To visualize planned behavior of an autonomous vehicle (AV) traveling along a roadway, a user interface engine receives data describing a planned pathway of the AV along the roadway and object data describing an object having a predicted pathway crossing the planned pathway of the AV at a cross point. The user interface engine classifies the object either an asserting object or a yielding object based on a prediction of whether the object reaches the cross point before the AV or after the AV. The user interface engine generates an image that includes the planned pathway of the AV and the object in the environment of the AV. The image of the object indicates whether the object is classified as an asserting object or a yielding object.

Provided is a vision system, vehicle including thereof, and a controlling method of the vehicle. The vision system includes a camera provided on a vehicle and having a front view of the vehicle outside, and configured to capture image data; and a controller having a processor configured to process the captured image data by the camera; and the controller may be configured to recognize an object existing in the front view based on the processed image data, determine whether the vehicle can depart based on information on the recognized object, control an output of departure availability notification or stop notification information corresponding to the determined departure availability.

The rise of the connected objects known as the “Internet of Things” (IoT) will rival past technological marvels. This application discloses an object control system (OCS) to control movement of an object in a smart environment. The object control system uses a virtualized shared database and a shared object management center to control the navigation and protection of moving and flying objects through an IoT network utilizing IoT devices. It also uses time of day to schedule activities of the moving, flying, stationary and fixed objects in the smart environment to allow all objects within object control system operate freely with no interference and collision.

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.

A method includes receiving data relating to pedestrian activity at one or more locations outside of a crosswalk, analyzing the data, based on the data, identifying at least one location of the one or more locations as a constructive crosswalk, and controlling operation of an autonomous vehicle based on the at least one location of the constructive crosswalk.

The present document provides an apparatus for assisting driving of a host vehicle that operates according to an operating condition to prevent a forward collision of a host vehicle, the apparatus comprising: a navigation system for providing location information of the host vehicle; a sensor for detecting forward of the host vehicle and the presence or absence of a pedestrian in front of the host vehicle; and a controller communicatively connected to the sensor, wherein the controller is configured to determine whether the host vehicle has entered a driving caution area based on at least one of location information of the host vehicle and forward information of the host vehicle, and mitigate an operating condition of the forward collision avoidance system if the host vehicle has entered the driving caution area and the pedestrian is present in the driving caution area.

One or more techniques and/or systems are provided for notifying drivers to assume manual vehicle control of vehicles. For example, sensor data is acquired from on-board vehicles sensors (e.g., radar, sonar, and/or camera imagery of a crosswalk) of a vehicle that is in an autonomous driving mode. In an example, the sensor data is augmented with driving condition data aggregated from vehicle sensor data of other vehicles (e.g., a cloud service collects and aggregates vehicle sensor data from vehicles within the crosswalk to identify and provide the driving condition data to the vehicle). The sensor data (e.g., augmented sensor data) is evaluated to identify a driving condition of a road segment, such as the crosswalk (e.g., pedestrians protesting within the crosswalk). Responsive to the driving condition exceeding a complexity threshold for autonomous driving decision making functionality, a driver alert to assume manual vehicle control may be provided to a driver.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The system can determine a collision avoidance path by: 1) predicting the behavior/trajectory of other moving objects (and identifying stationary objects); 2) given the driving trajectory (issued by autonomous driving system) or predicted driving trajectory (human), establishing the probability for a collision that can be calculated between the vehicle and one or more objects; and 3) finding a path to minimize the collision probability.

A vehicle configured to operate in an autonomous mode may operate a sensor to determine an environment of the vehicle. The sensor may be configured to obtain sensor data of a sensed portion of the environment. The sensed portion may be defined by a sensor parameter. Based on the environment of the vehicle, the vehicle may select at least one parameter value for the at least one sensor parameter such that the sensed portion of the environment corresponds to a region of interest. The vehicle may operate the sensor, using the selected at least one parameter value for the at least one sensor parameter, to obtain sensor data of the region of interest, and control the vehicle in the autonomous mode based on the sensor data of the region of interest.