A system described herein may provide a technique for the generation of a node map using contraction hierarchy techniques in a manner that accounts for multi-link constraints. Multi-link constraints may include a sequence of two or more links through the node map, and paths that include such multi-link constraints may be associated with an additional cost based on such inclusion. Shortcut links that represent paths through nodes contracted out of the node map may be associated with portions of multi-link constraints. Paths through such shortcut links, where such paths include the remainder of the multi-link constraint, may be considered as including the multi-link constraint, and the cost of such paths may be calculated accordingly. The costs of links and/or paths, including paths that include multi-link constraints, may be used in determining a path from a source node to a target node of the node map.

The present subject matter relates to determine a snapping position in a road network for a destination object by using a cost matrix indicative of accumulative cost values of cells of the matrix. The accumulative cost value of a cell is indicating a cost to travel a path from the cell to a road segment of the road network.

An autonomous vehicle includes a control system for remotely controlling the same. The autonomous vehicle includes an autonomous driving control apparatus having a processor that is configured to transmit an emergency request message to a control system when an emergency occurs to an emergency patient in the vehicle during autonomous driving, and the autonomous driving control apparatus is configured to direct the autonomous vehicle to follow a path with a shortest estimated required time among a contact path with an ambulance, a contact path with a neighboring vehicle capable of first aid, or a travel path to a hospital depending on remote control of the control system.

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive images representative of an environment of the host vehicle and analyze the images to identify a first object and a second object. The processor may determine a first predefined navigational constraint implicated by the first object and a second predefined navigational constraint implicated by the second object, wherein the first and second predefined navigational constraints cannot both be satisfied, and the second predefined navigational constraint has a priority higher than the first predefined navigational constraint. The processor may determine a navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint and, cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

A maintenance time acquisition unit acquires a periodic inspection and maintenance time determined in advance for each of a plurality of electric vehicles, a battery remaining life prediction unit predicts a remaining life of each of storage batteries from a state of the storage battery of each of the plurality of electric vehicles, and an operation plan creation unit creates an operation plan of the plurality of electric vehicles based on the periodic inspection and maintenance time of each of the plurality of electric vehicles and the remaining life of the storage battery of each of the plurality of electric vehicles.

A vehicle routing evaluation system makes predictions about network performance data along road segments relevant to navigation of a vehicle and generates routing instructions or recommendations based in part on the network performance data. The vehicle routing evaluation system may send control signals to automatically control navigation of the vehicle to follow the routing generated routing or may present the navigation instructions to a teleoperator that controls the vehicle. Alternatively, the vehicle routing evaluation system generates a display with a navigational map overlay providing visual cues indicative of predicted wireless performance along various road segments to enable the teleoperator to select between possible routes.

A system (900) and method (1100) instructing a vehicle (910) where and when to refuel is disclosed herein. The system (900) comprises a server (925) for receiving a workflow for a vehicle (910). The workflow comprises an origination location (901) of the vehicle, a destination (950) of the vehicle (910), a route (905) to the destination, a cargo, a time of departure and a time of arrival. The server (925) determines a plurality of fuel stops (930) along the route (905).

One example method includes receiving information indicating a population of wild insects within a geographic region; determining a number of wild insects per unit area within the geographic region; placing, based on the number of wild insects per unit area, one or more insect release points based on the number of wild insects per unit area, each insect release point indicating a release of a predefined quantity of insects; and generating an insect release route through the geographic region, the insect release route passing through each insect release point.

A method of controlling a vehicle or robot. The method includes the following steps: determining a first control sequence, determining a second control sequence for controlling the vehicle or robot depending on the first control sequence, a current state of the vehicle or robot, and on a model characterizing a dynamic behavior of the vehicle or robot, controlling the vehicle or robot depending on the second control sequence, wherein the determining of the first control sequence is performed depending on a first candidate control sequence and a second candidate control sequence.

The present application discloses a method and apparatus for determining a route, a device and a computer storage medium, and relates to the field of big data. An implementation includes: acquiring route description information input by a user, and acquiring a route contour with the route description information; matching the route contour in road network data to obtain the route matched with the route contour, so as to generate recommended routes, wherein this operation specifically includes: extracting intersection points in the route contour, each of which is formed by intersecting at least two lines; selecting one of the intersection points, and querying the road network data using a corresponding angle sequence of the selected intersection point in the route contour, so as to obtain intersections matched with the selected intersection point as candidate intersections; traversing the candidate intersections, fixedly mapping the selected intersection point to the positions of the candidate intersections, equally scaling the route contour in the road network data, and recording mapped road information if all lines of the route contour are mapped onto connected roads; and generating the recommended routes with the recorded road information.