B60W50/00

Obstacle avoidance apparatus and obstacle avoidance route generating apparatus

Provided is an obstacle avoidance apparatus that can specify a distance between a subject vehicle and an obstacle when making the subject vehicle avoid the obstacle. An obstacle avoidance apparatus includes: an obstacle movement predictor that predicts movement of the obstacle; and a constraint generator that establishes a constraint on a state quantity or a control input of the subject vehicle by determining whether to steer right or left around the obstacle and defining a no-entry zone for preventing the subject vehicle from colliding with the obstacle. The constraint generator incorporates, into the no-entry zone, an area to the left of the obstacle when determining to steer right around the obstacle, and incorporates, into the no-entry zone, an area to the right of the obstacle when determining to steer left around the obstacle.

Vehicle traveling control system and vehicle control system

A vehicle traveling control system according to the example in the present disclosure communicates with an automatic operation control system which drafts a traveling plan of the vehicle, and performs an automatic traveling control for automatically running the vehicle along the traveling plan received from the automatic operation control system. The vehicle traveling control system predicts a risk based on information about surrounding environment of the vehicle, and performs, when the risk is predicted, a risk avoidance control to intervene in the automatic traveling control in order to avoid the risk. When the risk avoidance control is executed, the vehicle traveling control system transmits information on the risk avoidance control to the automatic operation control system.

Electronic control system for vehicle, program update approval determination method and program update approval determination program

An electronic control system for vehicle includes a center device that manages a program update of a vehicle, and a vehicular master device that is communicable with the center device. The center device, responsive to a user giving approval for program update by using a device not being a possession owned by the user, receives approval information of the user, and stores and manages the approval information in association with vehicle information of the user. The center device transmits the approval information to the user's vehicle side. When the vehicular master device receives the approval information, the vehicular master device performs rewriting of the program.

Electronic control system for vehicle, program update approval determination method and program update approval determination program

An electronic control system for vehicle includes a center device that manages a program update of a vehicle, and a vehicular master device that is communicable with the center device. The center device, responsive to a user giving approval for program update by using a device not being a possession owned by the user, receives approval information of the user, and stores and manages the approval information in association with vehicle information of the user. The center device transmits the approval information to the user's vehicle side. When the vehicular master device receives the approval information, the vehicular master device performs rewriting of the program.

Autonomy first route optimization for autonomous vehicles

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

ROUTE-BASED SELECTIONS OF VEHICLE PARAMETER SETS

In some examples, a controller receives information of a route of a vehicle, and selects a first parameter set from among a plurality of parameter sets based on the route of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller causes application of the first parameter set to control a setting of the one or more adjustable elements of the vehicle.

ROUTE-BASED SELECTIONS OF VEHICLE PARAMETER SETS

In some examples, a controller receives information of a route of a vehicle, and selects a first parameter set from among a plurality of parameter sets based on the route of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller causes application of the first parameter set to control a setting of the one or more adjustable elements of the vehicle.

Dynamic Safe Storage of Vehicle Content

Systems and methods are provided for dynamically protecting transportable articles in vehicles. A system for dynamically protecting a transportable article in a vehicle may include one or more processors and non-volatile memory storing instructions. The instructions, when executed by the one or more processors, cause the system to determine at least one of a characteristic or a trait of the transportable article; detect, based on sensed data, an emergency condition; select one or more article protection components based on (i) the at least one of the characteristic or the trait of the transportable article, and (ii) the detected emergency condition; and in response to detecting the emergency condition, deploy the selected one or more article protection components to protect the transportable article.

COMPUTER-AIDED METHOD AND DEVICE FOR PREDICTING SPEEDS FOR VEHICLES ON THE BASIS OF PROBABILITY

The invention relates to a computer-aided method for generating a drive cycle for a vehicle which is suitable for simulating a driving operation, in particular a real driving operation. The computer-aided method comprises establishing a state vector of the drive cycle for a current time interval from a past speed curve, providing an acceleration prediction model, determining an acceleration value in consideration of probabilities resulting from the acceleration prediction model and the state vector, integrating the determined acceleration value over the current time interval in order to obtain a predicted speed value for a next future time interval, and appending the predicted speed value to the past speed curve in order to generate the drive cycle. Furthermore, the invention relates to a device for generating a drive cycle for a vehicle which is suitable for simulating a driving operation, in particular a real driving operation, and means for establishing a state vector of the drive cycle for a current time interval from a past speed curve, means for determining an acceleration value in consideration of probabilities resulting from the acceleration prediction model and the state vector, means for integrating the determined acceleration value over the current time interval in order to obtain a predicted speed value for a next future time interval, and means for appending the predicted speed value to the past speed curve in order to generate the drive cycle.

SYSTEMS AND METHODS FOR PREDICTING BLIND SPOT INCURSIONS
20230005374 · 2023-01-05 ·

Systems and methods are provided for predicting blind spot incursions for a host vehicle. In one implementation, a navigation system for a host vehicle may comprise a processor. The processor may be programmed to receive, from an image capture device located on a rear of the host vehicle, at least one image representative of an environment of the host vehicle. The processor may be programmed to analyze the at least one image to identify an object in the environment of the host vehicle and to determine kinematic information associated with the object. The processor may further be programmed to predict, based on the kinematic information, that the object will travel in a region outside of a field of view of the image capture device and perform a control action based on the prediction.