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An Analysis of 2000 IH-35 Traffic Composition and Reassignment Solutions
Performed by:Manager: Caleb Kraenzel
Assistant Manager: Georgia ApplemanWebmaster/Analyst: Robert Roberts
Analyst: Stephen LeClairAnalyst: Matthew Manske
Analyst: Amanda Neal
Overview• Purpose• Scope• Primary Data• Results
– Traffic Density & Congestion– Freight Traffic– Commuter Traffic– Overall Composition
• Solutions• Conclusion
Purpose
• Determine the composition of the traffic on IH-35.
– What amount of the overall traffic is freight? Commuter? Miscellaneous?
• Knowledge of traffic composition can aide in the planning of solutions to help alleviate congestion.
Scope
Primary study area:Hays & Williamson County traffic input into Travis County.
The secondary study area :consists of Caldwell, Guadalupe, Comal, and Bexar County.
Primary Data Sources• CTPP data
– Journey to Work Commuter Tables
• Statewide Analysis Model (SAM)– Mined necessary data and layers from SAM for analysis
• Projection- State Plane Texas Central 4203
• Spatial Units used in analysis– Traffic Analysis Zone (TAZ)– County Level
Statewide Analysis ModelAnalyst Interface• Unable to use for spatial analysis
– Due to limitations of the software– Due to limitations of hardware
• Forced to revise methods• Broad data arrays in relational data bases
enabled us to conduct data driven analysis to complete project goals.
Congestion
• Analysis performed displayed differing areas of congestion along IH-35
• IH-35 becomes highly congested between Slaughter Lane and William Cannon Drive.
• Stays congested through Travis County
Freight Traffic MethodologyAssign sequential highway segment numbers from north to south on IH-35 in Williamson, Travis, and Hays County.
Sort by segment number
Select segments closest to county boarders with complete data record sets.
Compare results with the TxDOT IH35/SH130 Truck Diversion report
Add fields and calculate:
Truck_BA, %ComboTruck_AB, %ComboTruck_BA, EstTruck_AB, EstTruck_BA, EstTruck_AB25, EstTruck_BA25
Commuter Traffic Methodology
HIGHWAYSIH-35US 290US 183SH-95TAZ.SHP
SUMMERIZE CTPPSUMMERIZE CTPP
SUM TAZ SHAPEFILES
•Hays County TAZs•Williamson County TAZs
•Secondary Study Area TAZs
+
•Distance Determined Hays TAZs
•Distance Determined Williamson TAZs
SPATIAL ANALYST•Euclidean Distance•Reclassify•Raster Calculator•Convert to Polygon
Distance Buffer.shp+
Overall Composition 2000
YEAR 2000: IH-35 TRAFFIC COMPOSITION ENTERING TRAVIS COUNTY
Miscellaneous *239,537
63%
Freight 39,490
10% Commuters to Work
105,64227%
*Miscellaneous includes all traff ic that is not freight or commuters to w ork
COMPOSTION 2025YEAR 2025: IH-35 TRAFFIC COMPOSITION ENTERING TRAVIS COUNTY
Miscellaneous *625,440
56%
Freight63,754
8%
Commuters to Work
425,86438%
*Miscellaneous includes all traffic that is not freight or commuters to work TRAFFIC COUNT INCREASE FROM 2000 TO 2025
0
150,000
300,000
450,000
600,000
750,000
900,000
Commuters to Work Freight Miscellaneous*
traffic type
traf
fic
cou
nt
2025
2000
Errors and Variables
• Traffic variability on a daily basis must analyzed on an annual basis and/or average.
• Incomplete SAM data, missing data fields or error laden data entry.
• CTPP based sampling of 1 out of 6 long form census surveys containing commuter questions.
• Miscellaneous traffic could adversely effect percentage of freight or work-commuter percentages.
Solutions• Traffic Reassignment
– Street Network with weights assigned to roads
• Transportation Alternatives
• Legislative Solution
• Loop system Solution
Transportation Alternatives
• Each alternative removes drivers and their cars from the roadway and puts them into another mode of transport.
– Bus Systems
– Commuter Rail
Commuter RailCould remove up to
an estimated 8,500 commuter trips per day from IH-35 traffic. In 2025 trip totals are expected to double (17,000) commuter trips a day.
Loop System
• The following solution was determined to be a potential alternative to alleviate traffic along IH-35 between San Antonio and Austin.
Conclusion
• Overall Composition
• Solutions
• Further Analysis– Any other analysis would require much more
data, sources, man power and time. Traffic is a never-ending equation.
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