Disclosed is an identification system to improve safety on roads and allow for the driver or for the vehicle itself, if it is autonomous or semi-autonomous, to have readable and useful information about road signs, roadways, and adjacent roadway information. The disclosed identification system comprises a marker with marker communication information that can be read by a vehicle information system to provide information to the vehicle. Information that the marker communication information may convey would allow the vehicle information system to detect or recognize, or both detect and recognize critical road sign, roadway information, and adjacent roadway information. Then, the vehicle information system could respond to the information received from the marker communication information.

A camera system mounted on a vehicle includes a first substrate including an image sensor that generates image information by photoelectric conversion and a first communication unit, and a second substrate including a second communication unit for performing wireless communication with the first communication unit and a first information processing section at least capable of recognition processing for recognizing a situation outside the vehicle based on the image information acquired via the second communication unit.

An approach is provided for determining road work zone travel time reliability based on vehicle sensor data. The approach involves, for instance, aggregating telematic data generated by vehicles traveling within a geographic area, to detect a road work zone and/or active time period(s) thereof. The approach also involves identifying a start location and an end location of the road work zone. The approach further involves identifying a starting time point when one of the vehicles approaching the start location and an end time point when the vehicle passes the end location. The approach further involves calculating a time difference between the start and end time points as a travel time through the road work zone. The approach further involves aggregating the vehicle travel times, to compute work zone travel time reliability index(es) for the road work zone. The approach further involves providing the travel time reliability index(es) as an output.

A method of generating log data that includes a plurality of records, in which information detected through image recognition processing on a plurality of image frames is recorded. The method includes, detecting objects in each image frame through the image recognition processing, generating a record including identification information of each image frame and the aggregated number of objects detected in the image frame for each image frame, and adding metadata relating to the detected objects to the corresponding record when the aggregated number of objects is equal to or greater than one. When the aggregated number of objects is zero, the metadata related to the detected objects is not added to the record.

Systems and method are provided for controlling a vehicle. In one embodiment, a determination is made that a traffic control person and a traffic control sign are present within the environment of the vehicle based on sensor data, such as optical camera data. The position and orientation of the traffic control sign relative to the traffic control person is determined, e.g., via lidar sensor data, and the validity of the traffic control person and the traffic control sign is determined based on the position and orientation of the traffic control sign.

Systems and methods for detecting, geolocating, assessing, and/or inventorying infrastructure assets. In some embodiments, a plurality of images captured by a moving camera may be used to generate a point cloud. A plurality of points corresponding to a pavement surface may be identified from the point cloud. The plurality of points may be used to generate at least one synthetic image of the pavement surface, the at least one synthetic image having at least one selected camera pose. The at least one synthetic image may be used to assess at least one condition of the pavement surface.

A visual perception system includes a scanning camera, color sensor with color filter array (CFA), and a classifier node. The camera captures full color pixel images of a target object, e.g., a traffic light, and processes the pixel images through a narrow band pass filter (BPF), such that the narrow BPF outputs monochromatic images of the target object. The color sensor and CFA receive the monochromatic images. The color sensor has at least three color channels each corresponding to different colors of spectral data in the monochromatic images. The classifier node uses a predetermined classification decision tree to classify constituent pixels of the monochromatic images into different color bins as a corresponding color of interest. The color of interest may be used to perform a control action, e.g., via an automated driver assist system (ADAS) control unit or an indicator device.

The inventive subject matter provides devices and methods for improving driving safety using information obtained from images taken by a camera in a device. Among other things, contemplated devices and methods can produce alarms when it appear from rates of speed and acceleration/deceleration, that a vehicle will likely go through a red light, or fail to stop or sufficiently slow down at a stop sign. A significant feature of preferred devices and methods is that they are not dependent on WI-FI, cellular, satellite and radio signals, or any other external data transmission, and are not even dependent on speed, acceleration, or other information native to the vehicle.

The disclosed technology provides solutions for generating synthetic 3D environments, In some aspects, the disclosed technology includes a process of collecting sensor data corresponding with a three-dimensional (3D) space; identifying objects in the sensor data; filtering objects for inclusion in the synthetic map based on (1) a corresponding influence score for each of the one or more of the objects and (2) a corresponding duration of presence of each of the objects in the sensor data; selecting one or more of the objects based on the filtering, wherein the corresponding influence score of each of the one or more of the objects is greater than a first threshold and the corresponding duration of presence of each of the one or more of the objects is greater than a second threshold; and generating the synthetic map including a 3D rendering of the one or more of the objects selected.

A method for identifying an object in a piece of image information representing a scene in a detection range of a camera during a situation includes: a step of reading in; a step of selecting; and a step of searching. In the step of reading in, the piece of image information and at least one parameter representing the situation are read in. In the step of selecting, a feature combination of an object class of the object, which is predictably identifiable in the situation, is selected using the parameter. In the step of searching, the feature combination is searched for in the piece of image information to identify the object.