Patent classifications
B60W2754/10
OBSTACLE DETECTION FOR TRAILER OPERATION
A trailer maneuver assistance system and method provide for alerting a vehicle operator to possible obstacles within a predicted path of trailer. The predicted path is determined based on at least one sensor system mounted to the trailer and a determination that a detected obstacle is within the predicted path.
Control apparatus and method for improving fuel efficiency in CACC system
Disclosed herein is a control apparatus and method for improving fuel efficiency in a CACC system, which can improve fuel efficiency through control of a vehicle speed so that a vehicle travels using an optimized cost in consideration of a target vehicle speed, current vehicle speed, minimum driving speed set in the vehicle, and a deceleration distance if the vehicle that uses the CACC system senses a forward vehicle and enters into a CACC active mode. The control method for improving fuel efficiency in a CACC system includes setting a target speed profile based on a target speed of the subject vehicle and an expected driving path, determining whether a target vehicle to be followed by the subject vehicle exists, and controlling the driving speed of the subject vehicle according to the set target speed profile depending on whether or not the target vehicle exists.
Enhanced travel modes for vehicles
A method for operating a fleet of vehicles may include determining a first set of parameters for operating a first vehicle as it travels to a destination, and determining a second set of parameters for operating a second vehicle. Consumption of the first set of parameters by the first vehicle may cause the first vehicle to accelerate, alter shocks and/or suspensions, and/or move into a free lane. Consumption of the second set of parameters by the second vehicle may cause the second vehicle to remain outside of a drive envelope of the first vehicle, between the first vehicle and the particular destination.
System, method and controller for graph-based path planning for a host vehicle
A method of path planning for a host vehicle includes: receiving host vehicle, environmental and obstacle information; calculating one or more projected host vehicle locations; computing a projected obstacle location for each obstacle; and determining a collision potential between each projected host vehicle location and each projected obstacle location. Until a maximum number of steps is reached, and while at least one projected host vehicle location has an associated collision potential below a collision threshold, the method further includes repeating the calculating, computing and determining steps.
COOPERATIVE ADAPTIVE CRUISE CONTROL SYSTEM BASED ON DRIVING PATTERN OF TARGET VEHICLE
A cooperative adaptive cruise control (CACC) system acquires a driving pattern of a target vehicle and variably provides an inter-vehicle distance and a responsible speed level of a subject vehicle that are followed by the CACC system based on the driving pattern. The CACC system includes a communication unit receiving vehicle information and road information of a region in which the subject vehicle travels; an information collection unit collecting driving information of a forward vehicle, vehicle information of the subject vehicle, and the road information; and a control unit controlling the inter-vehicle distance and the responsible speed level of the CACC system based on the driving pattern of the target vehicle according to generated control information.
Vehicle system for recognizing objects
A vehicle system includes an electronic control unit. The electronic control unit is configured to execute a first program, a second program, and a third program. The first program is configured to recognize an object present around a vehicle, the second program is configured to store information related to the recognized object as time-series map data, and the third program is configured to predict a future position of the object based on the stored time-series map data. The first program and the third program are configured to be (i) first, individually optimized based on first training data corresponding to output of the first program and second training data corresponding to output of the third program, and (ii) then, collectively optimized based on the second training data corresponding to the output of the third program.
AI-based vehicle collision avoidance and harm minimization
In a traffic emergency, there is no time for a human to integrate multiple sensor data streams and devise a plan for avoiding a collision. Only the electronic reflexes of a trained automatic system can provide evasive action in time. Disclosed is an artificial intelligence (AI) model trained to recognize an imminent collision based on sensor data, rapidly devise and test a large number of possible sequences of actions, some drawn from a library of previously-successful strategies and others invented by the AI model. If any sequence can avoid the collision, the AI model implements that sequence immediately. If none of the sequences can avoid the collision, the AI model calculates the harm caused by each sequence and picks the one that causes the least harm (fatalities, injuries, etc.) for implementation. AI is needed to find a possible solution in time to implement it and thereby mitigate the imminent collision.
Methods and Systems for Three Dimensional Object Detection and Localization
Example embodiments relate to techniques for three dimensional (3D) object detection and localization. A computing system may cause a radar unit to transmit radar signals and receive radar reflections relative to an environment of a vehicle. Based on the radar reflections, the computing system may determine a heading and a range for a nearby object. The computing system may also receive an image depicting a portion of the environment that includes the object from a vehicle camera and remove peripheral areas of the image to generate an image patch that focuses upon the object based on the heading and the range for the object. The image patch and the heading and the range for the object can be provided as inputs into a neural network that provides output parameters corresponding to the object, which can be used to control the vehicle.
SYSTEMS AND METHODS FOR HAZARD MITIGATION
A system and method to avoid collisions on highways, and to minimize the fatalities, injury, and damage when a collision is unavoidable. The system includes sensor means to detect other vehicles, and computing means to evaluate when a collision is imminent and to determine whether the collision is avoidable. If the collision is avoidable by a sequence of controlled accelerations and decelerations and steering, the system implements that sequence of actions automatically. If the collision is unavoidable, a different sequence is implemented to minimize the overall harm of the unavoidable collision. The system further includes indirect mitigation steps such as flashing the brake lights automatically. An optional post-collision strategy is implemented to prevent secondary collisions, particularly if the driver is incapacitated. Adjustment means enable the driver to set the type and timing of automatic interventions.
Cooperative adaptive cruise control system based on driving pattern of target vehicle
A cooperative adaptive cruise control (CACC) system acquires a driving pattern of a target vehicle and variably provides an inter-vehicle distance and a responsible speed level of a subject vehicle that are followed by the CACC system based on the driving pattern. The CACC system includes a communication unit receiving vehicle information and road information of a region in which the subject vehicle travels; an information collection unit collecting driving information of a forward vehicle, vehicle information of the subject vehicle, and the road information; and a control unit controlling the inter-vehicle distance and the responsible speed level of the CACC system based on the driving pattern of the target vehicle according to generated control information.