An Application of Mitigating Flow Bias from Origin/Destination Surveys in a Transit System Jamie...
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Transcript of An Application of Mitigating Flow Bias from Origin/Destination Surveys in a Transit System Jamie...
An Application of Mitigating Flow Bias from Origin/Destination Surveys in a Transit System
Jamie Snow (AECOM)
David Schmitt (AECOM)
May 20, 2015
2015 TRB Planning Applications Conference
Addressing Flow Bias in Transit Surveys
• Accurate information on flows is critical in transportation planning
• Observation: Expansion methods using only the origin/ destination survey typically under-represent short trips and misrepresent flows– Difficult to know where the biases occur
• Can flows be made more accurate using auxiliary data and iterative proportional fitting (IPF) techniques?
May 20, 2015 Page 2
2015 TRB Planning Applications Conference
Advanced Expansion Process (AEP) Methodology
May 20, 2015 Page 3
Define route segmentation
Develop segment-to-segment on-to-
off flows using survey and
ancillary data
Develop origin/destination
segment-to-segment flows using survey
Divide on-to-off flows by
origin/destination flows
Create synthetic origin/destination
records where necessary
Apply expansion factors to main survey records
2015 TRB Planning Applications Conference
Define Route Segmentation
May 20, 2015 Page 4
• Segment the transit routes using– Natural boundaries– Major cross streets– Large differences in travel
patterns
• Local routes represented by 4-6 segments
• Express and crosstown routes represented by 2-3 segments
2015 TRB Planning Applications Conference
Develop On-to-off Flows
• Automatic Passenger Counter (APC) data– Averaged over 5 months – Used to generate the column and row marginals for IPF
• On-to-off counts– Collected at 20% or 100% sampling rate, depending on route– Used to generate the “seed” matrices for the IPF process– Developed synthetic records where APC and/or OD > 0 but
On-to-off = 0
• Use IPF to expand on-to-off counts– On-to-off counts as “seed” matrices– APC counts for row/column marginals– Result: segment-to-segment flows
May 20, 2015 Page 5
2015 TRB Planning Applications Conference
Using IPF to Develop Segment to Segment Flows
May 20, 2015 Page 6
Generated from the APC data by route, time period,
direction, and segment
Generated from the on-to-off data by route, time period, direction, and segment
Indicates the need for a Synthetic Record
2015 TRB Planning Applications Conference
• Initial expansion factors developed by dividing segment-to-segment flows expanded to APC values by segment-to-segment count of OD survey records
• Synthetic records developed in cells where On-to-off flows and/or APC > 0 but OD = 0
May 20, 2015 Page 7
Develop Origin/Destination (OD) Flows
2015 TRB Planning Applications Conference
Origin/Destination Expansion Example
May 20, 2015 Page 8
Performed by direction and time period for each route
* Synthetic OD survey records developed where the observed flow > 0 but count of main survey records = 0
Segment-to-segment flows expanded to APC values
Segment-to-segment
expansion factors
Segment-to-segment count of
OD survey records *
*Synthetic origin/destination survey record
2015 TRB Planning Applications Conference
Is AEP Better Than Traditional RTD Expansion?
• Traditional expansion: route, time period, and direction using OD survey only (RTD)
• Objective: compare AEP results to traditional expansion results using APC data as the “ground truth”
• Metrics• Mean Absolute Percent Error (MAPE)• Root Mean Square Error (RMSE)
• Three COTA routes• Local Route 1 (large – 8,800 daily boardings)• Crosstown Route 89 (medium – 1,000 daily boardings)• Express Route 61 (small – 150 daily boardings)
May 20, 2015 Page 9
2015 TRB Planning Applications Conference
Comparison Results – Local Route 1
May 20, 2015 Page 10
Average Daily Ridership = 8,824
Expanding the data using RTD produces
mean absolute percentage errors that are 3-5 times
higher than expanding the data
with the AEP
Similarly root mean square errors are 2-4
times higher expanding the data
using RTD
7 segments
2015 TRB Planning Applications Conference
Comparison Results – Route 89
May 20, 2015 Page 11
Average Daily Ridership = 999
Similar to Route 1, AEP expansion has
less MAPE than RTD. Less segmentation of
the route begins to close the gap between
expansion methods
RMSEs are closer but AEP methodology still
drastically outperforms RTD
expansion
3 segments
2015 TRB Planning Applications Conference
Comparison Results – Route 61
May 20, 2015 Page 12
Average Daily Ridership = 139
Again, AEP outperforms RTD expansion when comparing MAPE
When the minimal number of segments are utilized, RMSE for both methodologies are very similar
2 segments
2015 TRB Planning Applications Conference
Results Continued
AEP methodology addresses flow movements better using number of segments traveled; minimizes short trip bias
May 20, 2015 Page 13
2015 TRB Planning Applications Conference
EF=0 0-0.4 0.4-1.0 1.0-2.0 EF>2.0
Total # of Records 288 355 1,759 10,965 149 13,516 100%
% of the Total 2% 3% 13% 81% 1% 100%
Synthetic Records 0 190 256 582 10 1,038 8%
Missing O, B, A, and/or D? 200 0 0 0 0 200 1%
Erroneous information? 88 0 0 0 0 88 1%
OD sampling rate to On2Off sampling rate by a ratio > 1.5 0 86 673 589 0 1,348 10%
OD sampling rate to On2Off sampling rate by a ratio <0.3333 0 0 0 0 139 139 1%
On2Off expansion factor 0 - 0.5 0 58 155 442 0 655 5%
Result of RTD expansion (no On2Off records collected) 0 21 48 117 0 186 1%
Reasonable expansion factors in both surveys 0 0 627 9,235 0 9,862 73%
Expansion Factor (EF) CriteriaTotal % of Total
How many are/include
Criteria
Results Continued
May 20, 2015 Page 14
Large number of OD survey records with an expansion factor
less than 1.0 (+2,400 or 18%)
The causes were explicable based on the
data
2015 TRB Planning Applications Conference
Conclusions
• Using IPF with on-to-off flow data and APCs produces more accurate boarding and alighting results than RTD in these routes
• Also improved representation of short trips
• Missing flow movements incorporated into the expanded dataset which removed biases from over- and underweighting of various flow movements
May 20, 2015 Page 15
2015 TRB Planning Applications Conference
Acknowledgements
Rebekah Anderson, Ohio Department of Transportation
Dr. Mark McCord, The Ohio State University
Dr. Rabi Mishalani, The Ohio State University
Mike, McCann, The Central Ohio Transportation Authority
May 20, 2015 Page 16