detection between a host vehicle and a target object. In general, the cross-path angle by solving a multiple hypothesis problem characterized by independent calculations across a first plurality of time points, the multiple hypothesis problem supposing a plurality of possible cross-path angle solutions, each cross-path angle solution representing a corresponding possible trajectory for the target object. Advantageously, a cross-traffic alert or other feedback may be triggered based at least partially on whether the target object is within a region of interest, wherein the region of interest is determined at least in part based on the estimated cross-path angle. In some embodiments the cross-path angle may be determined by selecting a cross-path angle solution from the plurality of possible cross-path angle solutions which minimizes a variance between results of the independent calculations across the first plurality of time points. Other feature disclosed herein include, determining an estimate for the cross-path angle for each of a plurality of trackings of the target object, wherein each tracking is characterized by a different set of two or more time points. This may advantageously enable, determining a change in trajectory of the target object based on variance between cross-path angle estimates.

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Superior Township, MI, United States of America

Shan Cong