Predicting traffic violation hotspots using map features and sensors data
AssigneeHERE Global B.V.
InventorsAmarnath Nayak, Jerome Beaurepaire
Life of this patent
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Abstract
System and methods for determining traffic violation hotspots based on roadway feature and/or sensor data. Traffic violation hotspots include, for example areas where traffic violations are more likely to occur such as traffic light jumping, wrong way driving, over speeding, not wearing seatbelt, avoiding stop signs and red lights, distracted driving, passing other vehicles in a no-passing zone, among others. Traffic violation data from one region is used to train a model that is applied to a second region for which traffic violation data does not exist or is limited.
Claims19
A method for predicting traffic violation hotspots, the method comprising:
- acquiring historical traffic violation data for a plurality of locations in a first region;
- training a model to identify traffic violation hotspots using the historical traffic violation data;
- acquiring real-time data while traversing a location in a second region for which historical traffic violation data is limited;
- generating, by the trained model using the real-time data, a probability score that represents how probable the location in the second region is to be a traffic violation hotspot;
- and
- generating an update to a map displayed in a vehicle for the location based on the probability score, wherein the update to the displayed map includes one or more routing instructions for a different route associated with the second region.
A system for calculating a probability of a traffic violation, the system comprising:
- one or more navigation devices configured to acquire sensor data related a plurality of locations on a roadway;
- a mapping system comprising:
- a geographic database configured to store map feature data for the plurality of locations;
- and
- a server configured to store a first machine learning model configured to generate a first probability score when input real-time sensor data for a location for which there is limited traffic violation data, the server further configured to store a second machine learning model configured to generate a second probability score when input real-time mapping data for the location;
- wherein the server is configured to provide the first probability score, the second probability score, or the first probability score and the second probability score to the one or more navigation devices, wherein the server is configured to provide an update to a map displayed in a vehicle for the location based on the probability score, wherein the update to the displayed map includes one or more routing instructions for a different route associated with the location.
An apparatus comprising:
- at least one processor;
- and
- at least one memory including computer program code for one or more programs;
- the at least one memory configured to store the computer program code configured to, with the at least one processor, cause the at least one processor to:
- acquire data related to a location of a roadway for a first region;
- generate, using at least one model trained using machine learning, a probability score for how probable is the location is to be a traffic violation hotspot, the at least one model trained using historical traffic violation data from a second region;
- determine that the probability score exceeds a threshold score;
- and
- generate an update to a map displayed in a vehicle for the location, wherein the update to the displayed map includes one or more routing instructions for a different route associated with the second region.
Dependencies are inferred from the claim text.