17 results about "Route assignment" patented technology

The invention provides an intelligent assignment scheduling method and system for transportation, and relates to the field of logistics management, and the method comprises the steps: obtaining order information and transport capacity resource information, the order information comprises cargo attributes, the own transport capacity resource information comprises vehicle shipping space parameters, and the external transport capacity resource information comprises simplified load parameters; and processing the internal image of the vehicle cabin by using a wavelet transform method so as to determine three-dimensional parameters of the abnormal area and generate accurate vehicle cabin space parameters. Based on the order information and the accurate vehicle shipping space parameters, vehicle and route allocation is carried out through a multi-target scheduling algorithm, and candidate scheduling schemes are generated; and executing three-dimensional loading feasibility verification by utilizing a multi-grid construction module so as to predict the deformation condition of the goods and the vehicle shipping space and mark the ghost volume. And finally outputting an optimal scheduling scheme in response to verification passing. According to the method, the refinement level of logistics transportation management is effectively improved, space conflicts and overload risks are avoided, and the transport capacity resource utilization efficiency and the transportation safety are improved.

The invention relates to the field of intelligent logistics optimization, and discloses an unmanned aerial vehicle transportation route distribution method for logistics multi-point transportation, which comprises the following steps: carrying out coordinate-weight joint standardization on a distribution point set to generate a three-dimensional feature vector; constructing a topological complex based on the standardized data, and extracting a key ring structure through continuous coherence; encoding the ring structure into a topological constraint term of a quantum model, and constructing Hamiltonian containing distance, load and topological constraint; dividing quantum sub-blocks according to the topological ring, and executing block annealing solution through chain coupling constraint; and carrying out topology-guided privacy fine tuning under a federated learning framework by using gradient information of a quantum solution. According to the method, a complex path optimization problem is decomposed into sub-problems capable of being processed in parallel through a quantum topological coding and block annealing strategy, quantum bit grouping is guided through a topological ring structure, the calculation complexity is reduced, efficient solving of a large-scale logistics network is achieved, and the calculation speed is increased compared with a traditional optimization method.

A method includes (a) receiving course data identifying a first zone, a second zone, and a third zone within a golf course, (b) generating time prediction data including predicted work times indicating a predicted amount of time required for a mower to mow one of the zones, (c) receiving a set of desired mowing parameters indicating that a first mower and a second mower are available for maintenance of the golf course, (d) generating a first route assignment for the first mower and a second route assignment for the second mower based on the course data and the time prediction data, and (e) providing a graphical user interface including instructions for an operator to complete the first route assignment using the first mower. The first route assignment includes mowing the first zone and the second zone. The second route assignment includes mowing the third zone.

A load and route assignment system is provided and generally includes a computing device and a database. The database may store historical inbound load data and historical outbound load data related to previous inbound and outbound loads. The computing device can obtain and aggregate the historical inbound and outbound load data from the database, and determine an optimal path based on the aggregated historical data. The optimal path, along with load attribute data, may be stored in the database as a tour template for future load executions. The computing device may use the tour templates to determine future load assignments to vehicles. The computing device may also obtain real-time load requests, and match them to one or more of a plurality of tour templates. The computing device may assign the matched real-time load requests to a vehicle for execution in accordance with the corresponding load and tour template.

A method and server for generating a prediction score by a Machine Learned Algorithm (MLA). The method includes: acquiring route data, generating a plurality of route scores for the plurality of routes based on the route data, acquiring driver data, generating a plurality of driver scores for the plurality of drivers based on the driver data, and for a given route-driver pair: generating by the MLA a given prediction score indicative of a likelihood of the given driver having an accident on the given route within a predetermined amount of time after initiating the given route. The method also includes assigning, by employing a dispatching algorithm based on the prediction score, the given route to the given driver for providing a transportation service to the user.

To provide a ground control device which assigns routes to multiple trains to operate efficiently while preventing the route from becoming undefined.SOLUTION: A ground control device comprises a linkage information acquisition unit 31 to acquire linkage information including information on a ground signal, a holding signal and a direction of a point device from a linkage device 20, a positional information acquisition unit 32 to acquire positional information from a train 10, a storage unit 33 to store a route database 331 with route identification information, a block included in the route, directional information of the point device in the route, and the positional information of the point device defined, and a control unit 34 to give the route corresponding to the route of the train 10 to the train 10 so that the direction of the point device ahead of the on-rail position of the train 10 displayed in the positional information in the travelling direction matches the definition of the route database 331 based on the route information defined by the linkage information, the positional information, and the route database 331.SELECTED DRAWING: Figure 1

Embodiments of the present application provide a route assignment method and a route assignment device relating to the field of data processing technology. The route assignment method includes determining the destination of a target robot when the target robot is unloaded, assigning a route to the destination to the target robot based on a target aisle where the space below the shelf is not occupied by a robot, and transmitting the assigned route to the target robot. By applying the technical proposal provided by embodiments of the present application, the probability of robot congestion in a warehouse can be reduced.

Device for sorting parcels (115, 115-1, 115-2, 115-3, 115-4), the device comprising: a sliding device defining a transport surface (125, 125-1, 125-2, 125-3) configured to transport packages (115, 115-1, 115-2, 115-3, 115-4) from an upstream point of the sliding device to a downstream point of the sliding device, the transport surface (125, 125-1, 125-2, 125-3) comprising a plurality of surface segments (135, 135-1, 135-2, 135-3) disposed between the upstream point and the downstream point, each of the plurality of surface segments (135, 135-1, 135-2, 135-3) having selected geometry and surface properties for controlling speeds of the packages (115, 115-1, 115-2, 115-3, 115-4) when conveyed from the upstream point to the downstream point, wherein the sliding device further defines an opening (140, 140-1, 140-2) in the transport surface (125, 125-1, 125-2, 125-3),which is dimensioned to receive one or more of the packages (115, 115-1, 115-2, 115-3, 115-4) therethrough; at least one door (205) arranged in the sliding device, the door (205) being selectively positionable at least between: a first position in which the door (205) closes the opening (140, 140-1, 140-2) and forms at least a portion of the transport surface (125, 125-1, 125-2, 125-3), and a second position in which the door (205) opens the opening (140, 140-1, 140-2) to allow the one or more packages (115, 115-1, 115-2, 115-3, 115-4) to pass therethrough, the door (205) comprising: a first door region (430) defining a first portion of the portion of the transport surface (125, 125-1, 125-2, 125-3), the first portion having a first coefficient of friction; and a second door region (435) defining a second portion of the portion of the transport surface (125, 125-1, 125-2, 125-3), the second portion having a different, second coefficient of friction; and a route distributor (145, 145-1, 145-2) arranged below the opening (140, 140-1, 140-2) and comprising: a diverter system (215, 315) comprising one or more diverter devices (330, 340-1, 340-2) operable to divert individual packages (115, 115-1, 115-2, 115-3, 115-4) to a selected one of a plurality of outlets (320-1, 320-2, 320-3, 320-4).

A method for assigning a route of a truck, the method being performed by an electronic device according to an embodiment of the present disclosure, may comprise the steps of: generating a plurality of pieces of lane information indicating unique routes of trucks moving in different workplaces among a plurality of workplaces; generating a plurality of groups by grouping the plurality of pieces of lane information on the basis of the plurality of workplaces; and assigning a plurality of vendors to each of the plurality of groups.

The present application provides a method and system for intelligent assignment and scheduling of transportation, which relates to the field of logistics management. The method includes: obtaining order information and transportation capacity resource information, where the order information includes cargo attributes, the information of self-owned transportation capacity resources includes vehicle cabin parameters, and the information of external transportation capacity resources includes simplified load parameters. Processing the internal image of the vehicle cabin by using the wavelet transform method to determine the three-dimensional parameters of the abnormal area and generate accurate vehicle cabin parameters. Based on the order information and the accurate vehicle cabin parameters, vehicle and route allocation are performed through a multi-objective scheduling algorithm to generate a candidate scheduling plan; then a three-dimensional loading feasibility check is executed by using a multi-grid construction module to predict the deformation of the cargo and the vehicle cabin and mark the ghost volume. Finally, in response to the passing of the check, the optimal scheduling plan is output. The present invention effectively improves the refinement level of logistics transportation management, avoids space conflicts and overloading risks, and improves the utilization efficiency of transportation capacity resources and transportation safety.

A method (100) for dispatch planning of an electric vehicle (EV) fleet is disclosed, which optimizes route assignments and charging schedules. The method comprises obtaining fleet, route, and energy pricing information, including initial states of charge (SoC) and required SoC for each route. For each route, the method involves determining a pre-trip SoC and a post-trip SoC for feasible EVs, selecting an EV based on predefined criteria, and mapping it to the route. A charging schedule is determined using a charging duration factor (CDF) which is inversely proportional to average energy costs. The method outputs a dispatch plan with route mappings and the charging schedule. This approach balances maximizing fleet utilization with minimizing charging costs, offering a scalable solution for efficient EV fleet management.

The present disclosure provides a resource allocation method, apparatus, and control device. The method includes: obtaining network topology information, the network topology information including location information of nodes in the network and information about routes connecting nodes in the network; using an edge coloring algorithm to color all routes in the network into a plurality of colors, wherein routes colored the same color are not connected; allocating resources to each route to be transmitted based on the color of the route in the network and the route of information to be transmitted, wherein routes of the same color are allowed to be allocated resources of different beams in the same time slot; determining whether beams used by routes allocated to the same time slot conflict based on the location information of nodes in the network; and reallocating a time slot for at least one route with a conflict in the time slot in response to a conflict in beams used by routes allocated to the same time slot.

A system includes one or more processing devices and at least one memory on which are stored instructions that, when executed by the one or more processing devices, enable the one or more processing devices to perform a method of facilitating delivery of an item from a source destination to a target destination. The method includes the steps of receiving a delivery-route assignment request from a first user device associated with a producer, transmitting the request to one or more vehicle drivers, receiving an acceptance of the request from a second user device associated with a vehicle driver, receiving a first signal indicating that the vehicle driver is a predetermined first distance from the source destination, receiving a second signal indicating that the vehicle driver is a predetermined distance from the target destination, and in response to receiving the second signal, authorizing a payment to the vehicle driver.

A data migration method includes: obtaining, by a first node, a first route assignment table; receiving, by the first node, a first instruction; obtaining, by the first node by using the first route assignment table, a first partition identity (ID) based on a first primary key ID carried in the first instruction; determining, by the first node, a second node based on the first partition ID; and transmitting, by the first node, first data uniquely identified by the first primary key ID to the second node.

A mobility system for a vehicle may include, among other things, a computing device including one or more processors coupled to memory. The one or more processors may be collectively operable to execute a mobility environment. The mobility environment may be operable to obtain, from a route planner, a proposed route for a vehicle and a mission profile associated with the proposed route. The mobility environment may be operable to assign, using a machine learning model, a route score to the proposed route based on the respective mission profile. The mobility environment may be operable to communicate the route score to the route planner. A method for route planning of a vehicle is also disclosed.

The embodiment of the invention relates to the technical field of carbon emission benefit evaluation, and provides a carbon emission benefit evaluation method and system for a subway system, and the method comprises the steps: determining the travel demand distribution based on the current population distribution of a target city; carrying out traffic mode and route distribution on each travel demand based on the public traffic service and travel demand distribution of the target city; the method comprises the following steps: calculating a first traffic carbon emission comprising a subway system based on a traffic mode and a route distribution result of each travel demand, and carrying out anti-fact simulation on a condition that a public traffic service does not comprise the subway system, calculating a second traffic carbon emission which does not include the subway system based on the traffic mode of each travel demand and the route distribution result; and evaluating the carbon emission benefit of the subway system based on the first traffic carbon emission and the second traffic carbon emission. Therefore, the carbon reduction benefit of subway system operation can be accurately evaluated.

The present application relates to routing assignments based on error correction capabilities. The systems and methods described herein relate to bidirectional data path DQ symbol mappings generated based on error correction operations. A device may include a sub-wordline driver and a bidirectional data path DQ coupled between the sub-wordline driver and an input / output I / O interface circuit system based on an assignment indicated by the DQ symbol mapping. The assignment may be generated based on an error correction operation performed on data of a memory bank. Specifically, the DQ symbol mapping may be generated to avoid some situations that may render one or more data errors uncorrectable when they occur. These systems and methods may reduce the likelihood that data errors associated with the DQ are uncorrectable.