A vehicle-to-infrastructure cooperation information processing method, apparatus, device and an autonomous vehicle are provided. The method includes: acquiring first on-board perception data of a target vehicle, the first on-board perception data including data of an obstacle around the target vehicle sensed by the target vehicle; generating virtual obstacle data for representing the target vehicle according to positioning data of the target vehicle; generating second on-board perception data based on the virtual obstacle data and the first on-board perception data; and fusing the second on-board perception data with roadside perception data to obtain fusion data, the fusion data including all obstacle data in both the second on-board perception data and the roadside perception data, and the obstacle data in the roadside perception data including obstacle data for representing the target vehicle.

An information processing device that receives, from each of several vehicles, both image information captured by an image capture device installed at the vehicle, and vehicle information including position information on the vehicle; performs image processing identifying a characteristic of a dangerously-driven vehicle based on the image information; and in a case in which a dangerously-driven vehicle has been detected, modifies a priority level for image processing of the image information received from another vehicle in the vicinity of a vehicle that has detected the dangerously-driven vehicle, so as to be higher than for a vehicle not in the vicinity of the vehicle that has detected the dangerously-driven vehicle.

Disclosed are a driving guide system and method. The driving guide system includes an input unit configured to receive signal information from a signal controller, a memory in which a driving guide program using the signal information is embedded, and a processor configured to execute the program. When it is not possible to recognize a traffic light using a camera, the processor determines a driving behavior using the signal information and then performs autonomous driving according to the driving behavior or provides a notification to a driver.

A driver assistance system that notifies the driver of the braking information of the preceding vehicle or improves the sensitivity of the emergency braking system if the brake lamp of the preceding vehicle is failed includes: a first sensor mounted in a vehicle, having a front field of view of the vehicle, and configured to acquire a front image data; a second sensor selected from a group consisting of a radar sensor and a lidar sensor, mounted in the vehicle, having a front field of sensing of the vehicle, and configured to acquire a front detection data; and a controller including a processor configured to process the front image data and the front detection data, and the controller is configured to: detect a velocity of the preceding vehicle travelling in front of the vehicle and a brake lamp of the preceding vehicle in response to processing the front image data and the front detection data; and determine whether the brake lamp of the preceding vehicle is failed based on the velocity of the preceding vehicle and a lighting of the brake lamp of the preceding vehicle.

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.

An image reception unit receives an internal image from a mobile object. An accident risk prediction unit predicts a risk of occurrence of an accident inside the mobile object based on the internal image and situation information indicating a situation of the mobile object. A quality determination unit determines internal image quality information indicating quality of the internal image based on a result of the predicted risk of the inside accident. A quality adjustment unit adjusts the quality of the internal image based on the internal image quality information.

A mobile robot and a method for controlling a mobile robot are provided. The method includes: accessing a 3D map representation of an environment including a respective indication of a crosswalk, a waiting area, and a visual traffic indicator; detecting an object located in the waiting area for generating a bounding box of the object; mapping a position of the bounding box to the 3D map representation; determining a visual occlusion zone of the object in the waiting area; determining a reduced waiting area as a difference between the waiting area and the visual occlusion area, and triggering control of the propulsion system for moving the mobile robot to the reduced waiting area.

A method, apparatus, and computer-readable medium for confirming a perceived position of a traffic light, by obtaining identifiers and results of a first perception of traffic lights associated with the identifiers, the results of the first perception including a first estimation of an ellipse encompassing each of the traffic lights, receiving results of a second perception of traffic lights associated with the identifiers, the results of the second perception including a second estimation of an ellipse encompassing each of the traffic lights, calculating, based on the first perception and the second perception, association parameters for each possible pair of estimated ellipses, selecting, based on the calculated association parameters for each possible pair of estimated ellipses, matching pairs of estimated ellipses, and fusing each matching pair of estimated ellipses.

An autonomous driving system capable of detecting oncoming occluded vehicles is disclosed in low-light conditions. The system captures images which are processed and analyzed to determine bright spots in a region of interest which are related to reflections of an oncoming occluded vehicle. If an oncoming occluded vehicle is detected, the system analyzes the criticality of the situation based on a tunable threshold distance. The tunable threshold distance from the equipped vehicle (vehicle with the autonomous driving system) to the oncoming occluded vehicle. Factors for tuning the threshold distance may include curvature of the road, sharpness of the turn or occluded area, road surface conditions, speed of the equipped vehicle as well as mechanical capabilities of the equipped vehicle. If the situation is critical, the system generates a warning signal indicating a hazardous condition.

Systems and methods are provided for vehicle navigation. In one implementation, a navigation system for a host vehicle may comprise at least one processor. The processor may be programmed to receive from a first camera at least a first captured image representative of an environment of the host vehicle. The processor may be programmed to receive from a second camera at least a second captured image representative of the environment of the host vehicle. Both the first captured image and the second image includes a representation of the traffic light, and wherein the second camera is configured to operate in a primary mode where at least one operational parameter of the second camera is tuned to detect at least one feature of the traffic light. The processor may be further programmed cause at least one navigational action by the vehicle based on analysis of the representation of the traffic light.