Abstract: Desired vehicle destinations may be determined from spoken dialogs. A speech input may be received from a user through a voice user interface. Current utterance variables may be obtained by tokenizing the user speech input. One or more of a plurality of utterance templates for a reply to the user speech input may be determined by a trained automatic agent based on the plurality of current utterance variables. One of a plurality of Application Programming Interfaces (API) to call and one or more parameters for the API to call with may be determine by the trained automatic agent based on the plurality of current utterance variables. A response may be obtained from the API call. A context string for the reply to the user speech input by the trained automatic agent may be constructed based on the utterance templates and the response of the API call.

Abstract: The present disclosure relates to systems and methods for generating a document based on a template document. The system may perform the methods to crawl across a multi-level tree along a path from a root to a plurality of leaf nodes. The multi-level tree may include a plurality of intermediate level nodes, wherein each of the plurality of intermediate level nodes may be associated with one or more sub-nodes at a next level. Each of the plurality of intermediate level nodes may include an intermediate subject of the intermediate level node, a semantically incomplete intermediate description related to the intermediate subject, and template data defining a position that the intermediate description may be in a corresponding template document.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: Embodiments of the disclosure provide systems and methods for verifying digital payments for a payment platform. The system includes a communication interface configured to receive service data associated with a transaction from a terminal device associated with a user of the payment platform. The system further includes at least one processor configured to automatically determine whether an authentication is waived for the transaction based on the received service data and a blacklist generated using a machine learning model. The blacklist includes a list of suspicious users and transaction behaviors. The at least one processor further configured to approve the transaction without requesting user authentication information from the terminal device when the authentication is waived. The at least one processor also configured to request the user authentication information from the terminal device and validate the user authentication information when the authentication is not waived.

Abstract: After receiving a trip request, a ridesharing platform system can determine scores for each prior trip request within a time window from features associated with the prior trip request. The ridesharing platform system can determine patterns from corresponding scores and determine a risk for the trip request using on the patterns. The ridesharing platform system can determine whether to accept or decline the trip request based on the risk for the trip request.

Abstract: The present disclosure provides methods and systems for vehicle verification. The method may include receiving vehicle verification information related to a vehicle to be verified from a client, wherein the vehicle verification information includes a plurality of images acquired by the client via an imaging device, and the vehicle verification information responds to at least one vehicle verification instruction. The method may further include determining a verification result of the vehicle based on the vehicle verification information.

Abstract: Embodiments of the disclosure provide methods and systems for generating a color point cloud. The method may include receiving a point cloud and a plurality of images with respect to a scene captured by a plurality of sensors associated with a vehicle as the vehicle moves along a trajectory. The method may include segmenting the point cloud into a plurality of segments each associated with a start point and an end point on the trajectory of the vehicle. The method may also include associating each segment of the point cloud with one or more of the images based on the start point and the end point. The method may further include generating color point cloud by aggregating each segment of the point cloud and the one or more of the images based on calibration parameter in different distances between the segment of the point cloud and the vehicle.

Abstract: The present disclosure is related to systems and methods for recommending a personalized pick-up location. The method may include obtaining data from a requestor; determining a recommended pick-up location and a description of the recommended pick-up location based on the data; and output the recommended pick-up location and the description of the recommended pick-up location.

Abstract: A method for carpool services includes obtaining a pending transportation service requested by a service requester. The pending transportation service may include a first origin and a first destination. The method may also include determining a first pick-up location and a first departure time from the first pick-up location for the pending transportation service based on the first origin and the first destination. The method may also include determining a target service provider based on the pending transportation service and a shareable transportation service that has been accepted by the target service provider and has not been completed.

Abstract: The embodiments of the present disclosure provide a visual positioning method, the method may include obtaining a positioning image collected by an imaging device; obtaining a three-dimensional (3D) point cloud map associated with an area where the imaging device is located; determining a target area associated with the positioning image from the 3D point cloud map based on the positioning image; and determining positioning information of the imaging device based on the positioning image and the target area.

Abstract: The application discloses Systems and methods for a data synchronization. The system may include a receiving module, an instruction generating module and a sending module. The receiving module may be configured to receive the first instruction. The first instruction may be used to instruct the start of data acquisition of the system. In response to receiving the first instruction, the instruction generating module may be configured to generate a second instruction. The second instruction may be used to trigger at least two sensors to acquire data. The sending module may be configured to send second instruction to at least two sensors respectively based on the first delay. The first delay causes the time difference between at least two sensors starting to acquire data less than the first preset threshold.

Abstract: Systems and methods are provided for using encoded representations of numbers in various applications. The encoded representations of numbers, also referred to as number embeddings, may be multi-element data structures (e.g., multi-dimensional vectors) in which each element is a real-numbered value. The values of a given number embedding collectively encode information from which properties of the number represented by the number embedding may be derived. Number embeddings may be compared or otherwise analyzed with respect to each other to identify patterns or similarities in the numbers represented by each number embedding.

Abstract: Systems and methods are provided for ride order dispatching and vehicle repositioning. A method for ride order dispatching and vehicle repositioning, comprises: obtaining information comprising a location of a vehicle, current orders, and a current time; inputting the obtained information to a trained model; and determining action information for the vehicle based on an output of the trained model, the action information comprising: re-positioning the vehicle or accepting a ride order. The model is configured with: receiving information of drivers and information of orders as inputs; obtaining a global state based on the information of drivers, the information of orders, and a global time; and querying a plurality of driver-order pairs and driver-reposition pairs based at least on the obtained global state to determine the action information as the output.

Abstract: Systems and methods for optimizing an online on-demand service are provided. A method may include: obtaining driver information associated with a plurality of historical drivers corresponding to the plurality of historical orders; for each historical driver during a predetermined period of time, determining a plurality of records based on the order information and the driver information according to a decision-making processes, each record includes a driver's space-time status, a driver's action, a driver's revenue, and a driver's subsequent space-time status; and determining a value function based on the plurality of records of each historical driver according to a reinforcement learning algorithm.

Abstract: The present disclosure relates to a method and system for determining a transport service fee. The method may include: obtaining a service request transmitted from a passenger terminal, wherein the service request includes starting point information and destination information; determining an estimated transport service fee based on the service request; obtaining a price adjustment condition based on the service request, wherein the price adjustment condition is related to the starting point or historical information of the passenger terminal or a driver terminal; determining an amount of the price adjustment based on the price adjustment condition; determining an estimated transport service fee after the price adjustment based on the amount of the price adjustment and the estimated transport service fee; and sending the estimated transport service fee after the price adjustment to the passenger terminal.

Abstract: Systems and methods are provided for data security grading. An exemplary method for data security grading, implementable by a computer, may comprise receiving a request to access a query data field, searching for the query data field from a security level table, in response to finding the query data field from the security level table, obtaining from the security level table a security level corresponding to the query data field, and in response to not finding the query data field from the security level table, determining a security level corresponding to the query data field based at least on a lineage tree and the security level table. The lineage tree may trace the query data field to one or more source data fields, and the security data level table may comprise one or more security levels corresponding to the one or more source data fields.

Abstract: Methods and systems for off-route identification may be provided. A first navigation route of an object that is traveling and one or more positioning location points during traveling may be obtained. Whether a first preset condition is satisfied may be determined based on a positional relationship between the one or more positioning location points and the first navigation route. In response to determining that the first preset condition is not satisfied, whether the object is off-route may be determined based on information associated with the traveling of the object.

Abstract: A method for decrypting an encrypted message in a cluster may be provided. The method may include generating, by a first private key generator, one or more system parameters and a master key using a security parameter of the cluster and a depth of the maximum of a unit vector, the cluster including a first member and a second member. The method may also include generating, by the first private key generator, a private key of the first member; The method may further include generating, by a second private key generator, a private key of the second member based on the one or more system parameters, the identification vector of the first member, the private key of the first member, and an identification vector of the second member; The method may still further include decrypting the encrypted message the private key of the first member or the second member.

Abstract: A system may include a computer-readable storage medium configured to store a first set of instructions for determining one or more candidate driver terminals to accept a service request; and a processor in communication with the computer-readable storage medium, wherein when executing the first set of instructions, the processor is directed to: establish a communication with a passenger terminal; obtain a service request including a position of the passenger terminal from the passenger terminal: determine a wireless fidelity (WiFi) station based on the position of the passenger terminal; determine one or more driver terminals that access the WiFi station; determine an access instance of each of the one or more driver terminals; and determine one or more candidate driver terminals among the one or more driver terminals based on the one or more access instances of the one or more driver terminals.

Abstract: Dynamic pricing may be applied in an online ride-hailing platform. Information may be obtained. The information may include a set of pricing candidates and an initial status of a ride-hailing platform. The set of pricing candidates may be updated based on the initial status of the ride-hailing platform to minimize a cross-entropy between the set of pricing candidates and a target pricing policy that maximizes a total income of the ride-hailing platform. A price for at least one current trip request on the ride-hailing platform may be generated based on the updated set of pricing candidates.