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USE OF STATE FLEET VEHICLE GPS DATA FOR TRAVEL TIME ANALYSIS
David P. Racca
Center for Applied Demography and Survey Research (CADSR)University of DelawareGraham Hall, Rm 284, Newark, Delaware 19716Phone: (302) 831-1698E-mail: [email protected]
State of Delaware Public Vehicle GPS Data
• About 2400 vehicles broadcasting location every two minutes.
• 2 million point measures per month• Providing 5 to 10 million travel way measures per
month• Does not include public safety, transit buses, or
road maintenance vehicles.• 40% passenger cars, 34% passenger vans, 23%
pickups and SUVs• Data as far back as year 2007
An Opportunity to Develop a StatewideTravel Time / Speed Survey
• Besides safety measures, travel time and speed throughout the day is the most important performance measure
• Addresses roads large and small• Collection costs already covered• Includes detailed trip data allowing for
analysis of turning movement statistics
State Vehicle GPS Measurements
State Vehicle GPS MeasurementsSample Trip
Northern New Castle CountyWeekday Observations2012 to 2013
Sussex CountyWeekday Observations 2012-2013
Hourly 8am Observations
Processing• Capture historical GPS data by querying Networkfleet
web services for Delaware vehicles.• Process GPS XML response data• Create GPS point databases and GIS files• Extract and associate GPS points with particular trips
taken through time• Build a trip and link based version of the GPS data
- Estimate the path taken between GPS readings- Associate speed measures with a particular road
link, direction, and tuning movement• Screen the data for errors and anomalies.
The primary issues associated with traffic data and managing it and processing it in GIS are:
• Travel flow. Most of the data is directional• Standard and effective ways of referencing traffic data
to models of the transportation network• Integrating data of different spatial types, point, line, and
polygon. Examples: speed probe data, capacity data, device counters, travel demand
• Integration of data from different time dimensions. Dealing with large volumes of data. Aggregation and disaggregation.
• Integrating across various portions of the transportation network.
Desired Features For Referencing Traffic Data• is related to an established standard• can reference the smallest portions of road as well as
the largest• is not dependent on a particular cartographic source • can relate data from various sources and measurement
schemes• can be generalized to relate information about small and
large road segments• can capture the direction of traffic flow. Traffic data for a
particular portion of road is directional• Provide a fixed identifier for use by those who cannot
work with advanced DBMS or linear referencing systems (route and mile point)
Identification illustration
To relate a measure to a particular turning movement a “S”, “L”, “R”,or “U” is appended to the LRSID, for example. Left turn fromSudlers Row LRSID = 0006160176000000L
Sample Output
Weekday Hourly
“S” Straight or Thru Shown
Also available are Right & Left
Segments statewide included
Example Detail Captured for Road Links
Routing network is segmented at every major or minor intersection
Comparison of Segment Length, VehGPS vs NPMRDS
NPMRDS Data
State Vehicle GPS Data
Comparison of Coverage, State GPS vs NPMRDS
For State GPS Weekday 2012-2013, NPMRDS in Black
Comparison of Coverage, State GPS vs NPMRDS
For State GPS Weekday 2012-2013, NPMRDS in Black
Summary of Features of the State Vehicle GPS
• Data available for up to 6 past years• Wide coverage, data for small and large roads• Captures speeds and travel times relative to turning
movement• Measures available at great detail, road link breaks at
all intersections, large and small • Delay at intersections by turning movement ,
incorporated into road link speed / travel times. Ideal for generation of time sensitive routing network impedance.
• Cost of collection covered in existing program
Aggregations
Over 100 million measurements each year availablefor very detailed road segments throughout the Statecreates a large data set that requires aggregations toexamine conditions with respect to various factors ofinterest. These factors include:
• Time of day intervals, i.e. 30 minute, 60 minute intervals• Periods of the day, AM Peak, Midday, PM Peak, Evening • Day of week• Season, i.e Summer or Non-Summer• Holiday, non-Holiday• Year
Aggregation By Road Segment
Calculation of Free Flow Speed as the 75 percentileOf Hourly Averages (just major roads shown)
Calculation of Percent Degradation at 8am, weekdaysPercent degradation = 100 * (freeflow75 – speed) / freeflow75Calculated from weekday hourly averages
Calculation of Percent Degradation at 8am, weekdaysPercent degradation = 100 * (freeflow75 – speed) / freeflow75Calculated from weekday hourly averages
Travel Time Reliability
Intersection Study
Left turns that are most effected ( > 40% degradation) by morning (8am) congestions
Other potential applications
• Establishment of a statewide routing networkpopulated with DOW, time of day, impedances
• Before and after studies, land use and facility changes• Examining delay at intersections • Estimations of capacity and studies of volume speed
relationship• Relating traffic flow to land use and travel demand• Multimodal studies• Applications of a detailed time sensitive routing
network, such as accessibility studies
Some observations• Little experience in general working with this
kind of data. Capabilities with huge amounts of traffic data are often lacking.
• the data accurate? Can we trust it? What accuracy do we need?
• How does it compare to other sources? • Number of measures• Resolution• Time of Day, Day of Week, Season• Turning movement
• Different data sets may measure differently• Value depends on intended use. Corridor performance?
congestion at intersections, effects of land use?
Blue Tooth Locations
Blue Tooth Travel Times by Hour of the Day Station 3 to Station 4, Sussex County
Blue Tooth Compared to Fleet GPS Estimates
Other CADSR Work
• Travel surveys• Development of internet mapping and data query• Population, employment, and housing projections and
allocations• Accessibility studies• Markets for transit• Environmental and land use studies• Place and address files• Network modeling and routing