Method for providing corridor metrics for a corridor of a road network

Patent metadata

Field	Value
Publication number	US-11710073-B2
Application number	US-202117381330-A
Country	US
Kind code	B2
Filing date	Jul 21, 2021
Priority date	Apr 4, 2019
Publication date	Jul 25, 2023
Grant date	Jul 25, 2023

Abstract

Disclosed are systems and methods relating to providing corridor metrics based on road network data and telematic data.

First claim

What is claimed is:

1. A method for providing traffic metrics for a corridor of a road network comprising:
providing first road network data indicating a first plurality of road network subzones defining a geographic area occupied by the road network, the road network including a plurality of intersections;
processing the first road network data for labelling each road network subzone as one of a core subzone and a non-core subzone for forming a first plurality of core subzones and a first plurality of non-core subzones and storing an indication thereof in the first road network data;
mapping each of the first plurality of core subzones to an intersection of the plurality of intersections of the road network and storing an indication thereof in the first road network data;
forming a plurality of subsets of core subzones of the first plurality of core subzones, each thereof defining a geographic area occupied by an intersection core of an intersection of the plurality of intersections;
processing the first road network data for mapping each non-core subzone of the first plurality of non-core subzones to at least one intersection of the plurality of intersections;
forming second road network data including the first road network data and an indication of the at least one intersection of the plurality of intersections of the road network to which each non-core subzone of the first plurality of non-core subzones is mapped;
forming trip metadata dependent on second road network data and third vehicle data corresponding to the first plurality of road network subzones; and
processing the trip metadata associated with a plurality of contiguous intersections of the plurality of intersections of the road network defining the corridor for forming corridor metrics data indicative of corridor metrics for the corridor.

2. The method of claim 1 wherein forming the corridor metrics data includes forming traffic metrics data for each pair of contiguous intersections of the plurality of contiguous intersections indicative of traffic metrics for each pair of contiguous intersections.

3. The method of claim 1 wherein forming the corridor metrics data includes forming cumulative metric data indicative of one or more sequences of contiguous intersections of the plurality of contiguous intersections indicative of traffic metrics for the one or more sequences of contiguous intersections.

4. The method of claim 1 wherein processing the trip metadata associated with the plurality of contiguous intersections of the plurality of intersections defining the corridor for forming corridor metrics data indicative of the corridor metrics for the corridor includes processing the trip metadata and corridor data, the corridor data indicative of the plurality of intersections defining the corridor.

5. The method of claim 4 wherein the corridor data is provided by a user.

6. The method of claim 1 wherein processing the trip metadata associated with the plurality of contiguous intersections of the plurality of intersections of the road network defining the corridor for forming traffic metrics data indicative of the corridor metrics for the corridor includes,
processing the trip metadata associated with each contiguous intersection of the plurality of contiguous intersections for forming intersection metrics data indicative of intersection metrics for each thereof; and
processing the intersection metrics data for each contiguous intersection of the plurality of contiguous intersections for forming the corridor metrics data.

7. The method of claim 1 wherein processing the first road network data for mapping each non-core subzone of the first plurality of non-core subzones to the at least one intersection of the plurality of intersections of the road network includes,
for each road network subzone of the first plurality of road network subzones, processing road network data for forming point data indicating a point representing a location of the road network subzone;
for each intersection of the plurality of intersections, processing point data of a corresponding intersection core and point data of the first plurality of non-core subzones for clustering corresponding points into groups; and
for each point of a non-core subzone of the first plurality of non-core subzones grouped in a same group as points of an intersection core, mapping the non-core subzone to a corresponding intersection of the intersection core.

8. The method of claim 7 wherein processing the point data of the corresponding intersection core and the point data of the first plurality of non-core subzones for clustering corresponding points into groups includes, for at least a road network subzone, processing road network data for determining a centre point of the road network subzone.

9. The method of claim 7 wherein processing the point data of the corresponding intersection core and the point data of the first plurality of non-core subzones for clustering corresponding points into groups includes clustering the corresponding points into groups using a spatial clustering algorithm.

10. The method of claim 1 wherein forming the trip metadata dependent on the second road network data and the third vehicle data corresponding to the first plurality of road network subzones includes,
for each vehicle of a plurality of vehicles corresponding to the third vehicle data, selecting at least a first subset of temporally consecutive third vehicle data instances indicating the vehicle transitions from a first undrivable state to a second drivable state to a third undrivable state for forming journey data;
processing the journey data and road network data for mapping each instance of journey data to a road network subzone of the first plurality of road network subzones based on a journey data instance corresponding to a road network subzone of the first plurality of road network subzones and storing an indication of a location of the road network subzone, a label of the road network subzone, and intersection mapping of the road network subzone in the journey data;
selecting subsets of journey data instances for forming trip data indicative of vehicle trips and mapping the trip data to an intersection of the plurality of intersections of the road network; and
processing each trip data instance of trip data for forming the trip metadata.

11. The method of claim 10 wherein for each vehicle of the plurality of vehicles corresponding to the third vehicle data, selecting at least the first subset of temporally consecutive third vehicle data instances indicating the vehicle transitions from the first undrivable state to the second drivable state to the third undrivable state for forming the journey data includes, for at least a vehicle, selecting at least a sequence of third vehicle data instances including a third vehicle data instance indicating an ignition status of the vehicle is OFF, immediately followed by a third vehicle data instance indicating the ignition status of the vehicle is ON and the vehicle has a speed greater than 0 kilometers per hour (km/h), immediately followed by one or more third vehicle data instances indicating the ignition status of the vehicle is ON, immediately followed by a third vehicle data instance indicating the ignition status of the vehicle is OFF.

12. The method of claim 10 wherein selecting the subsets of journey data instances for forming the trip data indicative of vehicle trips includes,
selecting at least one first sequence of journey data instances from the journey data for forming the trip data, the at least one first sequence of journey data instances including at least one journey data instance corresponding

Assignees

• Geotab Inc
• Geo Tab Inc

Inventors

• Lewis Daniel J
• Bradley Robert

Classifications

• G06N20/00 Primary

  Machine learning · CPC title

• G01C21/3822

  Road feature data, e.g. slope data · CPC title

• G01S19/01

  Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO · CPC title

• G06F18/2321

  using statistics or function optimisation, e.g. modelling of probability density functions · CPC title

• G06V20/54

  of traffic, e.g. cars on the road, trains or boats · CPC title