Predicting impact of a traffic incident on a road network
First Claim
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1. A method for predicting impact of a traffic incident on a road network, the method comprising:
- receiving, by a processor, traffic data from at least one data provider; and
using a processor to;
calculate a plurality of traffic-flow velocities from the traffic data, each of the traffic-flow velocities being associated with a data-provider and a data-capture time; and
use a classification scheme and a learning model to predict, based on the traffic data, an impact class associated with the traffic-flow velocities, in which the impact class indicates a degree of severity of an incident and includes a cumulative incident delay identified based on the traffic data.
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Abstract
A method and system for predicting impact of traffic incidents on a road network by using a classification scheme to identify a known impact classes associated with captured traffic data.
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Citations
20 Claims
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1. A method for predicting impact of a traffic incident on a road network, the method comprising:
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receiving, by a processor, traffic data from at least one data provider; and using a processor to; calculate a plurality of traffic-flow velocities from the traffic data, each of the traffic-flow velocities being associated with a data-provider and a data-capture time; and use a classification scheme and a learning model to predict, based on the traffic data, an impact class associated with the traffic-flow velocities, in which the impact class indicates a degree of severity of an incident and includes a cumulative incident delay identified based on the traffic data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 16, 17, 18, 19)
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8. A system for predicting impact of a traffic incident in a road network, the system comprising:
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a plurality of data-capture devices disposed along the road network, the data-capture devices configured to capture the traffic data at a data-capture time; a processor configured to; calculate a plurality of traffic-flow velocities from the traffic data, each of the traffic-flow velocities being associated with a data-capture time and one of the traffic-data capture devices, use a classification scheme and a learning model to predict, based on the traffic data, an impact class associated with the traffic-flow velocities, in which an impact class indicates a degree of severity of an incident and a cumulative incident delay associated with the traffic-flow velocities. - View Dependent Claims (9, 10, 11, 12, 13, 20)
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14. A non-transitory computer-readable medium having stored thereon instructions for predicting impact of a traffic incident in a road network which when executed by a processor causes the processor to perform a method comprising:
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receiving traffic data from a plurality of data-capture devices; and using a processor to; calculate a plurality of traffic-flow velocities from the traffic data, each of the traffic-flow velocities being associated with a data-capture device and a data capture time, identify an impact type to associate with the incident region identified based on traffic data from data-capture data devices upstream of an incident, in which an impact type is divided into multiple impact classes, and use a classification scheme and a learning model to predict, based on the traffic data, an impact class associated with the traffic-flow velocities, in which an impact class indicates a degree of severity of an incident and includes a cumulative incident delay identified based on the traffic data. - View Dependent Claims (15)
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Specification