Jaywalking behaviors of vulnerable road users (VRUs) such as cyclists or pedestrians can be predicted. Location data is obtained that identifies a location of a VRU within a vicinity of a vehicle. Environmental data is obtained that describes an environment of the VRU, where the environmental data identifies a set of environmental features in the environment of the VRU. The system can determine a nominal heading of the VRU, and generate a set of predictive inputs that indicate, for each of at least a subset of the set of environmental features, a physical relationship between the VRU and the environmental feature. The physical relationship can be determined with respect to the nominal heading of the VRU and the location of the VRU. The set of predictive inputs can be processed with a heading estimation model to generate a predicted heading offset (e.g., a target heading offset) for the VRU.

This application is directed to on-vehicle behavior modeling of vehicles. A vehicle has one or more processors, memory, a plurality of sensors, and a vehicle control system. The vehicle collects training data via the plurality of sensors, and the training data include data for one or more vehicles during a collection period. The vehicle locally applies machine learning to train a vehicle driving behavior model using the collected training data. The vehicle driving behavior model is configured to predict a behavior of one or more vehicles. The vehicle subsequently collecting sensor data from the plurality of sensors and drives the vehicle by applying the vehicle driving behavior model to predict vehicle behavior based on the collected sensor data. The vehicle driving behavior model is configured to predict behavior of an ego vehicle and/or a distinct vehicle that appears near the ego vehicle.

An apparatus for warning the collision of a vehicle includes an information acquirer configured to acquire information on a surrounding object and information on a vehicle, and a controller configured to generate collision predicting information for the surrounding object, based on the information on the surrounding object and the information on the vehicle, and generate control information to control braking of the vehicle and to provide, based on the collision predicting information, a buffer element to an outside of the vehicle while controlling the braking of the vehicle.

A system and method for reducing the risk of road accidents on account of blind spot errors and a vehicle using the system and method includes a visual sensing unit, the visual sensing unit comprising a first camera and a second camera, wherein the first camera looks left and obtains a first image information, the second camera looks to the right and obtains a second image information; a pre-processing unit, the pre-processing unit being coupled with the visual sensing unit, wherein the pre-processing unit processes the first image information and the second image information to generate a single image. An image processing unit generates an obstacle recognition information according to the processed image.

A device includes a target information acquisition sensor configured to detect a target present in a region rearward of a host vehicle, and acquire information about the target as target information; and an electronic control unit configured to, while the host vehicle is stopped, calculate, based on the target information, a predicted time required for the target to come into contact with or close proximity to the host vehicle, and execute drop-off assist control for assisting drop-off of an occupant of the host vehicle when the predicted time is equal to or smaller than a predetermined time threshold, set the time threshold to a predetermined first time threshold when a speed of the target is equal to or lower than a predetermined first speed, and set the time threshold to a value smaller than the first time threshold when the speed of the target is higher than the first speed.

Embodiments described herein disclose systems and methods for a dual buffer zone system to ensure a stable nudge for autonomous driving vehicles. In one embodiment, a system perceives a driving environment surrounding an autonomous driving vehicle (ADV), including perceiving one or more obstacles within a view of the ADV. For each of the one or more obstacles, if a previous planning decision for the obstacle is not a nudge, the system associates a first buffer zone with the obstacle. Otherwise, the system associates a second buffer zone with the obstacle. Based on the associated buffer zone for the obstacle, the system determines a planning decision to nudge the obstacle to ensure a buffer distance between the ADV and the obstacle. The system generates a trajectory for the ADV based on the planning decisions for the one or more obstacles.

A system for providing an alert to an occupant of a vehicle may include one or more processors and a memory. The memory may store a free space detection module, a target detection module, a path prediction module, an activation threshold module, and an alert module. The modules include instructions that cause the one or more processors to determine one or more dimensions of a free space located adjacent to a side of the vehicle, determine one or more dimensions of one or more targets, determine one or more predicted paths of one or more targets, selectively adjust an activation threshold for providing an alert according to the one or more predicted paths, and activate the alert to inform the occupant of a hazard associated with the one or more targets according to whether the one or more predicted paths satisfies the activation threshold.

An alert control apparatus includes: an alert control unit to issue a first alert to an occupant in a moving body if an object in a particular category is present within a region to which the moving body is headed, and issue a second alert to the occupant if an object in a category other than the particular category is present within the region; a reception control unit to perform, when the moving body enters a new movement section on a movement route, control for receiving a category of an object present within the new movement section from an external apparatus. If there is an object for which an alert is to be issued during movement within the new section, the alert control unit, based on the category received from the external apparatus, controls as to which of the first and second alerts is to be issued.

An information processing device is configured to acquire first data related to a driving operation performed in a first vehicle and second data related to a surrounding condition of the first vehicle, and perform driving evaluation for the first vehicle based on the first data and the second data.

Methods of determining relevance of objects that a vehicle's perception system detects are disclosed. A system on or in communication with the vehicle will identify a time horizon, and a look-ahead lane based on a lane in which the vehicle is currently traveling. The system defines a region of interest (ROI) that includes one or more lane segments within the look-ahead lane. The system identifies a first subset that includes objects located within the ROI, but not objects not located within the ROI. The system identifies a second subset that includes objects located within the ROI that may interact with the vehicle during the time horizon, but not excludes actors that may not interact with the vehicle during the time horizon. The system classifies any object that is in the first subset, the second subset or both subsets as a priority relevant object.