Abstract:
Methods, computer-readable media, software, and system may generally build and quantify mobility patterns based on user location data, both at an individual level and an aggregate level. The system may determine the origin and destination data for each trip taken by a user. The system may then define areas of mobility using a mobility graph built from the data. The graph may include nodes and edges. In some examples, the nodes are constructed from the origins and destinations of the trajectories using spatial clustering techniques. Further, the edges between nodes may be constructed based on the trips between them, such as two nodes are connected by an edge if there is at least one trip between them. The edges may be given different weights based on trip frequencies. The system may then determine a region of mobility using the generated mobility graph and data clustering techniques.
Abstract:
Methods, computer-readable media, systems, and/or apparatuses for providing offer and insight generation functions are provided. For instance, user input may be received requesting generation of an offer. In response to receiving the request, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the application may be executed by the device and may facilitate establishing a communication session with a third party system, identifying and extracting data from the third party system, and transmitting the extracted data to an entity for evaluation. In some examples, evaluation by the entity may include generating one or more insights, outputs and the like. In some arrangements, the evaluation may be performed using machine learning and, in some examples, may be performed in real-time or near real-time.
Abstract:
A method, medium, and apparatus for educating and reducing risk to inexperienced drivers using vehicles with autonomous navigation systems. Data regarding a driver's past experience with vehicles and operating environments may be used to proactively warn the driver about a potential danger detected or predicted by the vehicle. An autonomous vehicle may prevent the driver from operating the vehicle under unfamiliar circumstances or from causing a collision. Data regarding a driver's past experience with vehicles and the safety features thereof may be used to mitigate risk of injury or property damage by selectively activating safety features in a new vehicle which the driver has not previously driven. Data regarding a driver's past experience with vehicles and safety features thereof may be used to determine a decreased or increased rental rate for a particular vehicle.
Abstract:
The disclosure provides an early notification system to alert a driver of an approaching unsafe autonomous or semi-autonomous driving zone so that a driver may switch vehicle to a non-autonomous driving mode and navigate safely through the identified location. In response, to a determination of an upcoming unsafe autonomous or semi-autonomous driving zone, the driver or system may take appropriate actions in response to the early notification.
Abstract:
A system including a computing device may receive base map information and trip request information. The base map information may include a plurality of attribute information associated with a plurality of road segments. The trip request information may include a destination to which a user plans to drive a vehicle. The computing device may determine a route for the user to travel based on the trip request information and base map information. The system might further calculate a risk score for each road segment forming the route, and generate a risk map based on the risk score and the route and cost of insurance along the route. The risk map may then be displayed to a user with alerts communicated on the map or via verbal alerts. The risk map may include markers or other objects depicting potential risks along the route the driver may face. Also, the risk map may be updated based on information collected from multiple sensors coupled to the vehicle, mobile phone or insurance database.
Abstract:
Systems and methods are disclosed for determining that an adverse driving event is likely to occur and utilizing accident calculus algorithms to determine and cause vehicle driving actions necessary to mitigate consequences of the adverse driving event. After determining that an adverse driving event is likely to occur, a computing device my forecast consequences of the driving event. The computing device may determine potential evasive maneuvers that may be taken responsive to the adverse driving event. Additionally, the computing device may determine consequences associated with the potential evasive maneuvers and assign a weight relative to the consequence. The computing device may compare the potential driving maneuvers based on the weighted consequences to determine a driving maneuver to take.
Abstract:
Systems and methods are disclosed for determining that an adverse driving event is likely to occur and utilizing accident calculus algorithms to determine and cause vehicle driving actions necessary to mitigate consequences of the adverse driving event. After determining that an adverse driving event is likely to occur, a computing device my forecast consequences of the driving event. The computing device may determine potential evasive maneuvers that may be taken responsive to the adverse driving event. Additionally, the computing device may determine consequences associated with the potential evasive maneuvers and assign a weight relative to the consequence. The computing device may compare the potential driving maneuvers based on the weighted consequences to determine a driving maneuver to take.
Abstract:
Event-based connected vehicle control and response systems, methods, and apparatus are disclosed. An example method comprises identifying the occurrence of an event, storing first data corresponding to apparatus operation for a first threshold amount of time prior to the event, during the occurrence of the event, and for a second threshold amount of time after the event, determining whether a responsive object is involved in or near the event, in response to determining that the responsive object is involved in or near the event, transmitting the first data to the responsive object, and receiving, from the responsive object, second data, analyzing the first data and the second data to determine a party at-fault for the event, aggregating the first data and second data into an event report, and causing, automatically, a response to be initiated through an entity associated with the party at-fault.
Abstract:
Systems and methods are disclosed for determining a navigation route based on the location of a vehicle and generating a recommendation for a vehicle maneuver. The method may comprise determining, based on sensor data received from a location sensor of a mobile device or a vehicle, a location of the vehicle. A computing device may determine a navigation route for navigating the vehicle from the location to a destination, and the navigation route may comprise a plurality of intersections. The computing device may determine a plurality of potential maneuvers at a first intersection of the plurality of intersections. The computing device may also determine, based on one or more factors, a navigation score for each of the plurality of potential maneuvers at the first intersection. Based on the navigation score for each of the plurality of potential maneuvers, the computing device may select a maneuver from the plurality of potential maneuvers to recommend for the vehicle.
Abstract:
Aspects of the present disclosure describe systems, methods, and devices for automated vehicular control based on glare detected by an optical system of a vehicle. In some aspects, automated control includes controlling the operation of the vehicle itself, a vehicle subsystem, or a vehicle component based on a level of glare detected. According to some examples, controlling the operation of a vehicle includes instructing an automatically or manually operated vehicle to traverse a selected route based on levels of glare detected or expected along potentials routes to a destination. According to other examples, controlling operation of a vehicle subsystem or a vehicle component includes triggering automated responses by the subsystem or the component based on a level of glare detected or expected. In some additional aspects, glare data is shared between individual vehicles and with a remote data processing system for further analysis and action.