Abstract: A method of hybrid lane modeling, including, receiving a roadway image, extracting a set of lane points from the roadway image, fitting a polynomial line to the set of lane points, determining a fitted error of the fitted polynomial line, outputting the polynomial line if the fitted error is less than a predetermined threshold, selecting a set of clean lane points from the set of lane points if the fitted error is greater than the predetermined threshold and interpolating a cubic spline line to the set of clean lane points.

Abstract: The present disclosure provides a method for communal facilities management in a smart city based on an Internet of Things.

Abstract: Provided are an intelligent parking method and apparatus, relating to the technical field of vehicles. The method comprises: determining a target parking route from at least one pre-stored parking route; determining a target position point in the target parking route closest to a vehicle; sending a prompt message for driving the vehicle to the target position point to a driver of the vehicle when a current position point of the vehicle and the target position point satisfy a proximity matching condition; and when the vehicle drives to the target position point, controlling the vehicle to park according to the target parking route from the target position point. Thus, the driver merely needs to drive the vehicle to a vicinity of the target parking route, and the vehicle may perform intelligent parking and may complete intelligent parking at a longer distance.

Abstract: Systems, methods, and non-transitory computer-readable media can receive transportation information associated with a transportation request, the transportation information comprising a pick up location and a drop off location. A first route associated with the transportation request and a non-autonomous vehicle can be determined. A second route associated with the transportation request and an autonomous vehicle can be determined based on an operating design domain (ODD) associated with one or more autonomous vehicles in a fleet of vehicles. At least one performance metric associated with the second route can be determined. The second route can be selected based at least in part on the at least one performance metric and a comparison of the first route and the second route. An autonomous vehicle from the fleet of vehicles can be assigned to the transportation request based on selection of the second route.

Abstract: A starting point, a set of one or more way points, and a destination point of a route along which the ADV is to be driven are determined. All lane segments near the starting point, the set of way points, and the destination point within a predetermined threshold distance are determined respectively. A set of route candidates are determined with an A-star (A*) searching algorithm based on a set of nodes representing all the lane segments near the starting point, the set of way points, and the destination point respectively. The route is selected from the set of route candidates based on respective costs of the set of route candidates. The ADV is being controlled to drive along the selected route autonomously.

Abstract: Providing explanations in route planning includes determining a route based on at least two objectives received from a user, where a second objective of the at least two objectives is constrained to within a slack value of a first objective of the at least two objectives; receiving, from the user, a request for an explanation as to an action along the route; and providing the explanation to the user. The explanation describes an extent of violating the slack value.

Abstract: Provided is an area evaluation system comprising an area evaluation unit (601) that evaluates, when a first mission that uses a first area and a second mission that does not use the first area are provided, utility of the first area based on a difference between utility of the first mission and utility of the second mission.

Abstract: A device for generating vehicle data-based boarding and alighting point information includes a time series data processor that resamples a plurality of time series data including first speed data of the vehicle based on a preset first time; a GPS data processor that resamples GPS data including second speed data of the vehicle based on a preset second time, a location data deriving device that integrates the time series data and the GPS data based on the first speed data, the second speed data, and DTW algorithm, and obtains location data of the vehicle from the integrated data; a location integrating device that integrates location information of a vehicle boarding point and an alighting point received from a public institution; and an identifier generator that generates a boarding point identifier and an alighting point identifier related to a location of the boarding point and the alighting point, respectively.

Abstract: The invention relates to a method for generating a dynamic speed profile of a motor vehicle which is suitable for simulating in particular actual vehicle operation on a route, comprising the following procedural steps: determining a route-based static speed profile for the route resolved into route segments based on information from a digital map; determining a route-based dynamized speed profile on the basis of the route-based static speed profile which factors in a defined maximum target deceleration to reach mandatory speed minima of the speed profile; determining a time-based dynamic speed profile resolved into time increments on the basis of the route-based dynamized speed profile, wherein an applied acceleration is determined in each time increment based on the speed dictated by the speed profile in a route segment corresponding to the respective time increment and the applied speed in the time increment; and outputting the time-based dynamic speed profile.

Abstract: The present disclosure is directed to a computer system and techniques for updating map data used for navigating an autonomous vehicle. In some embodiments, the computer system is configured to obtain map data including a starting location and a destination location; obtain a plurality of travel times corresponding to a plurality of respective possible routes for traveling from the starting location to the destination location; obtain benefit information for at least a first respective possible route; and determine a selected route based on the travel times and the benefit information. In some embodiments, the computer system is configured to obtain a route between a starting location and a destination location; obtain map-age information for the route; determine a first set of driving parameters for the autonomous vehicle based on the map-age information; and navigate the autonomous vehicle along the route using the first set of driving parameters.

Abstract: The subject disclosure relates to ways to improve route duration calculations e.g., estimated time of arrival (ETA) approximations, by taking consideration of reroute probabilities along a given vehicle path. In some aspects, the disclosed technology encompasses a process including steps for identifying a route between a first destination to a second destination, determining a reroute likelihood associated with at least one AV maneuver along the route, and calculating an estimated time of arrival (ETA) based on the reroute likelihood associated with at least one AV maneuver. Systems and machine-readable media are also provided.

Abstract: A method for generating shard data from a geographical area split into sections is proposed. The method uses data representative of a geographical area that is split into sections and data representative of semantic objects located in the geographical area. For each of the sections, semantic objects are searched that are located at least partly in a section. A shard data entry of the shard data is generated. The shard data entry includes one or more semantic objects found by the searching.

Abstract: A traffic signal fixture verification system including an optical recognition means configured to obtain one or more images of two or more traffic signal fixtures in proximity to an ego vehicle, and to detect a motion status of one or more vehicles in proximity to the ego vehicle, a processing means configured to determine a relevance value for two or more traffic signal fixtures identified in the one or more images, monitor a status of each of two or more relevant traffic signal fixtures having a relevance value greater than a threshold value, and based on the relevance values of the two or more relevant traffic signal fixtures, the respective status of each of the two or more relevant traffic signal fixtures, and optionally, and/or the motion status of the one or more vehicles surrounding the vehicle, actuate an accelerator function or a braking function of the ego vehicle.

Abstract: A system is provided for mitigating a road network congestion. The system includes a plurality of motor vehicles positioned in associated locations in a road network. Each vehicle has one or more sensors generating an input and a Telematics Control Unit (TCU) for generating at least one location signal for a location of the associated motor vehicle and at least one event signal for an event related to the associated motor vehicle, with the location signal and the event signal corresponding to a High Speed Vehicle Telemetry Data (HSVT data) based on the input from the sensors. The system further includes a computer, which communicates with a display device and the TCUs. The computer includes a processor and a computer readable medium including instructions, such that the processor is programmed to identify the congestion and determine that the congestion is a recurring or a non-recurring congestion.

Abstract: Aspects of the disclosure provide for identifying problematic areas within a service area for an autonomous vehicle transportation service. For instance, a starting location within the service area corresponding to a potential pickup location for passengers or cargo for the service may be identified. A destination within the service area may be identified. A simulation may be run in order to determine a route for a simulated vehicle to travel between the starting location and the destination. That the route includes a particular type of maneuver may be determined. A new simulation without allowing the simulated vehicle to complete the particular type of maneuver may be run. Whether the simulated vehicle reaches the destination in the new simulation may be determined. Based on the determination of whether the simulated vehicle reaches the destination in the new simulation, the starting location and destination location may be flagged as potentially problematic areas.

Abstract: The subject matter described in this specification is directed to a computer system and techniques for determining a location of an autonomous vehicle. The computer system is configured to determine the location using localization data from multiple data sources. When the localization data from the multiple data sources is unavailable or inaccurate, the computer system is configured to determine the location using predefined features of the environment.

Abstract: Systems and methods for optimizing issue reporting in a navigation environment are provided. In example embodiments, a networked system causes presentation of a navigation user interface on a user device of a user, whereby the navigation user interface includes a route being navigated and navigation instructions. The networked system also causes presentation of one or more issue icons on the user device, whereby each issue icon represents a different type of issue to be reported. A selection of an issue icon from the one or more issue icons is received by the networked system. In response to receiving the selection of the issue icon, the networked system infers a location associated with the issue. The networked system updates a database with the issue and the inferred location. In some embodiments, the database is updated after the inferred location or the issue is verified.

Abstract: A method for determining a pullover spot for a vehicle is described. The method includes using a computing device to detect information related to a system of the vehicle or an environment surrounding the vehicle using a sensor of a vehicle and determine a local failure of the vehicle based on the information. The computing device may then be used to determine that the vehicle should pullover before completing a current trip related to transporting a passenger or good by comparing vehicle requirements for the trip with the local failure and determine a pullover spot by identifying a first area for the vehicle to park in part based on a second area being available for a second vehicle to pick up the passenger or good. The computing device may operate the vehicle to the pullover spot and transmit a request for a second vehicle.

Abstract: Systems and methods are provided for predicting a traversal time for a route. A request for navigation directions is received and a route between the origin and destination is calculated. A series of route segments to be traversed on the route are identified, as well as one or more sub-series of route segments of the series of route segments, with each sub-series having route segments to be traversed consecutively on a portion of the route. For each sub-series, a sub-series traversal time is predicted based on historical traversal time data associated with historical trips where each of the route segments of the sub-series were traversed consecutively. A total route traversal time is predicted based on the sub-series traversal time. A set of navigation directions and the predicted total route traversal time are provided for presentation on a client device for navigating from the origin to the destination via the route.

Abstract: A data storage system configured to optimize selection of a plurality of data storage devices. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium including a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform storage device selection operations which include detecting and gathering storage device information for storing data recordings to the plurality of data storage devices, determining, by a storage load balancer, a plurality of storage efficiency scores for the plurality of data storage devices using a loss function and the gathered storage device information, generating a storage efficiency table, and assigning, by the storage load balancer, a first data recording to one of the plurality of data storage devices based on the storage efficiency table and an efficiency score threshold for the plurality of storage efficiency scores.

Abstract: A method is applied to an electronic device, and includes: obtaining content copied by a user on a first page, and determining a category to which the content belongs; obtaining a category of a second page; matching the category of the content against the category of the second page; and if a matching result is not empty, displaying at least one operation option on the second page, where the at least one operation option has a function of performing an operation for the content on the second page, so that the electronic device directly performs the function after the user selects the operation option.

Abstract: Dynamically adapting provision of notification output to reduce distractions and/or to mitigate usage of computational resources. In some implementations, an automated assistant application predicts a level of engagement for a user and determines, based on the predicted level of engagement (and optionally future predicted level(s) of engagement), provisioning (e.g., whether, when, and/or how) of output that is based on a received notification. For example, the automated assistant application can, based on predicted level(s) of engagement, determine whether to provide any output based on a received notification, determine whether to suppress provision of output that is based on the received notification (e.g.

Abstract: Systems and methods for an On-Demand Autonomy (ODA) service. The system includes a selection module of a leader vehicle (Lv) connected to an ODA server to determine whether to confirm a request for an on-demand autonomy (ODA) service which has been broadcast wherein the ODA service request includes control of a follower vehicle (Fv) to a requested location by creating a virtual link between the Lv and the Fv to configure a vehicle platoon to enable transport of the Fv by the Lv wherein the vehicle platoon is a linking of the Lv to the Fv via the virtual link to enable the Lv to assume the control of the Fv to the requested location.

Abstract: A method and system obtaining positioning data from an object traveling on a plurality of routes; mapping the data into a plurality of points on a digital map; identifying points that are unmatched to the stored route trajectory; obtaining candidate transition points from the unmatched points; aggregating the candidate transition points by applying a clustering algorithm; selecting a first cluster of points and a plurality of second clusters of points, determining a confidence level that the first cluster of points are transition points indicating a transition between the routes, classifying the first cluster of points as a first plurality of traveling points having a first direction in response to the confidence being below a threshold confidence and automatically adjusting the stored route trajectory to indicate that the first cluster of points are on the route trajectory.

Abstract: The present application discloses a map data updating method, an apparatus, a device and a readable storage medium. The specific implementation solution is: after receiving road information reported by an electronic device, a server obtains multiple sequences according to the road information, and each road information belonging to the same sequence has the same type and location. After that, the server inputs each road information contained in the sequences to a pre-trained neural network model, so that the neural network model outputs a recognition result according to the sequences. The server updates map data according to the recognition result. With such solution, valid road information is recognized by combining context of each road information in the sequences and the neural network technology, and the map data is updated, which achieves the purpose of accurately updating the map data.

Abstract: A vehicle control system includes a control unit for vehicle control and a server which distributes map information to the control unit. The map information includes information on a first type of road whereby full or partial driving assistance of the vehicle is possible, and information on a second type whereby full or partial driving assistance of the vehicle are not possible. The server includes an output unit which transmits information on a second type of road existing in a predetermined range from a first type of road on which the vehicle is traveling, and such that the first and second types of road form a predetermined angle or less. The control unit includes a map management unit including information on the first and second types of road, and a vehicle control unit controlling the vehicle by using the information on the first and second types of road.

Abstract: A method for dynamic airspace planning is performed by one or more processors, and includes identifying, in an airspace model that includes an array of nodes, a set of path elements. Each path element connects a pair of adjacent nodes in the array. The method includes obtaining, for each aircraft in a set of aircraft, a respective current position on a path element. The set of aircraft may include thousands of manned and/or unmanned aircraft. The method includes obtaining, for each aircraft, a respective final position on a path element; and enumerating, for each aircraft, a respective set of flight paths. Each flight path includes one or more path elements, and extends from at least the current position of a respective aircraft to the final position of the respective aircraft. The method includes determining, for each aircraft, a respective optimal flight path based on the respective set of flight paths.

Abstract: A method for route planning includes a) making an initial energy forecast for a journey route to a route destination using an initial speed for at least one section of the journey route. The method may also include: b1) making a first energy forecast for the journey route using a first speed for the at least one section; b2) making a second energy forecast for the journey route using a second speed for the at least one section; b3) determining whether the journey route, based on the second energy forecast, includes n or n?1 charging stops; and b4) if the journey route includes n charging stops, determining the first speed as specified speed for the at least one section of the journey route, or if the journey route includes n?1 charging stops, repeating steps b2) and b3) with a third speed for the at least one section.

Abstract: The method system described herein is configured to identify and execute a next recommended action for a user based on the user's audio input. In an embodiment, the system is configured to receive audio input from the user and convert the audio input into a string. The system may identify an attribute associated with the user. The system may identify a type of action based on the string. The system may query a data repository using the attribute associated with the user to retrieve information associated with the type of action. The system may identify a recommended action for the user based on the information associated with the type of action. The system may then execute the recommended action for the user.

Abstract: A method of route planning for an electric vehicle includes obtaining waypoint data that indicates waypoint locations for the electric vehicle. The method also includes generating a map and a plurality of route segments to connect each of the waypoint locations on the map. Further, the method includes calculating an optimal route for the electric vehicle to visit each of the waypoint locations by evaluating the plurality of route segments. In response to detecting changes occurring in conditions associated with each of the plurality of route segments, the method includes recalculating the optimal route for the electric vehicle.

Abstract: Embodiments provide computer apparatuses, computer systems and computer-executable methods for recommending a commercial item or entity to a consumer based on geographic zone data. The method includes receiving a first predetermined geographic zone, a first importance score associated with a consumer for the first predetermined geographic zone, and a second importance score associated with a commercial item or entity for the first predetermined geographic zone. The method also includes programmatically generating an overlap score based on the first and second importance scores, and programmatically generating a relevancy score based on the overlap score, the relevancy score indicating a probability that the commercial item or entity is of relevance to the consumer. The method further includes, based on the relevancy score, transmitting instructions to a computing device associated with the consumer to cause the computing device to render a representation of the commercial item or entity.

Abstract: A pothole monitoring and repair system for a road surface includes at least one UAV which includes a video camera, a video processor, a computing unit and a global positioning receiver. The UAV generates video streams of road surfaces using the video camera which are processed by the video processor to extract road frames. The computing unit generates a geo-fenced area of the road surface, and determines whether there is at least one pothole in each of the road frames within the geo-fenced area. The cloud server generates a map of the geo-fenced area, labels location coordinates of each pothole on the map, identifies and labels geographical features in the road frames within the geo-fenced area, extracts pothole features in the road frames, and uses a classifier to predict repair actions based on pothole features and geographical features, which are presented on a front end interface.

Abstract: Method, system for presenting an object on a computing device. A metaphor application on a computing device organizes a user interface based upon a metaphor. The metaphor organizes a document, file, application, or combination thereof based on geospheric direction, geolocation, or both. The metaphor may also organize a document, file, application, data, or a combination thereof based on a solid geometrical figure in three-dimensional Euclidean space. A document, file, application, or any combination thereof may be associated with geophysical direction, a geolocation, or both. The document, file, application, data, or any combination thereof may further be associated with a solid geometrical figure. A presentation object containing data on the document, file, application, data, or combination thereof, and the geospheric direction, geolocation, or both is formatted into data blocks for rendering on a display. The display may be the display screen of the computing device.

Abstract: A method and system of constructing a network map from imagery comprising using an iterative search process guided by a CNN-based decision function to derive a network graph directly from the output of the CNN.

Abstract: The disclosure generally pertains to recommending an alternative off-road track to a driver of a vehicle. In an example method, a processor receives a sensor signal that is generated in response to an operating condition of the vehicle on an off-road track. The operating condition can include, for example, an angular orientation of a chassis portion of the vehicle with respect to a ground surface (yaw, pitch, roll, etc.), steering characteristics, speed characteristics, and/or braking characteristics. The processor evaluates the sensor signal to identify an attribute of the off-road track, such as, for example, a difficulty factor and/or a challenge level. The processor may assign a track score to the off-road track based on the attribute and may provide to the driver, a recommendation for use of another off-road track based on comparing the first track score to a second track score associated with the other off-road track.

Abstract: A navigation system can identify locations of interest at a route destination. Those locations of interest at the destination can fall within a predetermined distance of the destination or those that are responsive to a query that includes the destination as a parameter. The navigation system can receive a selection of an identified location of interest near the destination, and update a route to terminate at the identified location of interest rather than the original destination. Information identifying the origin and destination for the route can be collected at a first user device and the route can be displayed at a second user device. Additional information is then received from the first user device (such as a selection of an identified location of interest near the destination). This additional information received at the first user device is used to update the route that is displayed on the second user device.

Abstract: A navigation system can identify locations of interest at a route destination. Those locations of interest at the destination can fall within a predetermined distance of the destination or those that are responsive to a query that includes the destination as a parameter. The navigation system can receive a selection of an identified location of interest near the destination, and update a route to terminate at the identified location of interest rather than the original destination. Information identifying the origin and destination for the route can be collected at a first user device and the route can be displayed at a second user device. Additional information is then received from the first user device (such as a selection of an identified location of interest near the destination). This additional information received at the first user device is used to update the route that is displayed on the second user device.

Abstract: Systems and methods for multi-modal trips. Systems and methods are provided for integrating multiple legs of a trip using different modes of transportation into a single, personalized transportation experience. In particular, systems and methods are provided for integrating multiple modes of transportation, such as an electric scooter ride and an autonomous vehicle ride, into a single trip.

Abstract: This document describes vehicle localization using map and vision data. For example, this document describes a localization system that obtains a map centerline point and a vision centerline point of a lane of a roadway. The localization system also obtains the position of the vehicle. The localization system can then compare the map centerline point and the vision centerline point to generate a lateral and a longitudinal correction relative to the vehicle's position. The lateral and longitudinal corrections are used to generate a corrected position. In this way, the described localization system can provide accurate vehicle localization that addresses potential drift caused by lapsed or inaccurate positioning data and allows for the operation of assisted-driving and autonomous-driving systems at higher speeds and on roadways with tighter curves.

Abstract: Implementations are directed to causing a voice bot to utilize a plurality of ML layers in resolving unique personal identifier(s) for a human while the voice bot is engaged in a corresponding conversation with the human. The unique personal identifier(s) can include a unique sequence of alphanumeric characters that is personal to the human. In some implementations, ASR speech hypothes(es) corresponding to spoken utterance(s) that include the unique personal identifier(s) can be processed to generate candidate unique personal identifier(s), given alphanumeric character(s) of the candidate unique personal identifier(s) can be selected, and the voice bot can prompt the human with clarification request(s) to clarify the given alphanumeric character(s) until it is predicted to correspond to the an actual unique personal identifier(s) for the human(s). The unique personal identifier(s) can then be utilized in performance of further action(s) by the voice bot and/or other systems.

Abstract: The present disclosure provides methods, devices and systems for route deviation quantification and vehicular route learning based thereon. In some examples, there is provided a method for route deviation quantification of a suggested route. The method comprises: obtaining a ground truth route based on a filtered trajectory, the filtered trajectory including an inferred location of origin and an inferred location of destination; obtaining a suggested route generated based on the inferred location of origin and the inferred location of destination; quantifying a deviation of the suggested route from the ground truth route by calculating an off course ratio based on a combined length of road segments in the suggested route that are matched to corresponding road segments in the ground truth route and a combined length of road segments in the ground truth route.

Abstract: The embodiments disclosed herein relate to concurrently displaying maps visualizing different subsets of transportation planning data. The concurrently displayed maps are automatically updated based on changes to the transportation planning data. A map locking functionality prevents the locked map from being updated based on changes to the transportation planning data. Other non-locked maps continue to be updated based on the changes to the transportation planning data. The map locking functionality allows for visualizing and comparing different states of the transportation planning data.

Abstract: An online shopping concierge system sorts a list of items to be picked in a warehouse by receiving data identifying a warehouse and items to be picked by a picker in the warehouse. The system retrieves a machine-learned model that predicts a next item of a picking sequence of items. The model was trained, using machine-learning, based on sets of data that each include a list of picked items, an identification of a warehouse from which the items were picked, and a sequence in which the items were picked. The system identifies an item to pick first and a plurality of remaining items. The system predicts, using the model, a next item to be picked based on the remaining items, the first item, and the warehouse. The system transmits data identifying the first item and the predicted next item to be picked to the picker in the warehouse.

Abstract: A system can autonomously or semi-autonomously guide a driver to a dock or parking location. The system can include a sensor or sensors that collect data to create a map of the dock or parking location, a user interface that allows the driver to select a dock or a feature in the map and to determine the final pose of the tractor and trailer, and a planner that creates a kinematically-correct and obstacle-free trajectory from the current location to the dock or parking location. The system can provide user aids, such as a ground guide avatar or avatars, that provide the distance to the dock, speed and turning directions, or other guidance.

Abstract: A method creates a reduced set of feasible transfers T(t, L?) for a trip t of line L, for each target line L? from a set of all transfers from line L to all other lines, by computing, for each origin line L, feasible transfers between stations of the origin line L and a destination line L?; sorting the computed feasible transfers to create a transfer set T(L); determining, for each trip t of origin line L, and for each transfer in the transfer set T(L), an earliest trip t? of L? wherein the transfer is feasible; and adding, for each trip t of origin line L, the determined transfer from t to t? to the reduced set of feasible transfers T(t, L?) when trip t? is the only destination trip of the transfers in the reduced set of feasible transfers T(t, L?) passing at the destination station and when it is earlier than all the previous destination trips of the transfers in the reduced set of feasible transfers T(t, L?) passing by the destination station.

Abstract: A system for vehicle navigation may include a processor including a circuitry and a memory. The memory may include instructions that when executed by the circuitry cause the processor to receive navigational information associated with the vehicle including an indicator of a location of the vehicle, and determine target navigational map segments to retrieve from a map database. The map database may include stored navigational map segments each corresponding to a real-world area. The determination of the target navigational map segments may be based on the indicator of vehicle location and on map segment connectivity information associated with the stored navigational map segments. The instructions may also cause the processor to initiate downloading of the target navigational map segments from the map database, and cause the vehicle to navigate along a target trajectory included in one or more of the target navigational map segments downloaded from the map database.

Abstract: Provided are an automatic parking control method and apparatus, relating to the industrial field of vehicles. The method comprises: when a speed of a vehicle is in a preset speed range and a time that the speed of the vehicle is in the preset speed range is greater than or equal to a preset time, collecting image data and radar data around the vehicle; inputting the image data and the radar data into a preset convolutional neural network model, and outputting at least one parking slot information; selecting target parking slot information according to a received parking-in selection operation; and according to the target parking slot information, generating a vehicle parking-in track for the vehicle to automatically park according to the vehicle parking-in track.

Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.

Abstract: A vehicle routing device that determines a route from an origin to a destination including route guidance. The route guidance is modified based on user input. The modification can supply increased or reduced route guidance at intervals along the route. Route guidance may be modified to incorporate landmarks and personal contacts.

Abstract: The present disclosure discloses a method for route optimization based on dynamic window and redundant node filtering, comprising using an existing raster map data set to determine the coordinate information of a starting position and a destination position of movement, and to mark a destination node and an obstacle node in the raster map; using A* algorithm to plan a global route; globally optimizing the global route planned by A* algorithm, and filtering redundant nodes out; combining a dynamic window algorithm to perform the local optimization section by section on the optimized global route so as to obtain a final global route. According to the present disclosure, the combination of algorithms reduces a single movement duration of a mobile robot and improves the smoothness of the movement route curve. At the same time, the problems of the robot occurring on the route during the static driving are alleviated.