Embed Size (px)
DESCRIPTION
Sonoma Marin Area Rail Transit (SMART). Analysis on the Effectiveness of the Proposed Rail System. MS&E 220 – Probabilistic Analysis Fall 2008 – Professor Samuel Chiu Prepared By: Samuel Gambrell Paul Jones David Williams December 4, 2008. Overview. - PowerPoint PPT Presentation
Citation preview
Sonoma Marin Area Rail Transit (SMART)
Analysis on the Effectiveness of the Proposed Rail System
MS&E 220 – Probabilistic AnalysisFall 2008 – Professor Samuel Chiu
Prepared By:Samuel GambrellPaul JonesDavid Williams
December 4, 2008
Overview
• This analysis will examine the probabilities related to making a decision on whether to support the Sonoma Main Area Rail Transit system
• This includes:– Creating a decision analysis tool – Examining input probabilities to the model
• Ridership• Costs & Revenue
Decision Analysis
• This process used decision trees, to structure the probability inputs
• Values of different outputs are assigned by the user
• Feedback on whether they should or should not support the decision is provided
• So is a measure of how much change is required for them to change their position
Decision Tree: Yes or No to the TrainValue Measure U-Value
0.39 Costs overrun >15 %20 20
Daily trips reduced0.25 15,403 0.29 Costs delta <>15%
25 2524.6104
0.31 Cost underrun of >15%30 30
0.39 Costs overrun >15 %10 10
Build SMART Train 0.5 11,210 0.29 Costs delta <>15%15 15
14.0709 14.6104
0.31 Cost underrun of >15%20 20
0.39 Costs overrun >15 %0 0
16 0.25 7018 0.29 Costs delta <>15%3 3
2.45226
0.31 Cost underrun of >15%5 5
>>> Do not build SMART Train16 16
Value from UserCosts Relative value
Greater than 87,184,492 Greater than 15,403 Costs overrun >15 % 20Greater than 87,184,492 Greater than 15,403 Costs delta <>15% 25Greater than 87,184,492 Greater than 15,403 Cost underrun of >15% 30around 63,453,133 around 11,210 Costs overrun >15 % 10around 63,453,133 around 11,210 Costs delta <>15% 15around 63,453,133 around 11,210 Cost underrun of >15% 20Less than 39,721,774 Less than 7,018 Costs overrun >15 % 0Less than 39,721,774 Less than 7,018 Costs delta <>15% 3Less than 39,721,774 Less than 7,018 Cost underrun of >15% 5
Relative value of 1/4 percent sales tax 16
Reduced cars on 101Pounds of GW gas reduced
Recommended Decision
If your prefence for saving the 1/4 % of sales tax changed by the value below, your preference would change
Vote against the train -1.929144516
Results and change of preference required to alter position
RIDERSHIP PROJECTIONS
Distance between Santa Rosa Stations = 1.18 milesTotal area of Santa Rosa within 1 mile of train station is = 5.36 square miles (see spreadsheet for calcs)
Population Density for Santa Rosa = 3844 people per square mileSanta Rosa Residents within 1 mile of SMART station is = 3,844 x 5.3564 = 20590
Population within 1 mile of station
Larkspur
San Rafael (2)
Novato (2)
Petaluma (2)
Cotati
Rohnert Park
Santa Rosa (2)
Windsor
Healdsburg
Cloverdale
0 10000 20000 30000
11721
21074
11812
24812
12001
19792
20590
11787
9114
10166
Population within 1 mile of SMART Station
Calculation for Santa Rosa (special case overlapping station radii) Commuters within 1 mile of station are
significantly more likely to use SMART
Low Projection:Assessed Ridership Conditioned on
Proximity to Station and Commuter Status
High Projection:Assessed Ridership Conditioned on
Proximity to Station and Commuter Status
A.
B.C. D.
Scenario Gas PriceRegular [$/gal.]
Projected Riders
Ridership as % of target Max of 6,200 riders
A. $0 per gallon equates to zero riders*** 0.00 0 0.00 %
B. June 2006 (actual)**** 3.21 5000 80.6 %
C. Hypothetical Case 1 * 5.00 5750 92.7 %
D. Hypothetical Case 2 * 6.00 5950 96.0 %
E. Maximum Target Riders ** Infinity 6200 100.0 %
E.
Projected Riders vs. Gas Price
Ridership Projections
SMART Project Cost
Sales Tax Growth
• Obtained Taxable Income from Sales for 1998 thru 2007 through California BOE
• Due to the complexity and uncertainties of a financial model a normal curve was used with the mean and SD of historical data to predict growth
• Dynamic equations were used to predict Taxable Income till 2029
Probability of Taxible Sales Income in Sonoma and Marin Counties
0
0.2
0.4
0.6
0.8
1
1.2
0 6 12 18 24 30 36 42 48 54 60 66 72 78 84
Taxible Sales Income in Billions
Prob
abili
ty
20072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029
Probability of Accumulative Gain from Tax for Each Year
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
$0.00
$65,0
00,00
0.00
$130
,000,0
00.00
$195
,000,0
00.00
$260
,000,0
00.00
$325
,000,0
00.00
$390
,000,0
00.00
$455
,000,0
00.00
$520
,000,0
00.00
$585
,000,0
00.00
$650
,000,0
00.00
$715
,000,0
00.00
$780
,000,0
00.00
$845
,000,0
00.00
$910
,000,0
00.00
$975
,000,0
00.00
$1,04
0,000
,000.00
$1,10
5,000
,000.00
$1,17
0,000
,000.00
$1,23
5,000
,000.00
$1,30
0,000
,000.00
$1,36
5,000
,000.00
$1,43
0,000
,000.00
$1,49
5,000
,000.00
Total Gain from 1/4 Cent Tax
Prob
abili
ty200920102011201220132014201520162017201820192020202120222023202420252026202720282029
Probability of Income from 1/4 Cent Sales Tax
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
$750
,000,0
00.0
0
$770
,000,0
00.0
0
$790
,000,0
00.0
0
$810
,000,0
00.00
$830
,000,0
00.00
$850
,000,0
00.0
0
$870
,000,0
00.00
$890
,000,0
00.0
0
$910
,000,0
00.0
0
$930
,000,0
00.0
0
$950
,000,0
00.0
0
$970
,000,0
00.0
0
$990
,000,0
00.00
$1,01
0,000
,000.00
$1,03
0,000
,000.00
$1,05
0,000
,000.00
$1,07
0,000
,000.00
$1,09
0,000
,000.00
$1,11
0,000
,000.00
$1,13
0,000
,000.00
$1,15
0,000
,000.00
$1,17
0,000
,000.00
$1,19
0,000
,000.00
$1,21
0,000
,000.00
$1,23
0,000
,000.00
$1,25
0,000
,000.00
$1,27
0,000
,000.00
$1,29
0,000
,000.00
$1,31
0,000
,000.00
$1,33
0,000
,000.00
$1,35
0,000
,000.00
$1,37
0,000
,000.00
$1,39
0,000
,000.00
$1,41
0,000
,000.00
$1,43
0,000
,000.00
$1,45
0,000
,000.00
Income
Prob
abili
ty
Income predicted by SMART paper
Model vs Paper
• According to the model the paper has a 99.85% chance of making the predicted income from sales tax
Assumed IncomeTotal Gains Probability
Yes $11,376 $33,201 0.7290.9
Yes $2,4000.9 No $0 $21,825 0.081
0.1Yes $19,425
0.9 Yes $11,376 $30,801 0.0810.9
No $00.1 No $0 $19,425 0.009
0.1
Yes $11,376 $13,776 0.0810.9
Yes $2,4000.9 No $0 $2,400 0.009
0.1No $0
0.1 Yes $11,376 $11,376 0.0090.9
No $00.1 No $0 $0 0.001
0.1
State Transit AssistanceProgram Funds
Federal HighwayAdministration Funds NCRA Capital Offsets
Currently unable to find a source for an accurate probability.
Probability of a Cost Overrun
• Based on Transit systems built since 1994• Used to calculate the probability of a cost
overrun– Assumed normal
Study ResultsNumber of Projects 16Overage Overrun 30%Standard Deviation 39%
Translating this to the SMART ProjectTotal Cost with no buffer $1,081,076,800.00Total Cost with 20% buffer built in to the estimates $1,351,346,000Estimated mean cost $1,405,399,840Standard deviation $527,024,940.00
