Aspects of the present invention disclose a method for routing one or more autonomous vehicles to minimize a density of autonomous vehicles and passengers passing through network areas with oversubscribed bandwidth. The method includes one or more processors determining a bandwidth requirement of a first autonomous vehicle. The method further includes determining respective bandwidth requirement for one or more additional autonomous vehicles utilizing a wireless network. The method further includes determining a total bandwidth capacity of one or more nodes of the wireless network. The method further includes determining routing instructions from a current location of the first autonomous vehicle to a destination of the first autonomous vehicle based at least in part on the bandwidth requirement of the first autonomous vehicle and the total bandwidth capacity of the one or more nodes of the wireless network.

Systems and methods for providing lane-specific recommendations to a vehicle operator of a vehicle operating on roadways are disclosed. The roadways include one or more lanes in each direction of travel. Exemplary implementations may: generate, by a set of sensors, output signals conveying information pertaining to the vehicle; determine a current location of the vehicle; determine a current direction of travel of the vehicle; detect a current lane being used by the vehicle from the multiple traffic lanes of the particular roadway at the current location in the current direction of travel; obtain lane-specific information regarding the multiple traffic lanes at or near the current location of the vehicle; obtain a goal for providing lane-specific recommendations; determine a lane-specific recommendation for the vehicle; and provide the lane-specific recommendation to the vehicle operator.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for determining data collection values for enhanced sensor provider vehicles in a provider vehicle pool and utilizing the data collection values to select and dispatch a provider vehicle for a transportation request. In particular, in one or more embodiments, the disclosed systems determine data collection values based on various route features for a particular enhanced sensor provider vehicle. Additionally, in one or more embodiments, the disclosed systems can utilize the data collection values in conjunction with a device matching algorithm and transportation values to select and dispatch a provider vehicle. Further, in some embodiments, the disclosed systems utilize collected sensory data to train one or more computer implemented machine learning models, such as an autonomous vehicle driving model.

The present disclosure relates to a vehicle scheduling method, apparatus, and system. The method includes: repeatedly performing following steps according to a preset scheduling period: receiving travelling information acquired by a target vehicle; searching, according to a global path of the target vehicle, a topological map for a target directional path matching the travelling information; determining a right-of-way node sequence of the target vehicle according to the target directional path and a coverage range of the target vehicle, where the right-of-way node sequence includes multiple right-of-way nodes, and the right-of-way nodes are nodes on the topological map; and determining right-of-way nodes matching the global path in the right-of-way node sequence as target right-of-way nodes in a case that each of the right-of-way nodes in the right-of-way node sequence is in a vacant state, and sending the target right-of-way nodes to the target vehicle, so that the target vehicle travels according to a path indicated by the target right-of-way nodes.

Upon report of an emergency incident, a system may dispatch one or more initial entities to respond to the incident and model an initial scene, based on the reported data. The system may further determine the availability of travel data, request available travel data and advise an entity of path feasibility. The system also determines availability of onsite data covering one or more locations associated with the incident and requests available onsite data. This data is used to update the scene model and determine additional necessary dispatches, data gathering, or both. Until additional data is determined to be no longer needed, the processor is configured to continue to: dispatch entities based on the updated scene model; determine the availability of additional onsite desired based on the updated scene model; request the new onsite data; and update the scene model based on any onsite data received responsive to any additional requests.

Aspects of the present disclosure describe systems, methods, and devices for automated vehicular control based on glare detected by an optical system of a vehicle. In some aspects, automated control includes controlling the operation of the vehicle itself, a vehicle subsystem, or a vehicle component based on a level of glare detected. According to some examples, controlling the operation of a vehicle includes instructing an automatically or manually operated vehicle to traverse a selected route based on levels of glare detected or expected along potentials routes to a destination. According to other examples, controlling operation of a vehicle subsystem or a vehicle component includes triggering automated responses by the subsystem or the component based on a level of glare detected or expected. In some additional aspects, glare data is shared between individual vehicles and with a remote data processing system for further analysis and action.

Disclosed are a method by which a V2X vehicle transmits a virtual V2X message in a wireless communication system supporting a sidelink according to various embodiments, and a device therefor, the method comprising: a step for periodically receiving a first message including first vulnerable road user (VRU) information on a first VRU from a network; a step for determining a state of the first VRU on the basis of the first VRU information, and determining whether to convert the first message to the virtual V2X message on the basis of the state of the first VRU; and a step for transmitting the virtual V2X message including the first VRU information, wherein the V2X vehicle converts the first message into the virtual V2X message when the first VRU state changes from a first state to a second state on the basis of the periodically received first message.

This disclosure relates to a distributed data center that includes resources carried by a fleet of vehicles. The system includes sensors configured to generate output signals conveying information related to the vehicles and/or the surroundings of vehicles. The system includes a remote computing server configured to maintain map data and distribute it to the fleet, including local map data to individual vehicles pertaining to their surroundings. Individual vehicles may compare the local map data with the information related to their individual surroundings. Based on such comparisons, individual vehicles may detect discrepancies between the local map data and the information related to their individual surroundings. The remote computing server may modify and/or update the map data based on the detected discrepancies.

A system for managing vehicles includes a plurality of first level managers, and a plurality of second level managers each being in a higher hierarchical level than the plurality of first level managers and managing a section. Each of the plurality of first level managers collects data using one or more sensors of a vehicle, abstracts the data to obtain first information, and transmits a first instruction to the vehicle based on the first information. One of the plurality of second level managers receives the first information from one or more of the plurality of first level managers in the section managed by the one of the plurality of second level managers, obtains second information based on the first information, and transmits a second instruction to the vehicle based on the second information. The first instruction is different from the second instruction.

A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.