Patent application number | Description | Published |
20100185382 | DISPLAYING ROAD TRAFFIC CONDITION INFORMATION AND USER CONTROLS - Techniques are described for displaying or otherwise providing information to users regarding various types of road traffic condition information in various ways. The information may be provided, for example, as part of a user interface (or “UI”), which may in some situations further include one or more types of user-selectable controls to allow a user to manipulate in various ways what road traffic condition information is displayed and/or how the information is displayed. A variety of types of road traffic condition information may be presented to users in various manners, including by presenting information on graphically displayed maps for geographic areas to indicate various information about road conditions in the geographic area. In addition, provided controls may allow users to select particular times, select particular routes, indicate to perform animation of various types of changing traffic conditions over a sequence of multiple successive times, etc. | 07-22-2010 |
20110035141 | DISPLAYING ROAD TRAFFIC CONDITION INFORMATION AND USER CONTROLS - Techniques are described for displaying or otherwise providing information to users regarding various types of road traffic condition information in various ways. The information may be provided, for example, as part of a user interface (or “UI”), which may in some situations further include one or more types of user-selectable controls to allow a user to manipulate in various ways what road traffic condition information is displayed and/or how the information is displayed. A variety of types of road traffic condition information may be presented to users in various manners, including by presenting information on graphically displayed maps for geographic areas to indicate various information about road conditions in the geographic area. In addition, provided controls may allow users to select particular times, select particular routes, indicate to perform animation of various types of changing traffic conditions over a sequence of multiple successive times, etc. | 02-10-2011 |
20110082636 | DYNAMIC TIME SERIES PREDICTION OF FUTURE TRAFFIC CONDITIONS - 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. | 04-07-2011 |
20110106416 | PREDICTING EXPECTED ROAD TRAFFIC CONDITIONS BASED ON HISTORICAL AND CURRENT DATA - Techniques are described for determining and using information regarding expected road traffic flow conditions information for vehicles traveling on roads. The expected road traffic flow conditions for a particular portion of a road may be generated by combining historical representative information about road traffic flow conditions for that road portion with current information about actual traffic flow on or near that road portion. The combination may, for example, provide benefits for estimating expected traffic flow conditions information for roads with structural flow obstructions that cause reduced traffic flow at certain road locations and times—for example, the expected traffic flow conditions information may be based at least in part on fitting or otherwise adapting partial actual traffic flow information about a vehicle's actual travel path to a historical travel profile for a road that includes representative traffic flow information for various combinations of road locations and time periods. | 05-05-2011 |
20110112747 | DETECTING ANOMALOUS ROAD TRAFFIC CONDITIONS - Techniques are described for automatically detecting anomalous road traffic conditions and for providing information about the detected anomalies, such as for use in facilitating travel on roads of interest. Anomalous road traffic conditions may be identified using target traffic conditions for a particular road segment at a particular selected time, such as target traffic conditions that reflect actual traffic conditions for a current or past selected time, and/or target traffic conditions that reflect predicted future traffic conditions for a future selected time. Target traffic conditions may be compared to distinct expected road traffic conditions for a road segment at a selected time, with the expected conditions reflecting road traffic conditions that are typical or normal for the road segment at the selected time. Anomalous conditions may be identified based on sufficiently large differences from the expected conditions, and information about the anomalous conditions may be provided in various ways. | 05-12-2011 |
20110224893 | LEARNING ROAD FEATURE DELAY TIMES BASED ON AGGREGATE DRIVER BEHAVIOR - Techniques are described for generating and using information regarding road traffic in various ways, including by obtaining and analyzing road traffic information regarding actual behavior of drivers of vehicles on a network of roads. Obtained actual driver behavior information may in some situations be analyzed to determine actual delays for vehicles encountering various particular road features in the network of roads, such as for identified decision points at which drivers face choices corresponding to possible alternative routes through the network of roads (e.g., intersections, highway exits and/or entrances, etc.) and/or for other traffic flow impediments. The identified and determined information from the analysis may then be used in various manners, including in some situations to assist in determining particular recommended or preferred routes of vehicles through the network of roads based at least in part on actual driver behavior information. | 09-15-2011 |
20110224898 | LEARNING ROAD NAVIGATION PATHS BASED ON AGGREGATE DRIVER BEHAVIOR - Techniques are described for generating and using information regarding road traffic in various ways, including by obtaining and analyzing road traffic information regarding actual behavior of drivers of vehicles on a network of roads. Obtained actual driver behavior information may in some situations be analyzed to identify decision point locations at which drivers face choices corresponding to possible alternative routes through the network of roads (e.g., intersections, highway exits and/or entrances, etc.), as well as to track the actual use by drivers of particular paths between particular decision points in order to determine preferred compound links between those decision point locations. The identified and determined information from the analysis may then be used in various manners, including in some situations to assist in determining particular recommended or preferred routes of vehicles through the network of roads based at least in part on actual driver behavior information. | 09-15-2011 |
20110288756 | FILTERING ROAD TRAFFIC CONDITION DATA OBTAINED FROM MOBILE DATA SOURCES - Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics from the data samples. In some situations, the filtering of the data samples includes identifying data samples that are inaccurate or otherwise unrepresentative of actual traffic condition characteristics, such as data samples that are not of interest based at least in part on roads with which the data samples are associated and/or that otherwise reflect vehicle locations or activities that are not of interest. | 11-24-2011 |
20120136561 | DYNAMIC TIME SERIES PREDICTION OF TRAFFIC CONDITIONS - 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. | 05-31-2012 |
20140309914 | LEARNING ROAD NAVIGATION PATHS BASED ON AGGREGATE DRIVER BEHAVIOR - Techniques are described for generating and using information regarding road traffic in various ways, including by obtaining and analyzing road traffic information regarding actual behavior of drivers of vehicles on a network of roads. Obtained actual driver behavior information may in some situations be analyzed to identify decision point locations at which drivers face choices corresponding to possible alternative routes through the network of roads (e.g., intersections, highway exits and/or entrances, etc.), as well as to track the actual use by drivers of particular paths between particular decision points in order to determine preferred compound links between those decision point locations. The identified and determined information from the analysis may then be used in various manners, including in some situations to assist in determining particular recommended or preferred routes of vehicles through the network of roads based at least in part on actual driver behavior information. | 10-16-2014 |
Patent application number | Description | Published |
20090095377 | SYSTEMS AND METHODS FOR TRACKING LUMBER IN A SAWMILL - At least one geometric characteristic for each of a number of pieces of lumber is determined. Each of the pieces of lumber may then be logically associated with at least one of a log or a cant from which the piece of lumber was sawn. | 04-16-2009 |
20090095378 | SYSTEMS AND METHODS FOR MONITORING A SAW BLADE DURING SAWING - A light source is used to illuminate a sawn portion of a piece of wood and exposed surfaces of the saw blade on both sides of the sawn portion. The sawn portion and the exposed surfaces of the saw blade are then imaged substantially concurrently using a single image generator. At least one geometric characteristic of the sawn portion and at least one geometric characteristic of the saw blade are determined based on the imaging. | 04-16-2009 |
20090095379 | SYSTEMS AND METHODS FOR GANGSAW MANAGEMENT - The geometric characteristics for a plurality of boards that have been completely sawn by a gangsaw are determined. A sawn surface of one of the plurality of boards is then logically associated with one of the plurality of saw blades in the gangsaw. | 04-16-2009 |
20090255607 | SYSTEMS AND METHODS FOR TRACKING LUMBER IN A SAWMILL - At least one geometric characteristic for each of a number of pieces of lumber is determined. Each of the pieces of lumber may then be logically associated with at least one of a log or a cant from which the piece of lumber was sawn. | 10-15-2009 |
20120227866 | MACHINE VISION BASED SAWMILL AUDIT SYSTEM - Sawmill auditing and control apparatus and methods employ information from one or more scan zones and/or controllers (e.g., PLCs). Boards may be logically associated with mill equipment which produced the boards, allowing defects or imperfections to be tied to certain equipment. For example, boards may be associated with a primary breakdown machine or a gangsaw, or with a pair of cutters (e.g., saws, chip heads). Such allows auditing of mill operations to identify improperly functioning machinery or out of tolerance conditions, to correct such, and/or provide notification. | 09-13-2012 |
20120262725 | SYSTEMS AND METHODS FOR TRACKING LUMBER IN A SAWMILL - At least one geometric characteristic for each of a number of pieces of lumber is determined. Each of the pieces of lumber may then be logically associated with at least one of a log or a cant from which the piece of lumber was sawn. | 10-18-2012 |
20130199672 | SYSTEMS AND METHODS FOR AUDITING OPTIMIZERS TRACKING LUMBER IN A SAWMILL - An audit system and method audits operation of an optimizer system in a mill, for example auditing operation of a cant optimizer which optimizes sawing patterns. The audit system may be completely independent of the optimizer. For example, the audit system may acquire information (e.g., optically) indicative of a geometry of boards downstream from a piece of equipment such as a gangsaw. The audit system may computationally reconstruct a cant from which the boards were sawn, determine an outside dimension indicative of wane, and simulate alternative sawing patterns, determining a theoretical amount of recovery that would have resulted from each and comparing such to actual recovery from the log or cant. Alternative sawing patterns may take into account various wane rules and comparison may take into account current demand and/or prices for dimensional lumber. | 08-08-2013 |
20140238546 | SYSTEMS AND METHODS OF ORIENTING A CANT IN LUMBER MILLS - Processing of a cant may include determining a rotational orientation about a longitudinal axis of the cant that optimizes a recovery from the cant from subsequent sawing operations. Such may include optimizing a width of a board that will be produced dependent on the particular rotational longitudinal orientation. Such may include determining a surface area of a board which would be produced, a thickness of a board that would be produced, and/or a volume of a board that would be produced. Such may include accounting for any premium associated with various width categories in which a board that would be produced would fit. Such may account for any premium associated with grade or quality of a board that would be produced. A corresponding signal may provide information to a human operator and/or automated machinery to orient the cant in an optimized orientation. | 08-28-2014 |
20140251499 | METHODS AND SYSTEMS OF MANAGING CHIPPING AND SAWING EQUIPMENT - At least one image device proximate a second conveyor is disposed a predetermined distance in front of chip heads. The at least one image device can image a log and capture the actual log position on a sharp chain before its being engaged by chip heads. A computing device is coupled to the at least one image device to receive data including the actual log position information. The computing device compares the actual log position to a preferred log position solution so as to check whether a log deviates from its expected position. If any position deviation exists, the computing device may send instructions to adjust the positions of the chip heads and saws to ensure that a log is correctly positioned relative to the chip heads and saws, whereby correcting log position errors and eliminating transport accuracy losses. | 09-11-2014 |