Denso International America, Inc.

Denso Corporation

Denso Corpora Tion

Minglei Huang

Hiroshi Inou

Yu Yan

Prasanna Sivakumar

A method includes obtaining steering data of the vehicle from one or more steering sensors, determining whether the vehicle is operating in one of a turning state and a non-turning state based on the steering data, performing a localization routine based on a first echo set of the 3D data points from among the plurality of 3D data points when the vehicle is operating in the turning state, and performing the localization routine based on a second echo set of the 3D data points from among the plurality of 3D data points when the vehicle is operating in the non-turning state, where a number of the plurality of 3D data points of the first echo set is greater than a number of the plurality of 3D data points of the second echo set.

Systems and methods for controlling a vehicle localization routine

A system for measuring accuracy of an electronic map or a localization of a vehicle may include one or more processors and a memory in communication with the one or more processors having an image capture module, a ground truth generating module, a curve function generating module, and an accuracy determining module. These modules contain instructions that when executed by the one or more processors causes the processors to obtain sensor data that includes images of one or more road lane markings of a road or trajectory data regarding the trajectory of the vehicle, determine ground truth curvature values, perform a curve fitting of map lane marking points or map trajectory points, and compare curvature values of a curve function generated by the curve fitting to the ground truth curvature values to determine the accuracy the electronic map or the localization of the vehicle.

System and method for measuring the accuracy of an electronic map or a localization of a vehicle

The present disclosure is directed toward a lane detection method. The method includes: acquiring road information for a section of a road upon which a subject vehicle is traveling, determining whether an adjacent vehicle is traveling in vicinity of the subject vehicle, defining, in response to determining the presence of the adjacent vehicle, a vehicle trajectory based on movement of the adjacent vehicle and the road information, detecting one or more lane markings along the road upon which the subject vehicle is traveling, defining a lane marking trajectory in response to detecting the one or more lane markings, calculating a lane accuracy for each estimated lane trajectory that includes the vehicle trajectory, the lane marking trajectory, or a combination thereof, and selecting a drive lane from among the estimated lane trajectories based on the lane accuracy.

Lane detection method and system for a vehicle

A lane trace control system for maintaining a vehicle in its intended lane of travel. The system includes a lane trace control module configured to: compare the road information obtained by a lane recognition camera with map data obtained from a map module; determine a confidence level of the lane recognition camera based on a magnitude of any differences identified between the road information obtained from the lane recognition camera and the obtained map data; generate a target wheel angle for keeping the vehicle in its intended lane based entirely on the road information obtained from the lane recognition camera when the confidence level is above a predetermined threshold; and generate the target wheel angle based on a combination of the road information obtained from the lane recognition camera and the obtained map data of the road when the confidence level is below the predetermined threshold.

Vehicle lane trace control system

An autonomous drive system for a vehicle. The system has an autonomous drive module configured to pilot the vehicle. A control module monitors operating performance of the autonomous drive system. A location module identifies the vehicle's location. A transmitter/receiver communicates with a high risk location monitoring module at a location remote to the vehicle. When the control module determines that performance of the autonomous drive system is below a predetermined performance threshold, the control module retrieves the vehicle's location from the location module and transmits the vehicle's location to the high risk location monitoring module, which records the vehicle's current location to notify other vehicles that autonomous drive issues may occur at the vehicle's location.

Autonomous drive system

A method for generating images of traffic objects using deep learning is disclosed. The method includes obtaining image data from an image. The method includes assigning a set of default parameters to the image data, and the set of default parameters include values associated with at least one of a weather condition of the image and a defect condition of an object of the image. The method includes generating a set of predicted parameters based on the image data. The method includes determining an error for each parameter of the set of predicted parameters, and the error is based on a value of the parameter of the set of predicted parameters and a value of a corresponding default parameter of the set of default parameters. The method includes adjusting a weight of a corresponding connection of the deep learning module.

Synthetic traffic object generator

A driver visibility detection system for a vehicle includes an indicator, an eye position obtainer, and a visible range calculator. The indicator indicates the driver to look at, through a windshield of the vehicle, a furthest ground position of a road on which the vehicle is traveling. The eye position obtainer recognizes an eye position of the driver when the driver looks at the furthest ground position. The visible range calculator calculates a visible range of the driver based on the eye position detected by the eye position obtainer.

Driver visibility detection system and method for detecting driver visibility

A system and method are provided and include a light source projector mounted on a subject vehicle, a controller that controls the light source projector to project a bounding box on a roadway upon which the subject vehicle is traveling in a destination lane of a lane change of the subject vehicle; and a sensor that detects a response image projected by a secondary vehicle on the roadway in the adjacent lane, the response image indicating either agreement or disagreement with the lane change of the subject vehicle. The controller generates an alert in the subject vehicle based on the detected response.

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Farmington, MI, United States of America

Minglei Huang