US 11,443,331 B2Granted

Multi-target tracking for demand management

AssigneeConduent Business Solutions, LLC

InventorsChristopher R. Dance, Roberto Ramon Rodriguez

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Abstract

In a method for monitoring a tracked parameter for a set of targets, a first methodology is applied during a current time interval to acquire observations of the tracked parameter for a selected sub-set of the set of targets. A second methodology is applied during the current time interval to acquire observations of the tracked parameter for at least those targets that are not in the selected sub-set of the set of targets. A variance forecast is generated for an upcoming time interval for each target based on a current variance for the target and on either observations acquired using the first methodology or using the second methodology. The selected sub-set of the set of targets is updated for the upcoming time interval to maximize an aggregation of variance forecasts over the updated selected sub-set of the set of targets.

Claims14

Dependent claims

A non-transitory storage medium storing instructions readable and executable by an electronic data processing device to perform a tracking method comprising iteratively repeating the set of operations:

applying a first methodology (O) to acquire observations of a parking occupancy metric for a selected sub-set of a set of parking space segments wherein the parking occupancy metric represents the fraction of occupied parking spots in the selected sub-set of parking space segments, wherein the parking space segments are grouped into parking space segment collections each observable by a single mobile observing unit of a set of mobile observing units, the first methodology computing the parking occupancy metric based on observations acquired for the selected sub-set of the set of parking space segments by the set of mobile observing units;
applying a second methodology (P) different from the first methodology and that does not use observing units to acquire observations of the parking occupancy metric for at least those parking space segments of the set of parking space segments that are not in the selected sub-set of the set of parking space segments, the second methodology estimating the parking occupancy metric based on collected parking payments;
generating variance forecasts for each parking space segment of the set of parking space segments using:
a variance update function (g) operating on observations of the parking occupancy metric acquired using the first methodology (O) that is used when the parking space segment is in the selected sub-set of the set of parking space segments;
and
a variance update function (f) operating on observations of the parking occupancy metric acquired using the second methodology (P) that is used when the parking space segment is not in the selected sub-set of the set of parking space segments;
and
updating the selected sub-set of the set of parking space segments for an upcoming time interval, and re-allocating the mobile observing units of the set of mobile observing units by moving mobile observing units of the set of mobile observing units to positions observing the updated sub-set of the set of parking space segments for the upcoming time interval to maximize the aggregation of variance forecasts over the set of parking space segments observable by the re-allocation of the mobile observing units.

5 more elements

A tracking method for monitoring a parking occupancy metric for a set of parking space segments, the tracking method comprising:

applying a first methodology during a current time interval to acquire observations of the parking occupancy metric for a selected sub-set of the set of parking space segments using a set of mobile observing units allocated to observe the selected sub-set of the set of parking space segments, wherein the parking occupancy metric represents the fraction of occupied parking spots in the selected sub-set of parking space segments;
applying a second methodology that does not use observing units and is different from the first methodology during the current time interval to acquire observations of the parking occupancy metric for at least those parking space segments that are not in the selected sub-set of the set of parking space segments;
generating variance forecasts for an upcoming time interval for each parking space segment using a computer configured to compute either:
a variance update function operating on a current variance for the parking space segment and on observations acquired for the parking space segment in the current time interval using the first methodology that is used when the parking space segment is in the selected sub-set of the set of parking space segments;
and
a variance update function operating on the current variance for the parking space segment and on observations acquired for the parking space segment in the current time interval using the second methodology that is used when the parking space segment is not in the selected sub-set of the set of parking space segments;
using the computer, updating the selected sub-set of the set of parking space segments for the upcoming time interval to maximize an aggregation of variance forecasts over the updated selected sub-set of the set of parking space segments;
and
after updating the selected sub-set of the set of parking space segments for the upcoming time interval, re-allocating the mobile observing units of the set of mobile observing units to observe the updated sub-set of the set of parking space segments for the upcoming time interval by moving mobile observing units of the set of mobile observing units to positions observing the updated sub-set of the set of parking space segments for the upcoming time interval.

6 more elements

A system for monitoring a parking occupancy metric for a set of spatially distributed parking space segments grouped into parking space segment collections of a set of parking space segment collections , the system comprising:

a first observation system comprising a set of mobile observing units arranged to acquire observations of the parking occupancy metric for a selected sub-set of the set of spatially distributed parking space segments in which the parking occupancy metric represents the fraction of occupied parking spots in the selected sub-set of parking space segments, where each parking space segment collection of the set of parking space collections is observable by a single mobile observing unit and the selected sub-set is defined by an allocation → of the mobile observing units set of the mobile observing units to parking space segment collections of the set of parking space collections ;
a second observation system configured to acquire observations of the parking occupancy metric without using observing units for at least those parking space segments of the set of spatially distributed parking space segments that are not in the selected sub-set of the set of spatially distributed parking space segments;
and
a computer configured to generate variance forecasts for each parking space segment of the set of spatially distributed parking space segments by computing:
for parking space segments belonging to the selected sub-set of the set of spatially distributed parking space segments, a variance update function operating on a current variance for the parking space segment and on observations acquired for the parking space segment using the first observation system, and
for parking space segments of the set of spatially distributed parking space segments that do not belong to the selected sub-set of the set of spatially distributed parking space segments, a variance update function operating on the current variance for the parking space segment and on observations acquired for the parking space segment using the second observation system;
and further configured to update the selected sub-set of the set of spatially distributed parking space segments for an upcoming time interval, and re-allocating the mobile observing units of the set of mobile observing units by moving mobile observing units of the set of mobile observing units to positions observing the updated sub-set of the set of parking space segments for the upcoming time interval to maximize an aggregation of variance forecasts over the updated selected sub-set of the set of spatially distributed parking space segments.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application: 14/179,970Filed 13 Feb 2014
Published: US 2015/0227952 A113 Aug 2015
Granted: 13 Sep 2022
Term ends: Not estimatedThe source records don’t support an estimate.

Classification3 codes

G06Q 30/0202
Market modelling; Market analysis; Collecting market data: market predictions or forecasting for commercial activities
G06Q 10/04
Administration; Management: forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or…
G06Q
Information and communication technology [ict] specially adapted for administrative, commercial, financial, managerial

Family

US 2015/0227952 A1Pre-grant publication · published 13 Aug 2015
US 11,443,331 B2This patent

From the US filing history. Foreign family members aren’t listed.

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