This disclosure provides methods, devices and systems for a vehicle user equipment (VUE) to obtain extrinsic information about an object or location. The VUE may transmit a request for information about the object or the location to a road side unit (RSU). The RSU may receive the request and determine a set of extrinsic information for the first UE regarding the object or the location based on a set of information from one or more other UEs. The extrinsic information includes information that is not provided by the VUE. The RSU may transmit the set of extrinsic information to the VUE. The VUE may determine whether to accept a feature of the object or the location in the extrinsic information based on the set of extrinsic information and a set of intrinsic information detected by the VUE, The VUE may select an autonomous driving action based on the accepted feature.

One variation of a method for accessing supplemental data from other vehicles includes, at an autonomous vehicle: recording a scan image of a scene around the autonomous vehicle at a first time; detecting insufficient perception data in a region of the scan image; in response to detecting insufficient perception data in the region, defining a ground area of interest containing the region and wirelessly broadcasting a query for perception data representing objects within the ground area of interest; in response to receiving supplemental perception data—representing objects within the ground area of interest detected by the second vehicle at approximately the first time—from a second vehicle proximal the scene, incorporating the supplemental perception data into the scan image to form a composite scan image; selecting a navigational action based on objects in the scene represented by the composite scan image; and autonomously executing the navigational action.

Location technologies are combined with other information systems to provide augmented information for individuals such as a traveler in an automobile.

Location technologies are combined with other information systems to provide augmented information for individuals such as a traveler in an automobile.

Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

A vehicle may transmit, to a network entity, a lane use request message associated with a lane for the vehicle. The network entity may identify lane information associated with a lane for a vehicle. The network entity may identify vehicle information associated with the vehicle. The network entity may transmit, to the vehicle, and the vehicle may receive, from the network entity, a lane use grant message based on at least one of the identified lane information or the identified vehicle information. The lane use grant message may be indicative of a permission for the vehicle to use the lane. The vehicle may not be permitted to use the lane without the permission. The lane may correspond to a flexible direction lane, an emergency lane, a road shoulder, an HOV lane, or a passing lane.

The present invention relates to a method for alerting drivers and/or autonomous vehicles of high risk scenarios. The method includes obtaining positional data of a vehicle, where the positional data is indicative of geographical position and heading of the vehicle. The method further includes obtaining environmental data of the vehicle, where the environmental data is indicative of state of the surrounding environment of the vehicle. The method includes determining, by means of trained model, accident intensity for upcoming road portion for the vehicle, the trained model being configured to determine accident intensity associated with the upcoming road portion based on the obtained environmental data and the obtained positional data. Then, if the determined accident intensity exceeds threshold, the method comprises transmitting signal indicating approaching high risk scenario to a Human-Machine-Interface, HMI, of the vehicle and/or to a control system of the vehicle.

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, systems, and computer-readable storage media for obtaining sensor data captured by one or more sensors that generate data representative of characteristics of a roadway, determining a state of the roadway by processing the sensor data, the state at least partially comprising a first configuration of the roadway, determining, at least partially based on the state, a period of time to deploy a plurality of road barriers on the roadway, and deploying the plurality of road barriers based on the period of time to provide a second configuration comprising at least one dedicated lane.

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.