Data are collected on a turbidity of a fuel tank at each of a plurality of fueling stations. A fueling station is selected based on the collected data. A vehicle is moved to the selected fueling station.

Methods and apparatuses are provided for use in wireless communication devices to provide a capability for vehicles to actively perform traffic planning with regard to other vehicles, for example, within a region comprising an intersection and possibly wherein the intersection is not associated with a device or service for such or similar purposes. Such underlying techniques may reduce traffic congestion in certain instances by allowing two or more vehicles to negotiate or otherwise coordinate safe traversal within a region comprising an intersection. Moreover, the traffic planning techniques may be of use for a variety and/or mixture of different types of vehicles, paths, intersections, etc.

A path providing device configured to provide a path information to a vehicle includes: a communication unit configured to receive, from a server, map information including a plurality of layers of data, an interface unit configured to receive sensing information from one or more sensors disposed at the vehicle, a processor, and an event data recorder (EDR) configured to store vehicle status information including first sensor data sensed by a first sensor associated with an operation of the vehicle, and second sensor data sensed by a second sensor associated with surrounding information of the vehicle. The processor is configured to determine an optimal path for guiding the vehicle from an identified lane, generate autonomous driving visibility information, update the optimal path based on dynamic information and the autonomous driving visibility information, and include the vehicle status information stored in the EDR in the autonomous driving visibility information.

When the distance indicated by distance information received by a Bluetooth module (31) is less than a predetermined first reference distance (KY1), a guidance image (33) including a distance image (33a) and a direction image (33b) is generated, and this guidance image (33) is displayed on a combiner (26) of a helmet (20). By stopping the display of the distance image (33a) of the guidance image (33) and continuing to display the direction image (33b) from when the distance indicated by the distance information becomes less than a second reference distance (KY2) shorter than the first reference distance (KY1) to when the guidance point is reached, the driver's attention is focused on the direction image (33b), so that a mistake in the direction of travel at the guidance point can be prevented.

Provided are an electronic control device and a vehicle control system capable of reducing a calculation amount and improving reliability of a travel route of a vehicle as compared with a conventional course setting device. An electronic control device 200 is mounted on a vehicle 100. The electronic control device 200 includes a map processing device 210 connected to an external sensor 110 that recognizes an obstacle around the vehicle 100 and a position sensor 120 that acquires position information of the vehicle 100 in a manner capable of information communication. The map processing device 210 includes a storage device 212 that stores map information including travel route information of the vehicle 100. The map processing device 210 records a travel route along which the vehicle 100 avoids an obstacle in the storage device 212, classifies the obstacle into a permanent obstacle and a transient obstacle, and updates the travel route information with an avoiding route based on the travel route along which the vehicle 100 has avoided the permanent obstacle.

The present disclosure provides a method and device for predicting a motion track of an obstacle and an autonomous vehicle, and relates to the technical field of autonomous driving, so as to at least solve the technical problem of low prediction precision of a motion track of an obstacle in an interaction scene. A specific implementation solution includes: environment information in a target scene, historical state information of a target obstacle and track planning information of a target vehicle are obtained, and the target obstacle is a potential interaction object of the target vehicle; and a motion track of the target obstacle is predicted based on the environment information, the historical state information and the track planning information.

Autonomous vehicle operational management may include traversing, by an autonomous vehicle, a vehicle transportation network. Traversing the vehicle transportation network may include operating a scenario-specific operational control evaluation module instance, wherein the scenario-specific operational control evaluation module instance is an instance of a scenario-specific operational control evaluation module, wherein the scenario-specific operational control evaluation module implements a partially observable Markov decision process. Traversing the vehicle transportation network may include receiving a candidate vehicle control action from the scenario-specific operational control evaluation module instance, and traversing a portion of the vehicle transportation network based on the candidate vehicle control action.

A method, a system, and a computer program product may be provided for providing traffic data to a client device. The system may receive from the client device, a request for traffic data corresponding to road segments of at least one map area, said request identifying the at least one map area and determine road segment identifiers corresponding to each of the road segments of the at least one map area and determine traffic data for at least a portion of the road segment identifiers, said traffic data obtained from a traffic data source. The system may further determine a plurality of traffic ranges based on the obtained traffic data and generate a bloom filter set, each bloom filter of the bloom filter set corresponding to a traffic range of the plurality of traffic ranges, wherein each bloom filter encodes road segment identifiers corresponding to the respective traffic range.

A system for managing a fleet of vehicles having autonomous or semi-autonomous control based upon real-time data analysis of live driving conditions including traffic conditions, weather conditions, pollution conditions, vehicle operations, vehicle emissions, legal restrictions, and fleet conditions. Older vehicles may be retrofitted with partial or total compatibility with the system via an aftermarket dongle that connects to the vehicle through a diagnostic port.

An example operation includes one or more of determining, by a transport, an energy transfer condition exists along a route, routing, by the transport, to a location on the route based on the energy transfer condition exceeding an energy transfer value and based on one or more traffic conditions, aligning, by the transport, a position of the transport at the location to wirelessly receive an energy transfer, and receiving, by the transport, the energy transfer while the transport is in motion.