Abstract: This disclosure generally relates to a method and system for requesting a ride for a third party rider. In one embodiment, a user device may be used to transmit a ride request to a server for a third party rider. The user device may receive an indication of a driver from a set of trusted drivers among a pool of drivers. Further, the user device and a device associated with the third party user may receive a ride confirmation.

Abstract: An autonomous vehicle (AV) planning method comprises: receiving sensor inputs pertaining to an AV; processing the AV sensor inputs to determine an encountered driving scenario; in an AV planner, executing a tree search algorithm to determine a sequence of AV manoeuvres corresponding to a path through a constructed game tree; and generating AV control signals for executing the determined sequence of AV manoeuvres; wherein the game tree has a plurality of nodes representing anticipated states of the encountered driving scenario, and the anticipated driving scenario state of each child node is determined by updating the driving scenario state of its parent node based on (i) a candidate AV manoeuvre and (ii) an anticipated behaviour of at least one external agent in the encountered driving scenario.

Abstract: Aspects of the disclosure relate to a system and method for electronically monitoring and using data indicative of driver characteristics based on sensors. For example, the system may determine an origin associated with a user, a destination associated with the user, and a desired arrival time at the destination. A driving characteristic computing device of the system may determine an estimate for a duration of a trip from the origin to the destination. Based on the estimate for the duration and the desired arrival time at the destination, the driving characteristic computing device may determine a recommended departure time from the origin for the user. Based on sensor data, the system may determine a departure time from the origin for the user. The driving characteristic computing device may compare the departure time to the recommended departure time, and a value of a property of insurance for the user may be determined based on the comparing.

Abstract: Disclosed embodiments include systems, vehicles, and methods for receiving inputs indicative of a destination and a potential intermediate destination and determining a time potentially available at the intermediate destination. In an illustrative embodiment, a system includes a computing device having computer-readable media storing computer-executable instructions configured to cause the computing device to receive a first input indicative of a destination. A second input is received that is indicative of a desired arrival time at the destination. A third input is received that is indicative of an intermediate destination to be visited before traveling to the destination. A first travel time to the intermediate destination, a second travel time to the destination, and a time available at the intermediate destination are determined. The time available at the intermediate destination is communicated to a user.

Abstract: According to an aspect of the present disclosure, provided is a shared vehicle service providing method based on a shared vehicle management server communicating with a shared vehicle and a user device. Also provided is a shared vehicle service providing method for managing an article of a shared vehicle user on the basis of a shared vehicle management server. More specifically, provided is a shared vehicle service providing method in which a shared vehicle management server manages dispatch of a shared vehicle and an article of a user on the basis of data acquired from the shared vehicle and a user device.

Abstract: A vehicle determines that a stop is upcoming along a route and determines that the upcoming stop will place the vehicle within range of a wireless transceiver. The vehicle approximates a predicted transfer rate of the wireless transceiver and determines if data onboard the first vehicle is to be uploaded, based on at least a size of the data, a priority assigned to the data and the predicted transfer rate. Additionally, the vehicle determines a predicted duration of communication between the vehicle and the transceiver based on the route and the upcoming stop, allowing the vehicle to determine a first predicted amount of data able to be transferred. The vehicle designates first data for upload, based on the first data having a size that is below the first predicted amount and begins transferring the designated data responsive to establishing communication with the wireless transceiver.

Abstract: Examples of service call-ahead systems and methods are disclosed. In one example implementation according to aspects of the present disclosure, a service order management system includes a processing device, a servicer device, and a memory device. The service order management system is enabled at least to prompt a servicer to modify an initial estimated time of arrival (ETA) and notify a customer of the modified ETA of a servicer at a service destination. Prompting the servicer to modify the initial ETA enables the processing device to notify the customer of the modified ETA, which is more accurate than the initial ETA. Other service call-ahead and notification techniques are also disclosed.

Abstract: Aspects of the present disclosure relate to a vehicle for maneuvering a passenger to a destination autonomously. The vehicle includes one or more computing devices that receive a request for a vehicle from a client computing device. The request identifies a first location. The one or more computing devices also determine whether the first location is within a threshold outside of a service area of the vehicle. When the location is within the threshold distance outside of the service area of the vehicle, the one or more computing devices identify a second location within the service area of the vehicle where the vehicle is able to stop for a passenger and based on the first location. The one or more computing devices then provide a map and a marker identifying the position of the second location on the map for display on the client computing device.

Abstract: In one embodiment, a method comprises determining, based on one or more metrics indicative of passenger demand and driver supply associated with a transportation service, to send a first minimum fare offer to a first driver, the first minimum fare offer specifying a first minimum amount of compensation to be provided to the first driver for a first time period; tracking compensation accrued by the first driver during the first time period for servicing at least one ride for the transportation service; and determining compensation for the driver for the first time period, wherein the determined compensation is the greater of the first minimum amount of compensation specified in the first minimum fare offer and the tracked compensation accrued by the first driver during the first time period for servicing the at least one ride for the transportation service.

Abstract: A system (100) and method for finding a likely available parking spot within a geographical area are disclosed. The system (100) may be configured to receive a request for directions for a first vehicle (702) to an open parking spot within a particular geographical area (210, 214), receive sensor information indicating potential open parking spots (346, 348), identify likely available parking spots (346, 348), and receive information regarding other vehicles searching for parking in the same geographical area. The system may use the identified likely available spots and the information regarding other vehicles searching for parking when computing a route (218, 220) to a likely available parking spot.

Abstract: Provided is an estimating system including: at least one memory configured to store computer program code; and at least one processor configured to access said at least one memory and operate according to said computer program code, said computer program code including: via point acquisition code configured to cause the at least one processor to acquire a position of a via point, wherein the route is a path followed by a mobile object when the mobile object moves toward a destination; staying time period code configured to cause the at least one processor to estimate, based on the position of the via point, a staying time period; and arrival time code configured to cause the at least one processor to estimate, by including the staying time period, an arrival time of the mobile object at the destination.

Abstract: Systems and methods related to ridesharing may involve receiving a ride request from a user including a desired destination and information associated with a current location of the user, and receive location information of on-demand and of fixed-line ridesharing vehicles and based on the received location information, identify a fixed-line ridesharing vehicle available to pick from a first pick-up location identify an on-demand ridesharing vehicle available to pick from a second pick-up location, both locations other than the current location of the user, determine a first value and a second value indicative of a time duration for the fixed-line and one demand ridesharing vehicles to arrive at the first and second pick-up locations, respectively, and when the first value is less than the second value, inform the user that the fixed-line ridesharing vehicle is enroute and direct the user to the first pick-up location.

Abstract: An information processing apparatus according to an embodiment includes an acquisition unit, an estimation unit, and a provision unit. The acquisition unit acquires stop information concerning a situation of a stop of a user at a facility on a route from a place of departure to a place of destination. The estimation unit estimates an amount of time required to the place of destination, based on the stop information that is acquired by the acquisition unit. The provision unit provides a content that is based on the amount of time required that is estimated by the estimation unit.

Abstract: Example embodiments described herein therefore relate to an AR guidance system to perform operations that include: detecting a client device at a location within a geo-fenced area, wherein the geo-fenced area may include within it, a destination of interest; determining a route to the destination of interest from the location of the client device within the geo-fenced area; causing display of a presentation of an environment within an AR interface at the client device; detecting a display of real-world signage within the presentation of the environment; generating a media item in response to the detecting the display of the signage within the presentation of the environment, wherein the media item is based on the route to the destination of interest; and causing display of the media item within the AR interface based on the position of the signage within the presentation of the environment.

Abstract: A robot according to an embodiment of the present disclosure includes an authentication interface for authenticating a user's boarding of the robot using authentication information of the user, a position detector for detecting a position of the robot in a space, a processor for identifying a first section corresponding to the detected position among at least one section in the space, recognizing at least one driving mode for the first section among a plurality of driving modes with different driving speeds, setting one of the recognized at least one driving mode as a driving mode for the first section based on the authentication information, and controlling driving of the robot based on the set driving mode, and a display for outputting information on the set driving mode.

Abstract: This disclosure relates generally to a method and system for dynamically predicting vehicle arrival time using a temporal difference learning technique. Due to varying uncertainties predicting vehicle arrival time and travel time are crucial elements to make the public transport travel more attractive and reliable with increased traffic volumes. The method includes receiving a plurality of inputs in real time and then extracting a plurality of temporal events from a closest candidate trip pattern using a historical database. Further, a trained temporal difference predictor model (TTDPM) is utilized for dynamically predicting the arrival time from the current location of the vehicle to the target destination based on the plurality of nonlinear features. The non-linear features and linear approximator formulation of TTDPM provides fast gradient computation improves training time.

Abstract: A system and method of augmenting a delivery route. The method comprises receiving first location information from a first position device and receiving second location information from a second position device. The method further comprises storing the first and second location information in a memory structure and determining, based on at least one of the first and second information, a time and a location for each of a plurality of stops. The method also comprises reconciling the determined time and location of each of the plurality of stops with a stored route comprising a plurality of stored stops, the stored stops having a stored location and a stored time associated therewith and estimating a plurality of transition times between pairs of the plurality of stops.

Abstract: Disclosed embodiments include systems, vehicles, and methods for receiving inputs indicative of a destination and a potential intermediate destination and determining a time potentially available at the intermediate destination. In an illustrative embodiment, a system includes a computing device having computer-readable media storing computer-executable instructions configured to cause the computing device to receive a first input indicative of a destination. A second input is received that is indicative of a desired arrival time at the destination. A third input is received that is indicative of an intermediate destination to be visited before traveling to the destination. A first travel time to the intermediate destination, a second travel time to the destination, and a time available at the intermediate destination are determined. The time available at the intermediate destination is communicated to a user.

Abstract: A system for navigation and ride hailing that provides options for navigating traffic through express lanes or the like. Information, such as express lane profile information, toll price information for the express lane during a period, and traffic information along one or more paths may be used to determine the fastest options along to a destination at different toll price points.

Abstract: A method for prediction model determination can include: determining a set of models, training each model, determining package transit data, evaluating the set of models, selecting a model from the set of models, predicting package transit data using the selected model, and/or any other suitable element.

Abstract: An electronic apparatus includes a wireless communication section that performs wireless communication through an external access point, a processing section that performs communication control of the wireless communication section, and a storage section. The storage section stores, in association with each other, terminal identification information for identifying the terminal device that performed wireless communication through the first access point and identification information for identifying the first access point. The wireless communication section performs a packet capturing process. The processing section determines, based on a capturing result, the identification information of the first access point, and the terminal identification information of the terminal device, whether switching from the first access point is performed.

Abstract: A method, including providing a device for an individual, storing information regarding a travel schedule or itinerary of the individual, determining a location of the device with a global positioning device, automatically and continuously monitoring the location of the device, comparing the location of the device with the travel schedule or itinerary, detecting a deviation of the device from a travel schedule or itinerary, or detecting an absence of, or a leaving of, the device from an expected location on the travel schedule or itinerary, generating a travel route deviation message and transmitting the travel route deviation message to a first communication device.

Abstract: An example method includes: receiving information indicative of a desired aircraft cruise insertion point comprising achieving a desired cruise altitude for an aircraft within a predetermined period of time from departure, or within a predetermined distance from departure; determining a desired airspeed for the aircraft; prior to a flight of the aircraft, determining, based on the desired airspeed and the desired aircraft cruise insertion point, a climb trajectory for the aircraft; and during a climb flight phase of the aircraft, varying climb thrust of an engine of the aircraft to follow the climb trajectory and achieve the desired aircraft cruise insertion point.

Abstract: Techniques described herein may be used to conserver battery power of an Internet of Things (IoT) tracker by increasing the overall amount of time that the IoT tracker is in a battery conservation mode (a sleep mode, a Power Save Mode (PSM), etc.). An IoT tracker may implement a battery conservation policy that may include instructions that cause the IoT tracker to monitor certain conditions, determine when the conditions satisfy a particular trigger, and implement a battery conservation mode in response to those conditions. Examples of such conditions may include (1) the IoT tracker being close to a user device designated to track the location of the IoT tracker, (2) identifying that a current time and day are associated with a pre-selected schedule for disabling tracking services, (3) the IoT tracker being located within a particular geographic area, and more.

Abstract: In one aspect, a computerized method for using machine learning methods for modeling for time in traffic for a vehicle on a delivery route includes the step of collecting a set of traffic feature values from a database. The method includes the step of normalizing the set of traffic feature values. The method includes the step of providing a machine learning model. The method includes the step of inputting the set of normalized traffic features into the machine learning model. The method includes the step of training the machine learning model with the set of normalized traffic features. The method includes the step of determining a target time for the vehicle on the delivery route.

Abstract: Disclosed are systems and methods relating to providing intersection metrics based on telematic data.

Abstract: Method and apparatus for flight path information reporting are disclosed. One method of UE such as aerial vehicles for flight path information reporting includes determining whether current flight path information is changed comparing with planned flight path information; and transmitting a report including the current flight path information to a network equipment such as eNB. The method contributes to improve mobility performance of the aerial vehicles by timely communicating the current flight path information.

Abstract: Systems, methods, and apparatuses described herein relate to a method for providing authentication with respect to a cash delivery request made by a customer using a customer user device of the customer. The method includes receiving at least one of security information or a first cash authentication code (CAC) from a cash dispenser machine. The cash dispenser machine obtains the security information or the first CAC from a first user device of a driver or the driver. The method includes authenticating the driver based on at least one of the security information or the first CAC. The method includes generating a second CAC. The method includes transmitting the second CAC to the first user device of the driver. The method includes authenticating the driver and the customer based on at least one of the security information or the second CAC.

Abstract: Aspects of the disclosure provide for advanced trip planning for an autonomous vehicle service. For instance, an example method may include determining a potential pickup location for a user, determining a set of potential destination locations for a user, and determining a set of potential trips. For each potential trip a vehicle of a fleet of autonomous vehicles of the service may be assigned and trip information, including an estimated time of arrival for the assigned vehicle of the potential trip to reach the destination location of the potential trip, may be determined. The trip information for each potential trip may be provided for display to the user. Thereafter, confirmation information identifying one of the set of potential trips may be received, and the assigned vehicle for one first of the set of potential trips may be dispatched to pick up the user.

Abstract: Technologies are disclosed for interacting with a virtual assistant to coordinate, recommend and perform actions. According to some examples, a user may use their voice to interact with a virtual assistant to receive recommendations relating to determining when to perform one or more actions. For example, a user may interact with a virtual assistant to request a recommendation as to when they should leave for the office, leave the office for the day, perform a task, and the like. The recommendation system accesses selected data sources (e.g., calendars, task lists, traffic, transportation schedules, maps, . . . ) to obtain data used in generating the recommendation. In addition, to providing a recommended time, the virtual assistant may also recommend actions to perform. The virtual assistant may also provide notifications to one or more other users that includes information relating to the user leaving.

Abstract: A system for operating an automated-taxi includes an input-device and a controller-circuit. The input-device is operable by a client to indicate a desired-destination of the client. The display is viewable by the client. The controller-circuit is in communication with the input-device and the display. The controller-circuit is configured determine a preferred-route in accordance with the desired-destination and a plurality of other-destinations indicated by a plurality of other-clients of an automated-taxi. The preferred-route includes an alternate-destination for the client. The alternate-destination characterized as within a distance-threshold of the desired-destination of the client. The controller-circuit is further configured to operate the display to request a route-approval from the client for the alternate-destination, and, in response to receiving the route-approval, operate the automated-taxi in accordance with the preferred-route to transport the client to the alternate-destination.

Abstract: This disclosure generally relates to a method and system for requesting a ride for a third party rider. In one embodiment, a user device may be used to transmit a ride request to a server for a third party rider. The user device may receive an indication of a driver from a set of trusted drivers among a pool of drivers. Further, the user device and a device associated with the third party user may receive a ride confirmation.

Abstract: According to an aspect of the present disclosure, provided is a shared vehicle service providing method based on a shared vehicle management server communicating with a shared vehicle and a user device. Also provided is a shared vehicle service providing method for managing an article of a shared vehicle user on the basis of a shared vehicle management server. More specifically, provided is a shared vehicle service providing method in which a shared vehicle management server manages dispatch of a shared vehicle and an article of a user on the basis of data acquired from the shared vehicle and a user device.

Abstract: An information processing device is installed in a vehicle and comprises an action history DB which stores a plurality of action histories including a combination of a content that was played based on an instruction of a user and a situation in which the content was played, and an automatic playing unit which, when a current elapsed time as an elapsed time from a time that an ignition switch of the vehicle was most recently turned ON or a current travel distance as a travel distance from a time that an ignition switch of the vehicle was most recently turned ON matches any one of the action histories of the action history DB, plays a content included in the matching action history.

Abstract: Systems and methods are disclosed for the development and management of curated navigational routes are disclosed. The curated navigational route can be a particular path of travel that is specifically designed for one or more users. The curated navigational routes are carefully constructed paths of travel that are custom defined by a route manager.

Abstract: This disclosure generally relates to a method and system for scheduling a ride for a third party by a ride requestor. In one embodiment, the method includes receiving a ride request for a third party rider from a user device. The method may further include identifying a set of drivers from a trusted drivers and identifying from the set of trusted drivers, an optimal driver. The method may further include transmitting a ride confirmation to the ride requestor, the optimal driver, and the third party rider.

Abstract: The present disclosure relates to a system and a method of allocating orders. The system may include a non-transitory computer readable storage medium and a processor. The non-transitory computer may store an executable module. The processor may execute the executable module stored in the computer readable storage medium. The non-transitory computer readable storage medium may include a receiving unit (231) and an order allocation unit (361). The receiving unit (231) may receive order information and user information. The user information may include location information and/or time information. The order allocation unit (361) may allocate an order based on the location information and/or the time information. The method may include receiving order information and user information, wherein the order information and the user information may include location information and/or time information, and allocating an order based on the location information and/or the time information.

Abstract: An information processing apparatus according to the present application includes an acquiring unit and a notification unit. The acquiring unit acquires riding position information related to a position of a virtual riding point that corresponds to a riding point that is used to ride in a moving vehicle and that is virtual set. The notification unit notifies, when a user satisfies condition information that indicates a condition related to behavior of the user approaching the virtual riding point, the user of the information related to the position indicated by the riding position information.

Abstract: A method includes capturing images at a device and analyzing the images at the device using a first analysis model to obtain information regarding an observed object that corresponds to a predetermined object. The method also includes determining whether the information regarding the observed object is consistent with stored mapping information, and, in response to determining that the information regarding the observed object is not consistent with the stored mapping information, modifying the stored mapping information based on the observed object.

Abstract: A system for providing dynamic roadside assistance coordination may include a customer mobile device or vehicle in direct, or indirect, wireless communication with an insurance provider and/or service provider remote server. The customer's device may transmit a request for roadside assistance (e.g., towing services), and a current GPS location. In response, a closest, trusted service provider vehicle may be determined, and then directed to the customer's location. For instance, a software application may receive the customer location and compare it with availability information to match the customer with a close and trusted service provider. The customer's device may receive an acknowledgement that help is on the way, and be able to track the current location of the service provider vehicle while en route. Payment for the roadside assistance may be automatically and electronically paid by the insurance provider. As a result, prompt and safe roadside assistance may be provided.

Abstract: A customer offset may be determined with respect to a customer who has previously traveled to one or more merchant locations. A merchant location offset may be determined with respect to multiple customers who have each traveled to a particular merchant location. Upon determining that the customer is in transit to the merchant location, a generic ETA to the merchant location may be determined. A customer-based ETA for the customer with respect to the merchant location may be determined based on the generic ETA and the customer offset. Moreover, a merchant location-based ETA for the customer with respect to the merchant location may be determined based on the generic ETA and the merchant location offset. Based on the refined and more accurate ETAs, the merchant location may be instructed to begin assembling items for pick-up by the customer.

Abstract: Systems, Methods and Apparatuses are provided to control actuation of an autonomous operating mode feature of a vehicle to operate when the vehicle is on a limited access freeway. The elevated freeway detection system includes: receiving, by an evaluation module, a plurality of data in real-time about the vehicle including: mapping, GPS and radar data of the vehicle to provide at least a current vehicle location and image data to capture surroundings of the vehicle; determining, whether the vehicle is mapped on a limited access freeway by computing a matching probability location data of the vehicle to the limited access roadway based on the map data, radar data and GPS data; and sending a signal to inhibit the autonomous feature from engaging in the vehicle when the vehicle is not on the limited access freeway.

Abstract: An information processing apparatus according to the present application includes an acquiring unit and a notification unit. The acquiring unit acquires riding position information related to a position of a virtual riding point that corresponds to a riding point that is used to ride in a moving vehicle and that is virtual set. The notification unit notifies, when a user satisfies condition information that indicates a condition related to behavior of the user approaching the virtual riding point, the user of the information related to the position indicated by the riding position information.

Abstract: A shipment system can coordinate a less-than-truckload shipment with one or more freight vehicles by receiving from a first computing device, data corresponding to a new less-than-truckload shipment request. The data can comprise a pickup location, a delivery location, a pickup time, and a delivery time. Additionally, the shipment system can identify, from accessing a database, one or more trucks that are assigned to a current less-than-truckload shipment and are capable of executing the new less-than truckload shipment while completing the respective current-less-than-truckload shipment. A message corresponding to an invitation for executing the new less-than-truckload shipment can be transmitted to one or more operator computing devices of the identified one or more trucks capable.

Abstract: A network system, such as a transport management system, efficiently allocates resources by monitoring the geospatial and topological locations of a rider responsive to receiving a trip request. A trip management module matches a rider with an available driver based in part on an comparison of the estimated times of arrival of the rider and the driver at the pickup location. A client positioning module monitors the rider's progress through nodes and edges in a topological graph associated with the origin location based on radio signatures received at the rider client device. A client ETA module calculates a rider ETA based on the rider's rate of travel through the origin location represented by nodes in the topological graph. Responsive to determining that the rider ETA and the driver ETA vary by over a threshold amount of time, the trip management module matches the rider with a second available driver.

Abstract: One example of determining an estimated time of arrival (ETA) based on calibrated distance includes a method implemented by a processor included in a mobile device to be carried by a user. An estimated distance between a starting location and an ending location is received. A calibration factor based on a location of the mobile device on the user's body and a movement pace of the user is determined. The estimated distance between the starting location and the ending location is modified based, in part, on the determined calibration factor resulting in a modified estimated distance. An estimated time to arrive (ETA) at the ending location is determined based, in part, on the modified estimated distance.

Abstract: A method, a system, and a computer program product are provided. At least one processor of a computing device determines that a mobile device remained in a vehicle used in a vehicle for hire service after the vehicle reached a destination. The at least one processor determines at least one second party to notify regarding the mobile device being left in the vehicle based on a use of the vehicle for hire service by a user of the mobile device and the at least one second party. The at least one processor notifies the at least one second party regarding the mobile device being left in the vehicle via at least one device used by the at least one second party.

Abstract: Implementations are directed to providing a semantic sequence based on a sequence associated with the event, and context data provided from a knowledge graph, receiving a set of cases associated with at least one entity included in the event, the set of cases including previous instances of events, and actions performed to resolve the previous instances of events, defining a sub-set of cases from the set of cases based on the context data, for each case of the sub-set of cases, determining a similarity score, each similarity score representing a degree of similarity between the event, and a case of the sub-set of cases, determining an explanation based on features of cases in the sub-set of cases based on the context data, and providing one or more actions based on actions of cases in the sub-set of cases.

Abstract: A system and method efficiently computes travel times between an origin and destination, minimizing expensive calls to a third party service by first geographically expanding both origin and destination and then searching a cache of previously computed or obtained travel times for any route satisfying the expanded origin and destination. A further embodiment concerns a system and method to prepare an optimized routing sequence to travel to a set of geographical task sites, in satisfaction of applicable conditions for one or more of the task sites. Advantageously, optimized routing may employ the disclosed method of computing travel times between origin and destination.

Abstract: Techniques described herein may be used to conserver battery power of an Internet of Things (IoT) tracker by increasing the overall amount of time that the IoT tracker is in a battery conservation mode (a sleep mode, a Power Save Mode (PSM), etc.). A IoT tracker may implement a battery conservation policy that may include instructions that cause the IoT tracker to monitor certain conditions, determine when the conditions satisfy a particular trigger, and implement a battery conservation mode in response to those conditions. Examples of such conditions may include (1) the IoT tracker being close to a user device designated to track the location of the IoT tracker, (2) identifying that a current time and day are associated with a pre-selected schedule for disabling tracking services, (3) the IoT tracker being located within a particular geographic area, and more.