The present application provides an object tracking method. The object tracking method includes obtaining an image of an area in front of a vehicle; dividing the image of the area in the front of the vehicle into a plurality of sub-images; determining a plurality of first sub-images that satisfy a plurality of threshold conditions out of the plurality of sub-images; selecting a plurality of target sub-images out of the plurality of first sub-images, at least one of the plurality of first sub-images is not selected as one of the plurality of target sub-images; and recognizing a target object in one of the plurality of target sub-images.

A vehicle, system and a method of operating the vehicle is disclosed. The system includes a first sensor, a second sensor and a processor. The first sensor captures an image of a traffic control device. The second sensor identifies a lane within a road that is occupied by the vehicle. The processor is configured to determine an attribute of the lane occupied by the vehicle, associate a semantic meaning to a motion control signal of the traffic control device, determine a maneuver for the vehicle based on the semantic meaning of the motion control signal and the attribute of the lane occupied by the vehicle, and perform the maneuver at the vehicle.

A device may receive accelerometer data and video data for a vehicle and may identify bounding boxes and object classes for objects near the vehicle. The device may identify tracks for the objects and may filter out tracks that are not associated with vehicles or vulnerable road users to generate one or more tracks or an indication of no tracks. The device may generate a collision cone identifying a drivable area of the vehicle to identify objects more likely to be involved in a collision and may filter out tracks from the one or more tracks, based on the bounding boxes, and to generate a subset of tracks or another indication of no tracks. The device may determine scores for the subset of tracks and may identify a track of the subset of tracks with a highest score. The device may perform actions based on the identified track.

A driving assistance apparatus comprises an image recognition unit configured to acquire an image of a traffic signal for an oncoming traffic lane from a rearward image capturing apparatus for capturing an image rearward of a vehicle, and in a case in which the vehicle is in a waiting state for turning across oncoming traffic at an intersection, to recognize a display state of the traffic signal for the oncoming traffic lane based on an image of the traffic signal for the oncoming traffic lane; a determination unit configured to determine, based on at least the display state of the traffic signal for the oncoming traffic lane that is recognized in the waiting state, whether or not a turning operation across the oncoming traffic lane is possible; and an information presentation unit configured to present information corresponding to the result of the determination to the driver.

An active sensor for performing active measurements of a scene is presented. The active sensor includes at least one transmitter configured to emit light pulses toward at least one target object in the scene, wherein the at least one target object is recognized in an image acquired by a passive sensor; at least one receiver configured to detect light pulses reflected from the at least one target object; a controller configured to control an energy level, a direction, and a timing of each light pulse emitted by the transmitter, wherein the controller is further configured to control at least the direction for detecting each of the reflected light pulses; and a distance measurement circuit configured to measure a distance to each of the at least one target object based on the emitted light pulses and the detected light pulses.

Provided are a method, an apparatus, and a computer program for extracting signal information through image data analysis including a traffic light. The method of extracting, by a computing apparatus, signal information through image data analysis including a traffic light according to various embodiments of the present disclosure includes collecting image data obtained by capturing an image in front of a vehicle, identifying a traffic light by analyzing the collected image data, and extracting signal information from the identified traffic light.

This document describes methods to assign a collective state to a group of traffic signal devices that are concurrently detected by multiple cameras. The states may be color states or other states. The system will process the images to identify states of each of the devices in the images. When the devices exhibit more than one state, the system will determine an overall state for the group by generating a confidence score for each of the states. The system will select, from the multiple states, the state having a confidence score that exceeds a threshold. The system will then use the selected state to assign an overall state to the group of traffic signal devices. The system may use the overall state to generate a signal that will cause the vehicle to perform an action such as a motion control action, or output of an audible or visual alert.

Techniques for collecting, synchronizing, and displaying various types of data relating to a road segment enable, via one or more local or remote processors, servers, transceivers, and/or sensors, (i) enhanced and contextualized analysis of vehicle events by way of synchronizing different data types, relating to a monitored road segment, collected via various different types of data sources; (ii) enhanced and contextualized analysis of filed insurance claims pertaining to a vehicle incident at a road segment; (iii) advantageous machine learning techniques for predicting a level of risk assumed for a given vehicle event or a given road segment; (iv) techniques for accounting for region-specific driver profiles when controlling autonomous vehicles; and/or (v) improved techniques for providing a GUI to display collected data in a meaningful and contextualized manner.

A vehicle configured to operate in an autonomous mode can obtain sensor data from one or more sensors observing one or more aspects of an environment of the vehicle. At least one aspect of the environment of the vehicle that is not observed by the one or more sensors could be inferred based on the sensor data. The vehicle could be controlled in the autonomous mode based on the at least one inferred aspect of the environment of the vehicle.

A method for ascertaining which one of at least two traffic light systems located in the area in front of a motor vehicle is to be observed by this motor vehicle. The ascertainment is performed by evaluating the driving behavior of a vehicle traveling in front as a function of the current light status of the traffic light systems.