Situation-aware route and destination predictions

• US 9,500,493 B2
• Filed: 06/09/2014
• Issued: 11/22/2016
• Est. Priority Date: 06/09/2014
• Status: Active Grant

• Current Assignee: Audi AG (Volkswagen AG), Volkswagen AG
• Original Assignee: Audi AG (Volkswagen AG), Volkswagen AG
• Inventors: Gerlach, Simon
• Primary Examiner(s): HOLLOWAY, JASON R
• Application Number:
  US14/299,554
• Publication Number:
  US 20150354978A1
• Time in Patent Office: 897 Days
• Field of Search: 701/424
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3617 using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• CPC Class Codes: G01C 21/362 received from an external device or application, e.g. PDA, mobile phone or calendar application
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G08G 1/096838 where the user preferences are taken into account or the user selects one route out of a plurality
• CPC Class Codes: G08G 1/096894 where input is assisted by the navigation device, i.e. the user does not type the complete name of the destination, e.g. using zip codes, telephone numbers, progressively selecting from initial letters

Abstract

A method for predicting a destination of a vehicle includes receiving vehicle data from a plurality of sensors, the vehicle data including at least a current location and a current time, determining a plurality of usage scenarios based on the vehicle data, accessing historical vehicle data and user data from a database, assigning, based on the vehicle data, a likelihood value to each of the plurality of usage scenarios, and predicting a set of destinations and routes for each of the plurality of usage scenarios.

Claims

1. A system, comprising:

a sensor configured to detect vehicle data;

a situation detection unit configured to receive the vehicle data from the sensor and to determine a plurality of common usage scenarios based on the vehicle data, the situation detection unit configured to determine and assign a likelihood value for the plurality of common usage scenarios;

a navigation system control unit configured to receive the vehicle data from the sensor and the plurality of common usage scenarios and the likelihood value from the situation detection unit, and the navigation system control unit is configured to predict a most likely usage scenario from the plurality of common usage scenarios and determine a set of destinations for the predicted most likely usage scenario;

a user interface configured to display the predicted most likely usage scenario to a user and configured to receive user input such that the user is able to confirm the predicted most likely usage scenario; and

a historical database containing vehicle data for prior vehicle trips and a reliability value for prior predictions,

wherein when the user confirms the predicted most likely usage scenario, the historical database is configured to update the reliability value, and

wherein when the user confirms the predicted most likely usage scenario the system applies settings, corresponding to the predicted most likely usage scenario, to in-vehicle systems.

2. The system according to claim 1, wherein the sensor comprises a plurality of sensors configured to detect a variety of vehicle data.

3. The system according to claim 1, wherein the in-vehicle systems comprise a vehicle navigation system and other in-vehicle systems.

4. The system according to claim 2, wherein the plurality of sensors are configured to detect external vehicle data and passenger usage parameters.

5. The system according to claim 1, wherein the system applies a weight to each destination in the set of destinations based on a likelihood that the destination matches a particular common usage scenario.

6. The system according to claim 5, wherein the system determines the weight based on data stored in the historical database.