Toyota Jidosha Kabushiki Kaisha

Denso Corporation

Hitoshi Kamada

Daisuke Hashimoto

Tetsuro Sugiura

Kenichiro Aoki

Ryusuke Kuroda

Norimasa Kobori

Taiyo Uejima

Takuya Fujiki

Tadashi Okubo

Wataru Kawashima

A brake light activation determining device has a processor configured to detect decrease in the speed of a vehicle ahead, which is located ahead of one's own vehicle, based on output information from a sensor that acquires information relating to the vehicle ahead, to discriminate whether the brake light of the vehicle ahead is activated based on an image representing the vehicle ahead, and to determine that the vehicle ahead is braking, when it has been discriminated that the brake light of the vehicle ahead has been activated, when the speed decrease timing at which reduction in the speed of the vehicle ahead has been detected and the activation timing at which brake light activation by the vehicle ahead was discriminated are synchronized for the vehicle ahead.

Brake light activation determining device, storage medium storing computer program for determining brake light activation, and method for determining brake light activation

A vehicle controller includes a processor configured to detect a vehicle ahead of a host vehicle from time-series sensor signals obtained by a sensor provided on the host vehicle for sensing objects around the host vehicle, track the vehicle ahead detected from the time-series sensor signals, determine whether the vehicle ahead has performed an avoidance action, based on the result of tracking, detect, when the vehicle ahead has performed an avoidance action, a trajectory of an edge of the vehicle ahead opposite a direction of avoidance in the avoidance action, and control travel of the host vehicle so that an edge of the host vehicle opposite the direction of avoidance moves along the detected trajectory.

Vehicle controller, method, and computer program for vehicle control

A vehicle controller includes a processor configured to: input characteristics extracted from an object region representing a target vehicle in an image obtained by a camera of a vehicle into a light-state classifier to identify a light state that is the state of a signal light of the target vehicle; determine a first control value, based on the result of identification of the light state and the positional relationship between the vehicle and the target vehicle, in accordance with a predetermined rule; input the result of identification of the light state into a control command classifier, which has been trained to output a second control value for controlling the vehicle to avoid a collision between the vehicle and the target vehicle, thereby determining the second control value; and determine an integrated control value to be used for controlling the vehicle, based on the first and second control values.

Controller, method, and computer program for controlling vehicle

A vehicle control system installed on a vehicle includes: a driver abnormality detection device configured to detect abnormality of a driver of the vehicle; a vehicle control device configured to execute vehicle stop control that stops the vehicle and abnormality notification processing that activates a notification device, when the abnormality of the driver is detected; and an information acquisition device configured to acquire driving environment information including at least one of surrounding situation information indicating a situation around the vehicle, vehicle state information indicating a state of the vehicle, and driving operation information indicating a driving operation by the driver. The vehicle control device determines, based on the driving environment information, whether to continue or terminate the abnormality notification processing after termination of the vehicle stop control.

Vehicle control system

A vehicle controller includes a processor configured to detect an object region including another vehicle near a vehicle from each of time series images obtained by a camera mounted on the vehicle; detect a predetermined action taken by the other vehicle, based on a trajectory of the other vehicle estimated from the object region of each image; identify the state of a signal light of the other vehicle, based on characteristics obtained from pixel values of the object region of each image; extract information indicating characteristics of an action of the other vehicle or the state of a signal light at the predetermined action taken by the other vehicle, based on the predetermined action detected in a tracking period and the state of the signal light related to the predetermined action; and predict behavior of the other vehicle, using the extracted information.

Growing community of inventors

Kawasaki, Japan

Hitoshi Kamada