Systems and methods are provided for navigating a host vehicle. In an embodiment, a processing device may be configured to receive images captured over a time period; analyze images to identify a target vehicle; receive map information associated including a plurality of target trajectories; determine, based on analysis of the images, first and second estimated positions of the target vehicle within the time period; determine, based on the first and second estimated positions, a trajectory of the target vehicle over the time period; compare the determined trajectory to the plurality of target trajectories to identify a target trajectory traversed by the target vehicle; determine, based on the identified target trajectory, a position of the target vehicle; and determine a navigational action for the host vehicle based on the determined position.

Implementations for an intelligent road barrier (IRB) system can include a plurality of road barriers located along a roadway, and a plurality of IRB kits, each IRB kit being including a set of sensors configured to obtain sensor data representative of at least a portion of a road state of the roadway proximate to the respective road barrier, a data processing unit configured to process at least a portion of the sensor data, a communication unit configured to send at least a portion of the sensor data and to receive sensor data from the one or more other IRB kits, and a state conveyance system configured to convey at least a portion of road state data to one or more vehicles associated with the roadway, the at least a portion of road state data being determined based on the at least a portion of the sensor data.

Methods and devices for using a relationship between activities of different traffic signals in a network to improve traffic signal state estimation are disclosed. An example method includes determining that a vehicle is approaching an upcoming traffic signal. The method may further include determining a state of one or more traffic signals other than the upcoming traffic signal. Additionally, the method may also include determining an estimate of a state of the upcoming traffic signal based on a relationship between the state of the one or more traffic signals other than the upcoming traffic signal and the state of the upcoming traffic signal.

Provided herein is a system and method of a vehicle. The system comprises one or more sensors, processors, maps, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: monitoring a location of the vehicle while driving; detecting a sign while the vehicle is driving; capturing, frame-by-frame, data of the sign until the sign disappears from a field of view of the sensor; synchronizing each frame of the data with the location of the vehicle; determining a location of the sign based on the frame-by-frame data; in response to determining, at a frame immediately before the sign disappears from the field of view of the sensor, that the vehicle is driving towards the sign, uploading the detected sign and the location of the sign onto the one or more maps; and implementing a driving action based on the sign.

Techniques for determining a location and type of traffic-related features and using such features in route planning are discussed herein. The techniques may include determining that sensor data represents a feature such as a traffic light, road segment, building type, and the like. The techniques further include determining a cost of a feature, whereby the cost is associated with the effect of a feature on a vehicle traversing an environment. A feature database can be updated based on features in the environment. A cost of the feature can be used to update costs of routes associated with the location of the feature.

This application relates to the automated driving field, and discloses a method for identifying abnormal driving behavior, a system, and a vehicle including the system. The method for identifying abnormal driving behavior includes: obtaining vehicle driving behavior data, and determining, based on the vehicle driving behavior data, whether a vehicle is in a state of suspicious abnormal driving behavior; obtaining current vehicle driving scenario data if the vehicle is in the state of suspicious abnormal driving behavior; and determining, based on the vehicle driving behavior data and the current vehicle driving scenario data, whether the suspicious abnormal driving behavior is abnormal driving behavior. In the technical solutions of this application, current driving scenario information is introduced to an identification process of abnormal driving behavior of the vehicle, so that accuracy of identifying the abnormal driving behavior is improved.

A method for managing an urgency state of a first vehicle, implemented by a managing system. The method includes: receiving a first indication of the urgency state of the first vehicle; determining a list of potential itineraries including at least one potential itinerary of the first vehicle; and sending an alert message to at least one detecting element, located at a traffic lane, the at least one detecting element being determined as a function of the at least one potential itinerary of the first vehicle.

An information processing device includes a communication unit and a control unit. The control unit selects at least one instant message as a selected message from one or more instant messages transmitted and received between terminal devices including a first terminal device. The control unit selects the selected message based on at least one of pick-up time and drop-off time of a vehicle picking up and dropping off a first user of the first terminal device. The control unit determines evaluation of a service provided in the vehicle based on the selected message.

The present invention relates to a method of cooperatively coordinating future driving maneuvers of a vehicle with fellow maneuvers of at least one fellow vehicle, wherein trajectories for the vehicle are rated with an effort value each, trajectories and fellow trajectories of the fellow vehicle are combined into tuples, the trajectory and the associated effort value of a collision-free tuple are selected as reference trajectory and reference effort value, trajectories with a lower effort value than the reference effort value are classified as demand trajectories, trajectories with higher effort value than the reference effort value are classified as alternative trajectories, and a data packet having a trajectory set consisting of the reference trajectory and the associated reference effort value as well as at least one trajectory from a group comprising the demand trajectories and the alternative trajectories as well as the respective effort values is transmitted to the fellow vehicle.

Techniques for encoding image data are discussed. Image data containing multiple image frames can be received from an image sensor associated with a vehicle. A first image frame and a second image frame may be associated with a first data chunk. A first metadata associated with the first image frame can be identified. Additionally, a second metadata associated with the second image frame can be identified. The first data chunk can be created that includes the first image frame, the second image frame, the first metadata, and the second metadata. The first data chunk can be stored in a video container, where the video container can be indexed to access the first image frame with the first metadata or the second image frame with the second metadata.