Processing GPS Data from Processing GPS Data from Travel SurveysTravel Surveys
Peter Stopher and Camden Peter Stopher and Camden FitzGeraldFitzGerald
Institute of Transport and Logistics Institute of Transport and Logistics StudiesStudies
The University of SydneyThe University of SydneyQingjian JiangQingjian Jiang
Parsons Brinkerhoff Australia Pty Parsons Brinkerhoff Australia Pty Ltd.Ltd.
IntroductionIntroductionConsiderable recent growth in
applications of GPS in transportCapability of producing huge data
streamsNeed for custom software to interpret
and use the dataDescription of 4 data processing
applicationsDescription of 2 data analysis steps
ContextContextUse of a GIS base for display and
analysisOur selections is TransCAD®
Use of developer tools in TransCAD®: GISDK ®
Equipment used:GeoStats GeoLogger (in-vehicle and
wearable)Neve StepLogger (wearable)
Application 1: Application 1: Converting to Trip Converting to Trip
RecordsRecordsData must first be reformatted
to match input specifications of TransCAD®
Data are usually in one of the standard NMEA streams
GeoLogger and StepLogger provide slightly different data streams
GeoLogger Data StreamGeoLogger Data Stream
VALID LATITUDE
HEMI-SPHERE LONGITUDE
HEMI-SPHERE
UTC TIME
UTC DATE
SPEED (KPH)
HEAD-ING
ALTI-TUDE HDOP
SATEL-LITES
V 33.89243 S 151.19162 E 50655 190202 0 0 43 2.4 3A 33.89237 S 151.19165 E 50658 190202 20 23 43 2.4 3V 33.89205 S 151.19153 E 50703 190202 0 0 43 2.4 0A 33.8916 S 151.19128 E 50708 190202 40.2 340 43 2.4 3V 33.89112 S 151.19105 E 50713 190202 0 0 43 2.4 0A 33.89077 S 151.19088 E 50718 190202 28 324 43 2.4 3A 33.8904 S 151.1906 E 50723 190202 35.4 327 43 2.4 3A 33.88993 S 151.19023 E 50728 190202 45.9 326 43 2.4 3A 33.88963 S 151.19005 E 50733 190202 19.3 351 43 2.4 3A 33.8893 S 151.19028 E 50738 190202 39.9 41 44 2.4 4A 33.88895 S 151.1908 E 50743 190202 45.9 53 42 2.4 4A 33.88863 S 151.1914 E 50748 190202 45.2 58 42 2.4 4A 33.88832 S 151.19198 E 50753 190202 45.5 57 43 2.4 4A 33.88797 S 151.19262 E 50758 190202 55.3 51 43 2.4 4A 33.88747 S 151.19325 E 50803 190202 57.9 43 42 2.2 4
StepLogger Data StreamStepLogger Data StreamValid Date Loc Time Longitude Latitude Altitude Heading Speed Satellites HDOPA 23/04/2005 0:56:50 138.6184 -34.80916 -3 145 1 5 2.3A 23/04/2005 0:56:56 138.6184 -34.80916 1 8 1 6 2A 23/04/2005 0:57:07 138.6184 -34.80909 5 80 1 6 1.5A 23/04/2005 0:57:08 138.6184 -34.80908 5 316 1 5 2.2A 23/04/2005 0:57:12 138.6184 -34.80908 6 118 1 6 2A 23/04/2005 0:57:13 138.6184 -34.80908 6 106 2 6 2A 23/04/2005 0:57:14 138.6184 -34.80908 7 90 4 6 2A 23/04/2005 0:57:15 138.6185 -34.80908 7 90 4 6 2A 23/04/2005 0:57:16 138.6185 -34.80908 8 92 4 6 1.6A 23/04/2005 0:57:17 138.6185 -34.80908 8 95 4 6 2A 23/04/2005 0:57:18 138.6185 -34.80909 9 92 5 5 1.6A 23/04/2005 0:57:19 138.6185 -34.80909 9 86 5 8 1A 23/04/2005 0:57:20 138.6185 -34.80908 9 87 5 5 1.9A 23/04/2005 0:57:21 138.6186 -34.80908 8 99 6 6 1.4A 23/04/2005 0:57:22 138.6186 -34.80908 8 103 6 8 1A 23/04/2005 0:57:23 138.6186 -34.80909 8 92 5 5 2.2A 23/04/2005 0:57:24 138.6186 -34.8091 7 93 4 6 2A 23/04/2005 0:57:25 138.6186 -34.8091 7 98 5 5 1.9A 23/04/2005 0:57:26 138.6187 -34.80911 7 102 5 8 1A 23/04/2005 0:57:27 138.6187 -34.80911 8 100 6 8 1A 23/04/2005 0:57:28 138.6187 -34.80912 8 92 5 6 2A 23/04/2005 0:57:29 138.6187 -34.80912 8 97 5 6 2A 23/04/2005 0:57:30 138.6187 -34.80912 8 94 5 7 1.3A 23/04/2005 0:57:31 138.6188 -34.80913 8 93 5 5 3A 23/04/2005 0:57:32 138.6188 -34.80913 8 89 5 5 1.6
Differences and Differences and SimilaritiesSimilarities
Both record latitude and longitudeGeoLogger includes hemisphereStepLogger uses plus and minus
Both record date and timeGeoLogger is UTCStepLogger converts to local
Both record altitude (not used), speed, and heading
Similarities and Similarities and DifferencesDifferences
Both record HDOP and number of satellites in viewNumber of satellites – 3 is minimum
for 2D solution and 4 for 3DHDOP is horizontal dilution of
precision – larger values indicate poor quality of data (little dispersion of satellites)
Processing DataProcessing DataCalculate local time and local dateCorrect latitude and longitude and
remove hemisphere designations (when necessary)
Calculate:Distance from previous record, using
latitude and longitudeTime in seconds based on zero seconds at
midnightElapsed time from the previous recordActual date in date format and day of
week
Remove Invalid PointsRemove Invalid PointsAll data points with too few (less than
three) satellites in view and/or a value of HDOP of five or greaterExcept for the first occurrence of such
data points in any group of data points of this type
Any data points where no movement is recorded based on: Speed of zeroLess than a 15 metre (0.00005º) change
in either latitude or longitudeHeading being zero or unchanged
Trip DetectionTrip Detection Detect a trip end when:
Ignition has been turned off (in-vehicle device only) Ignition has not been turned off (in-vehicle device
only) Direction is reversed, but there is a very short or
non-detectable stop Detect a trip end from wearable data, where
the device is always on Determine whether a trip ended and a new
one started during a period of signal loss Determine whether there is a loss of signal at
the beginning of a trip and repair the data record
Trip Detection Trip Detection HeuristicsHeuristics
The difference in successive latitude and longitude values is less than 0.000051 degrees AND
The heading is unchanged or is zero AND
Speed is zero ANDElapsed time during which these
conditions hold is equal to or greater than 120 seconds
If ignition is turned off for in-vehicle for 30-120 seconds – probable trip end
Trip Ends for Trip Ends for Wearable DevicesWearable Devices
The GeoLogger works as for the in-vehicle device
The StepLogger requires different logic, because zero speeds are not recordedDefines a Stop Point Set when there is a
group of records within 30 metres of each other
When the Stop Point Set lasts at least 120 seconds, it becomes a potential trip end
When a new point falls outside this set, a new trip is assumed to have started
Completion of Trip Completion of Trip RecordsRecords
Once trip ends have been detectedAll other manipulations of the data are
completedElapsed time and distance for the trip
are obtainedEach trip is given a trip numberEach point in the trip is given a new
sequence number
Application 2: Application 2: Correcting “Cold Start” Correcting “Cold Start”
ProblemsProblemsThese occur when there is a delay in
position acquisition at the start of a trip
For both wearable and in-vehicle devices, this may result in a missed trip, when the trip is short
If acquisition occurs within 100 metres, this is not considered to be a problem
Identification of the Identification of the ProblemProblem
Determine the distance between the start of this trip and the end of the previous one If less than 100 metres, no action is
requiredDetermine in which zone the trip
end liesZone I is the Sydney CBD and
surroundingsZone II is the rest of the metro area
Correction ProcessCorrection ProcessCompute the average speed of the
last 10 records and the first 10 records of the new trip
Using these speeds and the look-up tables for gap speed, we determine a speed for the gap
Compute the distance for the gapUses straight line distance for under
150 metresUses minimum time path distance with
end corrections for longer distances
Time EstimationTime EstimationUsing the speed and distance from
the previous steps, determine the time taken
Trip time also adds in an average amount of terminal time for either Zone I or Zone II
This process works for car tripsA procedure for other trips is still
being developed
Application 3: Signal Application 3: Signal LossLoss
Signal loss occurs in urban canyons, under heavy tree canopies, in tunnels, and in some public transport vehicles
Two issues:Has a stop occurred while the signal
was lost? What path was traversed while the
signal was lost?
Non-Car DataNon-Car Data If the gap occurs in data where the
GPS is NOT in a carDetermine the location of the point of
signal loss and the point of signal resumption
Determine if there is a rail, bus, or ferry path that connects the two
Determine if the connecting path is reasonable for the time between signal loss and signal resumptionIf it is reasonable, then interpolate the route
Data from an Urban Data from an Urban CanyonCanyon
Sydney CBD – Urban Canyon
Car DataCar Data Use the preceding 10 records and following
10 records to compute average speeds Connect the last point before and first
after with a minimum time path Estimate the implied speed along the
minimum time path, given distance and elapsed time
Compare this to the average speed for the last 10 and first 10 records either side of the gap If implied speed is less than 50 percent of
average speed, then assume a stop has occurred
Application 4: Application 4: Displaying the DataDisplaying the Data
After completing processing, trips from one day are stored in one file
For each day, each trip within the day receives a distinct colour code for the day
Trips are converted to solid lines, which are drawn on maps offset, so that each trip on a given link can be seen separately
A table is also created giving primary information about the trip
Raw Data DisplayRaw Data Display
Processed Data DisplayProcessed Data Display
Determining ModeDetermining ModeBegins with defining walk trips
Average speed maximum of 6 km/h and maximum speed of 10 km/h
Also, may not follow street system, especially where parks and open spaces occur
Next, define public transport tripsUsually follow a walk tripMay also be followed by a walk tripAverage speed in the range of 10-40
km/h
Determining ModeDetermining Mode If trip either disappears, or follows
entirely a public transport route, it is defined as public transport Identification of rail is usually made
from station boarding and disappearance of GPS signal
Identification of bus is usually made from speed and route
Remaining trips are bicycle or carDetermined principally by average
speeds
PurposePurposeUses address data collected at
recruitmentWorkplacesSchoolsGrocery stores
Requires a GIS of land use by parcelTrip purposes are identified from
known locations for work, education, and shopping
Other purposes are defined by the land uses
Processing and Data Processing and Data ManagementManagement
All the preceding steps are accomplished in about 2 hours for one week of GPS data
A folder is defined for each device for each householdAll files created for that device are
stored in that folderFiles can be examined at various
intermediate points for review
ConclusionsConclusionsProcessing steps identify about
95 percent of trip ends correctlyData gap repair (cold starts and
tunnels/canyons, etc. are found to be very successful
Mode and purpose identification is about 95 percent
Fully automated processing is still not completely possible
Future DirectionsFuture DirectionsCurrent processing has reduced
the time required for processing to about 25 percent of initial time requirements
Future potentials for better identification of cold starts/canyons, mode, and purpose from fuzzy logic