Abstract: A network system, such as a transport management system, infers movement and a location of a vehicle associated with a transportation service using sensor data from a provider client device and a wireless device mounted in a fixed position in the vehicle. Before or during a transportation service, the provider client device transmits sensor data to the network system for use in detecting the occurrence of one or more specified events, such as a sudden deceleration or a harsh turn. The network system fuses the received sensor data to infer the movement of the vehicle along forward, lateral, and vertical axes and implements an event detector by analyzing movement of the vehicle in the forward direction. Fused sensor data received from the wireless device is used to validate the detected movement and to determine a position of the vehicle.

Abstract: A network system, such as a transport management system, infers movement and a location of a vehicle associated with a transportation service using sensor data from a provider client device and a wireless device mounted in a fixed position in the vehicle. Before or during a transportation service, the provider client device transmits sensor data to the network system for use in detecting the occurrence of one or more specified events, such as a sudden deceleration or a harsh turn. The network system fuses the received sensor data to infer the movement of the vehicle along forward, lateral, and vertical axes and implements an event detector by analyzing movement of the vehicle in the forward direction. Fused sensor data received from the wireless device is used to validate the detected movement and to determine a position of the vehicle.

Abstract: Cascaded, boosted predictive models trained using distinct sets of exogenous and endogenous features are configured to predict component of performance ratings of entities. From the distinct predicted components, the second entity's rating factor can be determined. A second entity's rating factor represents the specific contribution a second entity makes to his average performance rating, as distinct from the rating that an arbitrary or hypothetical second entity would obtain.

Abstract: A network system, such as a transport management system, selects a pickup location for a trip and navigates a rider to the selected pickup location using augmented reality (AR). Responsive to receiving a trip request including an origin location, a pickup location selection module selects candidate pickup locations within a threshold distance of the rider client device. The pickup location selection module filters and ranks the candidates based on historical service data and location characteristics associated with the origin location as well as any history of pickups of the rider at the origin location and data from the trip request. The top-ranked candidate is selected as the pickup location and sent to the rider and driver client devices. An AR navigation module instructs the rider client device to visually augment a live video stream with computer-generated AR elements to navigate the rider from a current location to the pickup location.

Abstract: A network system, such as a transport management system, uses augmented reality (AR) to identify an approaching vehicle. Responsive to receiving a trip request, a trip management module matches the rider with an available driver and instructs a trip monitoring module to monitor the location of the driver's vehicle as it travels to the pickup location. When the driver's vehicle is within a threshold distance of the pickup location, an AR control module instructs the rider client device to begin a live video stream and instructs an image recognition module to monitor the video stream for the driver's vehicle. Responsive to the driver's vehicle entering the field of view of the camera on the rider client device, the AR control module selects computer-generated AR elements and instructs the rider client device to visually augment the video stream to identify the driver's vehicle as it approaches the pickup location.

Abstract: A network system, such as a transport management system, selects a pickup location for a trip and navigates a rider to the selected pickup location using augmented reality (AR). Responsive to receiving a trip request including an origin location, a pickup location selection module selects candidate pickup locations within a threshold distance of the rider client device. The pickup location selection module filters and ranks the candidates based on historical service data and location characteristics associated with the origin location as well as any history of pickups of the rider at the origin location and data from the trip request. The top-ranked candidate is selected as the pickup location and sent to the rider and driver client devices. An AR navigation module instructs the rider client device to visually augment a live video stream with computer-generated AR elements to navigate the rider from a current location to the pickup location.

Abstract: A network system, such as a transport management system, uses augmented reality (AR) to identify an approaching vehicle. Responsive to receiving a trip request, a trip management module matches the rider with an available driver and instructs a trip monitoring module to monitor the location of the driver's vehicle as it travels to the pickup location. When the driver's vehicle is within a threshold distance of the pickup location, an AR control module instructs the rider client device to begin a live video stream and instructs an image recognition module to monitor the video stream for the driver's vehicle. Responsive to the driver's vehicle entering the field of view of the camera on the rider client device, the AR control module selects computer-generated AR elements and instructs the rider client device to visually augment the video stream to identify the driver's vehicle as it approaches the pickup location.

Abstract: A network system, such as a transport management system, uses augmented reality (AR) to identify an approaching vehicle. Responsive to receiving a trip request, a trip management module matches the rider with an available driver and instructs a trip monitoring module to monitor the location of the driver's vehicle as it travels to the pickup location. When the driver's vehicle is within a threshold distance of the pickup location, an AR control module instructs the rider client device to begin a live video stream and instructs an image recognition module to monitor the video stream for the driver's vehicle. Responsive to the driver's vehicle entering the field of view of the camera on the rider client device, the AR control module selects computer-generated AR elements and instructs the rider client device to visually augment the video stream to identify the driver's vehicle as it approaches the pickup location.

Abstract: A network system, such as a transport management system, infers movement and a location of a vehicle associated with a transportation service using sensor data from a provider client device and a wireless device mounted in a fixed position in the vehicle. Before or during a transportation service, the provider client device transmits sensor data to the network system for use in detecting the occurrence of one or more specified events, such as a sudden deceleration or a harsh turn. The network system fuses the received sensor data to infer the movement of the vehicle along forward, lateral, and vertical axes and implements an event detector by analyzing movement of the vehicle in the forward direction. Fused sensor data received from the wireless device is used to validate the detected movement and to determine a position of the vehicle.

Abstract: A tracking server receives GPS data from a location tracking device located in a vehicle. The GPS data describes a path that is representative of a pathway of the vehicle used to complete a trip from a starting location to a destination location. The tracking server identifies noisy GPS data included in the received GPS data and revises a portion of path corresponding to the noisy GPS data. The tracking server may update a map database to include one or more road segments associated with the revised portion of the path. Furthermore, the tracking server may calculate a fare for the trip based on the revised path.

Abstract: A network system, such as a transport management system, selects a pickup location for a trip and navigates a rider to the selected pickup location using augmented reality (AR). Responsive to receiving a trip request including an origin location, a pickup location selection module selects candidate pickup locations within a threshold distance of the rider client device. The pickup location selection module filters and ranks the candidates based on historical service data and location characteristics associated with the origin location as well as any history of pickups of the rider at the origin location and data from the trip request. The top-ranked candidate is selected as the pickup location and sent to the rider and driver client devices. An AR navigation module instructs the rider client device to visually augment a live video stream with computer-generated AR elements to navigate the rider from a current location to the pickup location.

Abstract: A network system, such as a transport management system, selects a pickup location for a trip and navigates a rider to the selected pickup location using augmented reality (AR). Responsive to receiving a trip request including an origin location, a pickup location selection module selects candidate pickup locations within a threshold distance of the rider client device. The pickup location selection module filters and ranks the candidates based on historical service data and location characteristics associated with the origin location as well as any history of pickups of the rider at the origin location and data from the trip request. The top-ranked candidate is selected as the pickup location and sent to the rider and driver client devices. An AR navigation module instructs the rider client device to visually augment a live video stream with computer-generated AR elements to navigate the rider from a current location to the pickup location.

Abstract: A network system, such as a transport management system, uses augmented reality (AR) to identify an approaching vehicle. Responsive to receiving a trip request, a trip management module matches the rider with an available driver and instructs a trip monitoring module to monitor the location of the driver's vehicle as it travels to the pickup location. When the driver's vehicle is within a threshold distance of the pickup location, an AR control module instructs the rider client device to begin a live video stream and instructs an image recognition module to monitor the video stream for the driver's vehicle. Responsive to the driver's vehicle entering the field of view of the camera on the rider client device, the AR control module selects computer-generated AR elements and instructs the rider client device to visually augment the video stream to identify the driver's vehicle as it approaches the pickup location.

Abstract: A network system, such as a transport management system, uses augmented reality (AR) to identify an approaching vehicle. Responsive to receiving a trip request, a trip management module matches the rider with an available driver and instructs a trip monitoring module to monitor the location of the driver's vehicle as it travels to the pickup location. When the driver's vehicle is within a threshold distance of the pickup location, an AR control module instructs the rider client device to begin a live video stream and instructs an image recognition module to monitor the video stream for the driver's vehicle. Responsive to the driver's vehicle entering the field of view of the camera on the rider client device, the AR control module selects computer-generated AR elements and instructs the rider client device to visually augment the video stream to identify the driver's vehicle as it approaches the pickup location.

Abstract: Examples include a network computer system and/or service which operates to remotely monitor vehicles to detect and characterize driving actions of drivers with respect to specific road segments of a roadway, enabling driving actions performed by multiple drivers at a specific road segment to be characterized and modeled. Models can inform municipalities about potential traffic hazards or other safety challenges. Individual drivers can also be measured against the model to help understand driver performance. Validating vehicle data against baseline values can also detect spoofing of that data.

Abstract: Systems and methods for training models and using the models to detect events are provided. A networked system assembles one or more triplets using sensor data accessed from a plurality of user devices, the assembling including applying a weak label. The networked system autoencodes the one or more triplets based on a covariate to generate a disentangled embedding. A model is trained using the disentangled embedding, whereby the model is used at runtime to detect whether an event associated with the model is present. In particular, runtime sensor data from the real world is autoencoded to generate a runtime embedding, whereby the runtime sensor data comprising sensor data from at least one of a device of a user. The runtime embedding is comparted to one or more embeddings of the model, whereby a similarity in the comparing indicates the event associated with the model occurring in the real world.

Abstract: Examples include a network computer system and/or service which operates to remotely monitor vehicles to detect and characterize driving actions of drivers with respect to specific road segments of a roadway, enabling driving actions performed by multiple drivers at a specific road segment to be characterized and modeled. Models can inform municipalities about potential traffic hazards or other safety challenges. Individual drivers can also be measured against the model to help understand driver performance. Validating vehicle data against baseline values can also detect spoofing of that data.

Abstract: A network system, such as a transport management system, selects a pickup location for a trip and navigates a rider to the selected pickup location using augmented reality (AR). Responsive to receiving a trip request including an origin location, a pickup location selection module selects candidate pickup locations within a threshold distance of the rider client device. The pickup location selection module filters and ranks the candidates based on historical service data and location characteristics associated with the origin location as well as any history of pickups of the rider at the origin location and data from the trip request. The top-ranked candidate is selected as the pickup location and sent to the rider and driver client devices. An AR navigation module instructs the rider client device to visually augment a live video stream with computer-generated AR elements to navigate the rider from a current location to the pickup location.

Abstract: A network system, such as a transport management system, uses augmented reality (AR) to identify an approaching vehicle. Responsive to receiving a trip request, a trip management module matches the rider with an available driver and instructs a trip monitoring module to monitor the location of the driver's vehicle as it travels to the pickup location. When the driver's vehicle is within a threshold distance of the pickup location, an AR control module instructs the rider client device to begin a live video stream and instructs an image recognition module to monitor the video stream for the driver's vehicle. Responsive to the driver's vehicle entering the field of view of the camera on the rider client device, the AR control module selects computer-generated AR elements and instructs the rider client device to visually augment the video stream to identify the driver's vehicle as it approaches the pickup location.

Abstract: A tracking server receives GPS data from a location tracking device located in a vehicle. The GPS data describes a path that is representative of a pathway of the vehicle used to complete a trip from a starting location to a destination location. The tracking server identifies noisy GPS data included in the received GPS data and revises a portion of path corresponding to the noisy GPS data. The tracking server may update a map database to include one or more road segments associated with the revised portion of the path. Furthermore, the tracking server may calculate a fare for the trip based on the revised path.