DETERMINING ROAD TRAFFIC CONDITIONS USING MULTIPLE DATA SAMPLES

• US 20120150425A1
• Filed: 12/08/2011
• Published: 06/14/2012
• Est. Priority Date: 03/03/2006
• Status: Active Grant

• Current Assignee: Inrix Incorporated
• Original Assignee: Inrix Incorporated
• Inventors: Chapman, Craig H., Parikh, Kush G., Downs, Oliver B., Cahn, Robert C., Hersch, Jesse S.
• Granted Patent: US 8,483,940 B2
• Time in Patent Office: Days
• US Class Current: 701/119
• CPC Class Codes: G01C 21/3691 Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions arrangements for giving variable traffic instructions G08G1/09
• CPC Class Codes: G08G 1/00 Traffic control systems for road vehicles arrangement of road signs or traffic signals E01F9/00 ; automatic vehicle control B62D
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/0968 Systems involving transmission of navigation instructions to the vehicle

Abstract

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 and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment 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 of interest from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

Claims

1-96. -96. (canceled)

97. A computer-implemented method for providing information related to vehicle travel on roads, the method comprising:

for each of one or more roads,

obtaining a plurality of data samples of one or more types that reflect travel characteristics of vehicles traveling on the road during a period of time, the obtained data samples including multiple mobile data source data samples that are reported by one or more mobile devices moving along the road;

automatically assessing, by one or more programmed computing systems, the obtained data samples to identify a group of multiple data samples to represent actual vehicle travel on the road during the period of time, the identifying of the group including excluding any data samples that are identified as being unrepresentative of actual vehicle travel on the road;

automatically analyzing, by the one or more programmed computing systems, the identified group of multiple data samples to determine one or more estimated measurements of actual traffic flow during the period of time on the road; and

providing one or more indications of the determined estimated actual traffic flow measurements for use in facilitating travel on the road.

98. The method of claim 97 wherein the providing of the one or more indications of the determined estimated actual traffic flow measurements includes providing the determined estimated actual traffic flow measurements to each of one or more users for display to the one or more users.

99. The method of claim 98 wherein the one or more roads are part of a network of multiple roads in a geographic area, and wherein the providing of the determined estimated actual traffic flow measurements to each of one or more users for display includes providing to each of the users a graphical representation of the geographic area that includes graphical indications of at least some of the multiple roads and that includes graphical indications for each of multiple road segments of corresponding determined estimated actual traffic flow measurements for that road segment.

100. The method of claim 97 further comprising, for each of at least one of the one or more roads, automatically generating one or more predicted measurements of future traffic flow during each of one or more future periods of times on the road, and providing one or more indications of the generated predicted future traffic flow measurements for use in facilitating future travel on the at least one roads.

101. The method of claim 100 wherein the period of time for which the estimated actual traffic flow measurements are determined is a current period of time, and wherein the predicted future traffic flow measurements for the one or more future periods of times are generated during the current period of time and are based in part on the determined estimated actual traffic flow measurements for the current period of time.

102. The method of claim 101 wherein the predicted future traffic flow measurements for a road for the one or more future periods of times are further based in part on current conditions that include multiple of current weather, current events that are scheduled to occur, current school sessions that are scheduled to occur, current traffic accidents on the road, and current construction activities on the road.

103. The method of claim 97 wherein the period of time is a future period of time, and wherein the determining of the one or more estimated measurements of actual traffic flow on a road during the period of time includes predicting the one or more estimated actual traffic flow measurements so as to reflect actual traffic that will occur on that road during the future period of time.

104. The method of claim 97 wherein the automatic assessing of the obtained data samples for a road includes analyzing the mobile data source data samples of the obtained data samples to determine information about at least one of speed and direction of movement of the one or more mobile devices moving along that road.

105. The method of claim 97 wherein the obtained plurality of data samples further include one or more road traffic sensor readings that are generated by one or more road traffic sensors associated with the one or more roads, the one or more road traffic sensors including at least one of an embedded loop sensor, a camera, a radar ranging device, a motion sensor, and an RFID-based sensor to detect RFID-based tags in vehicles.

106. The method of claim 97 wherein the one or more mobile devices moving along the one or more roads each includes at least one of a device with GPS capabilities and of a device with cellular telephone transmission capabilities.

107. The method of claim 97 wherein the determined estimated actual traffic flow measurements for a road during the period of time include one or more estimates of speeds of vehicles traveling on that road during the period of time.

108. The method of claim 107 wherein the determined estimated actual traffic flow measurements for a road during the period of time further include multiple of one or more estimates of a traffic arrival rate volume for that road during the period of time, of one or more estimates of traffic density for that road during the period of time, and of one or more estimates of percentage traffic occupancy of at least one point on that road during the period of time.

109. The method of claim 97 wherein the one or more programmed computing systems are part of an automated traffic information system.

110. A non-transitory computer-readable medium whose contents configure a computing device to provide information related to vehicle travel on a road, by performing a method comprising:

receiving an indication of multiple data samples that reflect travel characteristics of one or more vehicles traveling on one or more roads, the multiple data samples including information reported by one or more mobile devices on the one or more roads at one or more times;

automatically analyzing the multiple data samples to determine one or more estimated measurements of traffic conditions on at least one of the one or more roads during a period of time, the automatic analyzing being performed by the configured computing device; and

providing one or more indications of the determined estimated traffic conditions measurements.

111. The non-transitory computer-readable medium of claim 110 wherein the multiple data samples further include information reported by one or more traffic sensors associated with the one or more roads.

112. The non-transitory computer-readable medium of claim 111 wherein the one or more traffic sensors include at least one of one or more embedded loop sensors, one or more cameras, one or more radar ranging devices, one or more motion sensors, and one or more RFID-based sensors.

113. The non-transitory computer-readable medium of claim 110 wherein the multiple data samples are reported from multiple distinct mobile devices moving along the one or more roads.

114. The non-transitory computer-readable medium of claim 113 wherein the multiple distinct mobile devices include at least one device with global positioning system (“

GPS”

) capabilities and at least one device with cellular telephone transmission capabilities.

115. The non-transitory computer-readable medium of claim 113 wherein the multiple distinct mobile devices are traveling in multiple distinct vehicles.

116. The non-transitory computer-readable medium of claim 110 wherein the providing of the one or more indications of the determined estimated traffic conditions measurements includes providing information about the determined estimated traffic conditions measurements to one or more users for use in facilitating travel by the one or more users on the one or more roads.

117. The non-transitory computer-readable medium of claim 110 wherein the method further comprises automatically determining to replace the determined estimated traffic condition measurements from the automatic analyzing with other determined estimated traffic condition measurements for the one or more roads during the period of time that are based at least in part on historical information about traffic conditions related to the one or more roads, and wherein the provided one or more indications are of the other determined estimated traffic condition measurements.

118. The non-transitory computer-readable medium of claim 117 wherein the historical information is based on at least one of historical traffic sensor readings from one or more traffic sensors associated with the one or more roads and of historical mobile data source data samples reported by one or more mobile devices that previously moved along the one or more roads.

119. The non-transitory computer-readable medium of claim 110 wherein the method further comprises:

automatically determining estimated traffic condition measurements for the one or more roads during a second period of time based at least in part on historical information about prior traffic conditions for the one or more roads; and

providing one or more indications of the determined estimated traffic condition measurements for the one or more roads during the second period of time.

120. The non-transitory computer-readable medium of claim 110 wherein the contents are instructions that when executed program the configured computing device to perform the method, and wherein the computer-readable medium is a memory of the configured computing device.

121. A computing device configured to provide information related to vehicle travel on a road, comprising:

a processor;

a first module configured to, when executed by the processor, and for one or more roads and each of multiple periods of time, automatically analyze multiple data samples that reflect vehicles traveling on the one or more roads during the period of time in order to determine one or more estimated measurements of traffic conditions on at least one of the one or more roads during the period of time, the multiple data samples including at least one data sample based on information reported by one or more mobile devices moving along the one or more roads during the period of time; and

a second module configured to, when executed by the processor, provide one or more indications of at least some of the determined estimated traffic conditions measurements.

122. The computing device of claim 121 wherein at least one of the multiple periods of time is a future period of time, and wherein the determining of the estimated traffic conditions measurements for the one or more roads during each of the at least one future periods of time includes predicting future traffic conditions on the one or more roads for the future period of time based in part on current traffic conditions on the one or more roads.

123. The computing device of claim 121 wherein the first and second modules each includes software instructions for execution by the processor.