A vehicular vision system includes a side-viewing camera mounted within an exterior rearview mirror assembly attached at a side of a vehicle equipped with the vehicular vision system. The side-viewing camera has a field of view at least sideward of the side of the equipped vehicle at which the exterior rearview mirror assembly is attached. The side-viewing camera captures an image of a scene occurring exterior of the equipped vehicle. The captured image includes an image data set representative of the exterior scene. A control includes an image processor, and the image data set is provided to the control. The control processes a reduced image data set of the image data set provided to the control to detect edges present exterior of the equipped vehicle within an area of interest of the scene occurring exterior of the equipped vehicle that is within the field of view of the side-viewing camera.

A location estimating device has a processor that is configured to calculate a first estimated location of a vehicle using positional information representing the location of a vehicle and first map data overlapping with a first section of a vehicle traveling route, to calculate a second estimated location of the vehicle using positional information and second map data that overlaps with a second section of the traveling route, the first section and the second section having an overlapping section, and to assess whether or not the precision of the second estimated location satisfies a predetermined assessment criterion when the vehicle is traveling in the overlapping section from the first section toward the second section.

An imaging apparatus that is mounted on a vehicle that runs on a road surface includes: a light source that emits illumination light which is infrared light; a solid-state imaging device that images a subject and outputs an imaging signal indicating a light exposure amount; and a computator that computes subject information regarding the subject by using the imaging signal. The solid-state imaging device includes: first pixels that image the subject by receiving reflected light that is the illumination light reflected off the subject; and second pixels that image the subject by receiving visible light. Information indicated by an imaging signal outputted from the first pixels is information regarding a slope of the road surface, and information indicated by an imaging signal outputted from the second pixels is information regarding an appearance of the road surface.

Provided are a method and apparatus for determining driving information. The apparatus generates a probability map corresponding to a target object to be detected from a driving image, extracts representative points from a candidate region of the target object detected from the driving image, extracts some of the representative points based on the probability map, calculates a confidence value for the candidate region of the target object based on the extracted some representative points, and determines driving information of the vehicle based on the confidence value.

Systems and methods for detecting trailer angle are provided. In one aspect, an in-vehicle control system includes an optical sensor configured to be mounted on a tractor so as to face a trailer coupled to the tractor, the optical sensor further configured to generate optical data indicative of an angle formed between the trailer and the tractor. The system further includes a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to receive the optical data from the optical sensor, determine at least one candidate plane representative of a surface of the trailer visible in the optical data based on the optical data, and determine an angle between the trailer and the tractor based on the at least one candidate plane.

Disclosed are a vehicle control system, a marking classifying device, and a marking classifying method. Specifically, a vehicle control system according to the present disclosure may include: a camera mounted to a vehicle so as to have a field of view inside or outside the vehicle and configured to capture image data; a communication module configured to receive GPS signals from GPS satellites; a marking classifying device configured to classify and store types of markings provided on a road based on the image data and the GPS signals; and a control device configured to detect a marking on a road on which the vehicle is travelling based on the image data, identify a type of the detected marking based on the type of marking stored in the marking classifying device, and generate and output a control signal for controlling the driving of the vehicle based on the identified type of the marking.

A method of retrieving a map is disclosed. The method includes receiving a grid data of the map comprising lane segments, wherein the grid data includes an array of grids each associated with a list including none or at least one of the lane segments intersecting the respective grid; receiving coordinates of a location; identifying a first grid including the location based on the grid data; identifying a target grid that has an associated list including at least one of the lane segments as first lane segment; and outputting the first lane segment.

There is provided an automatic correction method for an onboard camera and an onboard camera device. The automatic correction method includes the following steps: obtaining a lane image with the onboard camera and a current extrinsic parameter matrix, and identifying two lane lines in the lane image; converting the lane image into a top-view lane image, and obtaining two projected lane lines in the top-view lane image for the two lane lines; calculating a plurality of correction parameter matrices corresponding to the current extrinsic parameter matrix according to the two projected lane lines; and correcting the current extrinsic parameter matrix according to the plurality of correction parameter matrices. This can be applied in situations where the vehicle is stationary or travelling for automatic correction on the extrinsic parameter matrix of the onboard camera.

Embodiments is disclosed to detect a locked heading direction of a pedestrian and to predict a path for the pedestrian using the locked heading direction. According to one embodiment, a system perceives an environment of an autonomous driving vehicle (ADV) using one or more image capturing devices. The system detects a pedestrian in the perceived environment. The system determines a facing direction of the pedestrian relative to the ADV as one of left/right side, front, or back. If the facing direction of the pedestrian is determined to be front or back facing, the system determines a lane nearest to the pedestrian. The system projects the pedestrian onto the nearest lane to determine a lane direction at the projection. The system determines a heading direction for the pedestrian locking to the lane direction of the nearest lane based on a predetermined condition.

Systems and methods are provided for determining a road profile along a predicted path. In one implementation, a system includes at least one image capture device configured to acquire a plurality of images of an area in a vicinity of a user vehicle; a data interface; and at least one processing device configured to receive the plurality of images captured by the image capture device through the data interface; and compute a profile of a road along one or more predicted paths of the user vehicle. At least one of the one or more predicted paths is predicted based on image data.