Systems and methods are disclosed for monitoring or affecting movement of a vehicle using a traffic device. An event data source may have a processor and/or a transceiver. The event data source may transmit, via the transceiver and to a vehicle and infrastructure computing device, information indicative of an event affecting a portion of road. The vehicle and infrastructure computing device may comprise a vehicle and infrastructure control computer. The vehicle and infrastructure computing device may receive, from the event data source, the information indicative of the event affecting the portion of road. The computing device may determine one or more traffic devices associated with the portion of road and configured to control traffic for the portion of road. Based on the information indicative of the event affecting the portion of road, the computing device may send, to the one or more traffic devices associated with the portion of road, instructions to change one or more characteristics of the one or more traffic devices.

Current data for a geographic area is accessed. The current data comprises at least one of (a) current traffic data for the geographic area, (b) current incident data for the geographic area, or (c) current weather data for the geographic area. Based on the current data, autonomous driving instructions are determined for the geographic area. A notification comprising the autonomous driving instructions is provided such that the notification is received by a vehicle apparatus located within the geographic area or expected to enter the geographic area based on a route being traversed by a vehicle corresponding to the vehicle apparatus. The vehicle apparatus is onboard the vehicle and is configured to control the vehicle in accordance with the autonomous driving instructions.

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.

The present disclosure is directed to dynamically analyzing data and conditions associated with the movement of a vehicle. A processor may evaluate vehicle location and speed information when identifying an amount of navigation data to send to a computer at a vehicle. The amount of information sent to the computer may vary based on the vehicle speed, a type of road that the vehicle is able to drive along, or may vary based on other attributes. The information sent to the computer may also relate to an area that the vehicle is anticipated to move through in a given time frame. Mapping data sent to the vehicle computer may be associated with a larger area when a vehicle is moving at a faster speed and may be associated with a smaller area when the vehicle is moving at a slower speed.

A vehicle control device includes a communication unit configured to be communicable with an autonomous driving vehicle that autonomously travels, a determination unit configured to determine whether there is a possibility that communication between the autonomous driving vehicle and the vehicle control device is disconnected, based on information indicating a communication status between the autonomous driving vehicle and the vehicle control device, and a travel instruction unit configured to transmit, when there is the possibility that the communication between the autonomous driving vehicle and the vehicle control device is disconnected, a travel instruction to the autonomous driving vehicle via the communication unit before the communication between the autonomous driving vehicle and the vehicle control device is disconnected. The travel instruction matches conditions associated with travel control of the autonomous driving vehicle.

A system including a processor and memory may provide for automatically activating or deactivating a feature of a fleet vehicle. For example, one or more fleet vehicles may include one or more of a global-positioning system, a speed governor, electronically-controlled brakes, an electronically-controlled accelerator, a speed limiter, or an on-board computer with a processor and memory. One or more features may be activated by a local or remote computing device or system. For example, a system may determine one or more recommended routes between two or more locations. The system may track a fleet vehicle's progress along a route, and activate a feature of the fleet vehicle based on the fleet vehicle following or not following the recommended route. For example, the system may cause activation of a speed limiter on the fleet vehicle, disable the fleet vehicle, and/or activate or deactivate autonomous features of the fleet vehicle.

A device can receive, from a client device, information identifying a location of the client device and determine at least one of an expected future location of the client device or the expected route of the client device based on the information identifying the location of the client device and at least one of: information identifying one or more expected possible routes e associated with the client device, or information identifying a route history associated with the client device, determine, based on the expected future location of the client device, information representing a map fragment and can determine speed limit information associated with the map fragment and, transmit, to the client device, the information representing the map fragment and the speed limit information, wherein the client device is to use the information representing the map fragment and the speed limit information to determine a speeding event associated with a vehicle.

A novel light-emitting element material is provided. Alternatively, a light-emitting element material capable of simplifying a process for manufacturing a light-emitting element is provided. Alternatively, a light-emitting element material capable of reducing the cost for manufacturing a light-emitting element is provided. Alternatively, one embodiment of the present invention provides a light-emitting element material capable of achieving a light-emitting element having favorable emission efficiency. A light-emitting element material including an organic compound which includes a first skeleton having a carrier-transport property and a second skeleton having a light-emitting property in one molecule and in which the molecular weight is less than or equal to 3000, is provided.

Controlling a vehicle according to a trained neural network model capable of being used to generate an output from which one or more vehicle operating variables can be estimated. The neural network model can be used to process, as input, aggregated data corresponding to operational and/or environmental characteristics experienced by the vehicle during at least a portion of a voyage. The aggregated data can include a range of values collected over a period of time when the vehicle is traversing the portion of the voyage. The output generated by the neural network model, based on processing the input, can be further processed in order to determine, for example, an estimated state of charge and/or an estimated remaining flight time for the vehicle. Such estimated values can thereafter be used by a controller of the vehicle to maintain course or maneuver to a charging station.

Systems, methods, and apparatus related to determining ice hazards on roads based on crowdsourced data from vehicles. In one approach, a server receives weather data and location data from each of several vehicles. The weather data is timestamped when received. The server determines, using the location data, a geographic region in which each vehicle is located. The weather data is stored in a database associated with the respective geographic region for the vehicle that transmitted the weather data. The server periodically scans the database to select weather data received over a selected time period. The selected data is analyzed to determine whether an ice hazard exists for one or more regions. A communication is sent to vehicles in those regions having the determined ice hazard.