Method of Verifying or deriving Attribute Information of a Digital Transport Network Database Using Interpolation and Probe Traces

• US 20120246192A1
• Filed: 12/31/2009
• Published: 09/27/2012
• Est. Priority Date: 08/03/2009
• Status: Active Grant

• Current Assignee: Tomtom Global Content B.V (TomTom NV)
• Original Assignee: Tomtom Global Content B.V (TomTom NV)
• Inventors: Kenyon, Shaundrea Margaret Newman
• Granted Patent: US 9,291,463 B2
• Time in Patent Office: Days
• US Class Current: 707/769
• CPC Class Codes: G01C 21/30 Map- or contour-matching
• CPC Class Codes: G01C 21/3819 Road shape data, e.g. outline of a route
• CPC Class Codes: G01C 21/3841 Data obtained from two or more sources, e.g. probe vehicles
• CPC Class Codes: G01C 21/3844 Data obtained from position sensors only, e.g. from inertial navigation
• CPC Class Codes: G06F 11/00 Error detection; Error correction; Monitoring error detection, correction or monitoring in information storage based on relative movement between record carrier and transducer G11B20/18; monitoring, i.e. supervising the progress of recording or reproducing G11B27/36; in static stores G11C29/00
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring

Abstract

A method of verifying or filling in attribution associated with segments of transportation networks that are digitally mapped from a digital transportation network database includes analyzing the database to identify at least one attribute of interest that is missing or whose accuracy is unreliable and associated with a segment of the network in; identifying first and second segments before and after segment in question which have associated attribution determined to be accurate; gathering a plurality of probe traces from users of probe-transmitting navigation devices that have traversed the segment(s) in question as well as traversed the first and second; and determining whether the probe-derived attribution information is reliable, and if so, comparing the trend of the probe-derived attribute information of the first and second segments with the trend of the database attributes of the first and second segments, and if there is a positive correlation, applying the probe-derived attribute information to the database for the segment(s) in question to fill in the missing or verify the unreliable database attribution for the segment(s) in question.

Claims

1. A method of verifying or filling in attribution associated with segments of transportation networks that are digitally mapped from a digital transportation network database, said method comprising:

analyzing the database to identify at least one attribute of interest that is missing or whose accuracy is unreliable and further identifying at least one segment in question of the transportation network with which the attribute of interest is associated;

further analyzing the database to identify a first segment of the transportation network and a second segment of the transportation network, wherein the first segment is immediately preceding and connected to a front end of the at least one segment in question and the second segment is immediately succeeding and connected to a back end of the at least one segment in question, and further wherein the first and second segments have associated attribution of interest that is determined to be accurate;

gathering a plurality of probe traces from users of probe-transmitting personal navigation devices that have traversed the at least one segment in question as well as traversed the first and second segments on either side of the at least one segment in question, wherein the probe traces include probe-derived attribute information; and

determining whether the probe-derived attribution information is reliable, and if so, comparing the trend of the probe-derived attribute information of the first and second segments with the trend of the database attributes of the first and second segments, and if there is a positive correlation, populating the attribution from the first and second segments based on correlation to the database for the at least one segment in question to fill in the missing or verify the unreliable database attribution for the at least one segment in question.

2. The method of claim 1, wherein the gathered probe traces are statistically averaged over the length of the respective segments to derive a mean probe trace associated with each of the first and second segments and the at least one segment in question.

3. The method of claim 2, wherein depending on the characteristics of the attribute of interest, determining either a) the value of the attribute for each segment, or b) the value of an indicator that is functionally related to the attribute of interest.

4. The method of claim 2, wherein the attribute of interest includes any one of:

posted speed, average speed, time-of-day based speed zones, roadway centerline location or positional accuracy, one-way traffic indications, stop signs and traffic lights.

5. The method of claim 2, wherein the attribute of interest is average speed, and the statistically averaged mean probe traces provide an average speed attribute that is correlated against the database applied speed attribution to confirm that the database applied speed attribution can be populated thru the gap or given higher confidence in the database.

6. The method of claim 2, wherein the attribute of interest is one of posted speed, time-of-day based speed zone, or one-way indication, and further wherein the statistically averaged mean probe traces provide an average speed value or travel direction value which are indicative of the posted speed, time-of-day based speed zone or one-way indication, or spatial location and determining the proportional function which converts the meant probe trace value to the probe-derived attribute value associated with either posted speed, time-of-day based speed zone, centerline position and shaping or one-way indication, and using correlation to existing database attribution to propagate attribution on the at least one segment in question to the database.

7. The method of claim 1, wherein if it is determined that the probe-derived attribution information is unreliable across the at least one segment in question, but still determined to be reliable across the first and second segments, and wherein the attribute of interest is posted speed or geometry position and accuracy across the at least one segment in question, then determining further whether the posted speed attributes stored in the database for the first and second segments are substantially the same value within specified limits, and if they are, determining whether the ratios of average speed across the first and second segments derived from the probe trace information versus the posted speed of the first and second segments, respectfully, are substantially that same value within specified limits, then calculating a posted speed attribute value for the at least one segment of interest based on the average of the posted speed attribute values of the first and second segments.

8. The method according to claim 1 wherein the steps are performed with the assistance of a computer and wherein the data are digital transformations of physical roadway attributes.

9. A method of verifying or filling in attribute information of a digital transportation network database, comprising:

identifying at least one attribute of interest in the database that is either missing or unreliable and matching the attribute of interest with a segment of the transportation network in question having associated therewith a first segment immediately preceding the at least one segment in question and whose database attribution is deemed reliable and further associated therewith a second segment immediately succeeding the at least one segment in question and whose database attribution is also deemed to be reliable, and wherein the first and second segments and the at least one segment in question are all part of an extended section of a common transportation network;

reporting data from a plurality of probe transmitters tracking across both of the first and second road segments and also across the at least one segment in question, the reported data including attribute information;

comparing the probe-derived attribute information of the first and second road segments with the attributes stored in the database for the first and second segments and if there is a positive correlation, updating the database by assigning the probe-derived attribute information to the database for the at least one segment in question.