Monitoring traffic congestion
First Claim
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1. A computer system for monitoring traffic congestion, comprising:
- a non-transitory memory device for storing computer-readable program code; and
a processor in communication with the non-transitory memory device, the processor being operative with the computer-readable program code to perform operations including;
receiving, by a congestion monitor of the computer system, vehicle data within a time slot from vehicle data sources located in a region of interest, each vehicle data source being located in a vehicle in the region of interest;
determining, by the congestion monitor, a sample size and an average speed for an edge of the region of interest based on the vehicle data, wherein the sample size corresponds to a number of vehicles located in the edge of the region of interest within the time slot and the edge of the region of interest is a predefined segment of a road network of the region of interest and wherein an inverse of a variance of the average speed is linearly related to the sample size when the sample size is less than a predetermined value,determining, by the congestion monitor, a congestion probability based on the sample size and the average speed and by;
determining the congestion probability comprises determining the variance of the average speed,determining a slope of a graph of the inverse of the variance against the sample size, andmodeling a distribution of true speed using a normal probability model, wherein a mean of the normal probability model is the average speed and a variance of the normal probability model is based on the slope, andpresenting a report in a graphical user interface based on the congestion probability of the edge of the region of interest.
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Abstract
Described herein is a framework to monitor traffic congestion. In accordance with one aspect of the framework, the framework receives vehicle data from vehicle data sources located in a region of interest. The framework may determine a sample size and an average speed for an edge of the region of interest based on the vehicle data. Congestion probability may then be determined based on the sample size and average speed. A report may be presented based on the congestion probability.
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Citations
20 Claims
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1. A computer system for monitoring traffic congestion, comprising:
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a non-transitory memory device for storing computer-readable program code; and a processor in communication with the non-transitory memory device, the processor being operative with the computer-readable program code to perform operations including; receiving, by a congestion monitor of the computer system, vehicle data within a time slot from vehicle data sources located in a region of interest, each vehicle data source being located in a vehicle in the region of interest; determining, by the congestion monitor, a sample size and an average speed for an edge of the region of interest based on the vehicle data, wherein the sample size corresponds to a number of vehicles located in the edge of the region of interest within the time slot and the edge of the region of interest is a predefined segment of a road network of the region of interest and wherein an inverse of a variance of the average speed is linearly related to the sample size when the sample size is less than a predetermined value, determining, by the congestion monitor, a congestion probability based on the sample size and the average speed and by; determining the congestion probability comprises determining the variance of the average speed, determining a slope of a graph of the inverse of the variance against the sample size, and modeling a distribution of true speed using a normal probability model, wherein a mean of the normal probability model is the average speed and a variance of the normal probability model is based on the slope, and presenting a report in a graphical user interface based on the congestion probability of the edge of the region of interest. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method of monitoring traffic congestion, the method being implemented by at least one computing device and comprising:
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receiving, by a congestion monitor of the at least one computing device, vehicle data within a time slot from vehicle data sources located in a region of interest;
each vehicle data source being located in a vehicle in the region of interest;determining, by the congestion monitor, a sample size and an average speed for an edge of the region of interest based on the vehicle data, wherein the sample size corresponds to a number of vehicles located in the edge of the region of interest within the time slot and the edge of the region of interest is a predefined segment of a road network of the region of interest and wherein an inverse of a variance of the average speed is linearly related to the sample size when the sample size is less than a predetermined value; determining, by the congestion monitor, a congestion probability based on the sample size and the average speed and by; determining the congestion probability comprises determining the variance of the average speed; determining a slope of a graph of the inverse of the variance against the sample size; and modeling a distribution of true speed using a normal probability model, wherein a mean of the normal probability model is the average speed and a variance of the normal probability model is based on the slope; and presenting a report in a graphical user interface based on the congestion probability of the edge of the region of interest. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. One or more non-transitory computer-readable media having stored thereon program code, the program code executable by a computer to perform steps comprising:
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receiving, by a congestion monitor of the computer, vehicle data within a time slot from vehicle data sources located in a region of interest;
each vehicle data source being located in a vehicle in the region of interest;determining, by the congestion monitor, a sample size and an average speed for an edge of the region of interest based on the vehicle data;
wherein the sample size corresponds to a number of vehicles located in the edge of the region of interest within the time slot and the edge of the region of interest is a predefined segment of a road network of the region of interest and wherein an inverse of a variance of the average speed is linearly related to the sample size when the sample size is less than a predetermined value;determining, by the congestion monitor, a congestion probability based on the sample size and the average speed and by; determining the congestion probability comprises determining the variance of the average speed; determining a slope of a graph of the inverse of the variance against the sample size; and modeling a distribution of true speed using a normal probability model, wherein a mean of the normal probability model is the average speed and a variance of the normal probability model is based on the slope; and presenting a report in a graphical user interface based on the congestion probability of the edge of the region of interest.
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Specification