Traffic classification based on spatial neighbor model
First Claim
1. A method for traffic classification, the method comprising:
- accessing a road topology comprising links from a geographic database;
selecting, using a processor, a link from the road topology;
identifying, using the processor, a subset of the road topology having neighboring links that have a significant conditional probability on the selected link; and
generating traffic estimation, using the processor, a traffic estimation model for the selected link using the subset of road topology and historical traffic data for the neighboring links an historical traffic data for the selected link,wherein the subset of the road topology includes a Markov blanket for the selected link in the road topology.
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Abstract
Systems, methods, and apparatuses are described for estimating traffic conditions on road segments when no real time traffic data is available. A computing device may access a road topology comprising links from a geographic database. One of the links is selected from road topology. The computing device identifies a subset of the road topology having neighboring links that have an influential conditional probability on the selected link. In one example, the subset of the neighboring links includes parent links for the selected link, child links for the selected link, and parents of child links of the selected link. The computing device generates a traffic estimation model for the selected link using the subset of road topology and historical traffic data for the neighboring links.
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Citations
20 Claims
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1. A method for traffic classification, the method comprising:
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accessing a road topology comprising links from a geographic database; selecting, using a processor, a link from the road topology; identifying, using the processor, a subset of the road topology having neighboring links that have a significant conditional probability on the selected link; and generating traffic estimation, using the processor, a traffic estimation model for the selected link using the subset of road topology and historical traffic data for the neighboring links an historical traffic data for the selected link, wherein the subset of the road topology includes a Markov blanket for the selected link in the road topology. - View Dependent Claims (2)
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3. A method comprising:
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accessing data indicative of a road network from a geographic database; selecting, using a processor, a selected link from the road network; identifying, using the processor, a subset of the road network having neighboring links that have a significant conditional probability on the selected link, wherein the subset of the road network includes at least one neighboring link not adjacent to the selected link; and generating, using the processor, traffic data for the selected link using the subset of the road network and historical traffic data for the neighboring links including the at least one neighboring link not adjacent to the selected link. - View Dependent Claims (4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus for traffic classification, the apparatus comprising:
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at least one processor; and at least one memory including computer program code for one or more programs;
the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least;selecting a selected link from a road network; identifying a subset of the road network having neighboring links that have a significant conditional probability on the selected link, wherein the subset of the road network includes at least one neighboring link not adjacent to the selected link; and generating traffic data for the selected link using the subset of the road network and traffic data for the neighboring links including the at least one neighboring link not adjacent to the selected link. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification