Dynamic time series prediction of future traffic conditions
First Claim
1. A computer-implemented method comprising:
- receiving information describing a network of roads in a geographic area;
for each of the roads in the network, identifying multiple segments of the road for which traffic congestion will be distinctly tracked; and
automatically facilitating navigation of vehicles over the network of roads based on predicted traffic congestion of the roads, the automatic facilitating of the navigation of the vehicles being performed by one or more configured computing systems and including, for each of multiple users,receiving a request from the user for information indicating predicted traffic conditions of roads of the network for travel to an indicated destination;
receiving information indicating current conditions that affect future traffic on the roads in the network, the current conditions including current levels of traffic on the roads, current weather for the geographic area, current events that are scheduled to occur in the geographic area, and current school sessions that are scheduled to occur in the geographic area;
identifying segments of roads of the network along one or more routes to the indicated destination from at least one possible starting position, each of the one or more routes including multiple identified road segments;
for each of multiple distinct future times, predicting an expected level of traffic congestion for each of the identified road segments at that future time, the predicting being based at least in part on the indicated current conditions;
for each of the one or more routes, determining a predicted travel time for the route based on the predicted expected traffic congestion levels for the multiple road segments of the route, the determining such that at least one predicted expected level of traffic congestion at a first future time is used for a first group of one or more of the road segments of the route and such that at least one predicted expected level of traffic congestion at a second future time is used for a second group of one or more other of the road segments of the route, the second future time being later than the first future time and the road segments of the second group being after the road segments of the first group along the route; and
providing information to the user that indicates the determined predicted travel time for at least one of the routes to the indicated destination,so that users can navigate vehicles over the network of roads based on predicted traffic congestion of the roads at multiple future times.
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Abstract
Techniques are described for generating predictions of future traffic conditions at multiple future times, such as by using probabilistic techniques to assess various input data while repeatedly producing future time series predictions for each of numerous road segments (e.g., in a real-time manner based on changing current conditions for a network of roads in a given geographic area). In some situations, one or more predictive Bayesian models and corresponding decision trees are automatically created for use in generating the future traffic condition predictions for each geographic area of interest, such as based on observed historical traffic conditions for those geographic areas. Predicted future traffic condition information may then be used in a variety of ways to assist in travel and for other purposes, such as to plan optimal routes through a network of roads based on predictions about traffic conditions for the roads at multiple future times.
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Citations
55 Claims
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1. A computer-implemented method comprising:
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receiving information describing a network of roads in a geographic area; for each of the roads in the network, identifying multiple segments of the road for which traffic congestion will be distinctly tracked; and automatically facilitating navigation of vehicles over the network of roads based on predicted traffic congestion of the roads, the automatic facilitating of the navigation of the vehicles being performed by one or more configured computing systems and including, for each of multiple users, receiving a request from the user for information indicating predicted traffic conditions of roads of the network for travel to an indicated destination; receiving information indicating current conditions that affect future traffic on the roads in the network, the current conditions including current levels of traffic on the roads, current weather for the geographic area, current events that are scheduled to occur in the geographic area, and current school sessions that are scheduled to occur in the geographic area; identifying segments of roads of the network along one or more routes to the indicated destination from at least one possible starting position, each of the one or more routes including multiple identified road segments; for each of multiple distinct future times, predicting an expected level of traffic congestion for each of the identified road segments at that future time, the predicting being based at least in part on the indicated current conditions; for each of the one or more routes, determining a predicted travel time for the route based on the predicted expected traffic congestion levels for the multiple road segments of the route, the determining such that at least one predicted expected level of traffic congestion at a first future time is used for a first group of one or more of the road segments of the route and such that at least one predicted expected level of traffic congestion at a second future time is used for a second group of one or more other of the road segments of the route, the second future time being later than the first future time and the road segments of the second group being after the road segments of the first group along the route; and providing information to the user that indicates the determined predicted travel time for at least one of the routes to the indicated destination, so that users can navigate vehicles over the network of roads based on predicted traffic congestion of the roads at multiple future times. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer-implemented method comprising:
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receiving indications of multiple road segments of multiple related roads; receiving information indicating current traffic conditions at a first time for each of the road segments; receiving information indicating other current conditions at the first time that affect traffic on the road segments, the other current conditions including multiple of current weather conditions, current events that are scheduled to occur, and current schedules for school sessions; using the indicated current traffic conditions for the first time and the indicated other current conditions for the first time to automatically predict multiple distinct levels of traffic congestion at multiple distinct future times after the first time for each of one or more of the multiple road segments, the automatic predicting being performed by one or more configured computing systems, the predicted traffic congestion levels for the multiple future times being distinct from historical average traffic congestion levels corresponding to the multiple future times; and using at least some of the predicted traffic congestion levels to facilitate travel on the roads. - View Dependent Claims (8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29)
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30. A non-transitory computer-readable medium whose stored contents configure a computing system to perform a method, the method comprising:
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receiving information indicating current traffic conditions at a first time for each of multiple road segments of one or more roads; receiving information indicating other current conditions at the first time that affect traffic on the multiple road segments, the other current conditions including at least one of current weather conditions, current events that are scheduled to occur, and current schedules for school sessions; using the indicated current traffic conditions for the first time and the indicated other current conditions for the first time to automatically predict multiple distinct future traffic conditions for the one or more roads, the automatic predicting being performed by the configured computing system, each of the predicted future traffic conditions being for one of the multiple road segments at one of multiple future times after the first time; and providing one or more indications of at least some of the predicted future traffic conditions for use in facilitating travel on the one or more roads. - View Dependent Claims (31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41)
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42. A computing system, comprising:
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one or more processors; a first component configured to, when executed by at least one of the one or more processors, and for each of multiple distinct future times, predict traffic conditions at that future time for each of one or more of multiple road segments of one or more roads based at least in part on obtained information indicating current conditions related to the road segments, the indicated current conditions including multiple of current traffic conditions for the road segments, current weather conditions, current scheduled events, and current school schedules; and a second component configured to, when executed by at least one of the one or more processors, provide one or more indications of at least one of the predicted traffic conditions for use in facilitating travel on the one or more roads. - View Dependent Claims (43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55)
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Specification