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WIFI Data Collection and the Effectiveness of Various Survey Expansion Techniques- A Case Study on I-95 Corridor in Palm Beach County, FL Presented to.

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Presentation on theme: "WIFI Data Collection and the Effectiveness of Various Survey Expansion Techniques- A Case Study on I-95 Corridor in Palm Beach County, FL Presented to."— Presentation transcript:

1 WIFI Data Collection and the Effectiveness of Various Survey Expansion Techniques- A Case Study on I-95 Corridor in Palm Beach County, FL Presented to TRB National Transportation Planning Applications Conference Raleigh, NC Presented by Srin Varanasi The Corradino Group 05/16/2017

2 Acknowledgements Cesar Martinez, PE Concept Development Supervisor
FDOT District 4- PLEM Fort Lauderdale, FL Sheng Yang, PE President CTS Engineering, Inc. Fort Lauderdale, FL Aditya Katragadda Transportation Planner, The Corradino Group, Fort Lauderdale, FL Ken Kaltenbach, PE Senior Vice President The Corradino Group, Louisville, KY

3 Presentation Overview
I-95 Express Palm Beach Planning Study overview Corridor description Bluetooth/WIFI data collection process OD expansion methods considered OD expansion using CUBE Analyst Results discussion

4 Study Overview Traffic data collection Traffic balancing, OD expansion
Corridor travel demand forecasts development Integration to VISSIM Microsimulation Develop feasible and viable concepts

5 Corridor Description I-95 Express Master Plan
Study the corridor improvements, including Express Lanes Northern Palm Beach County -about 60 miles north of Miami 8-10L Typical with an existing HOV lane

6 Bluetooth/WIFI Data Collection Process (1)
Acyclica Bluetooth/WIFI equipment Detects anonymous MAC addresses Targeted at Bluetooth/WIFI technologies of vehicles/mobile devices May 10-12th 2016 data collection- 3 consecutive weekdays (Tuesday-Thursday)

7 Bluetooth/WiFi Data Collection Process (2)
48 OD locations E and W of I-95 on cross streets 16 interim locations of I-95 mainline to validate the data Simultaneous 48-hour traffic count data collection at the OD locations

8 Bluetooth/WIFI Data Collection Results- Seed OD Matrix Development
Three sets of OD matrices AM peak hour PM peak hour Daily In most locations 15-25% detection rate A few outliers 5-15%; 25-40% Pros- Local OD detection High detection rate Cons Detects MAC IDs not vehicles Possibility of bias with more than one MAC ID presence Capture of parallel corridor traffic, when close by

9 OD Expansion Methods Considered (1)
CUBE Analyst Drive OD Expansion Use of feedback loop with highway assignment Tests using matrix cell confidences Close to 2% RMSE between assigned volumes and counts Similar trends in OD patterns to the raw BT/WIFI OD Null Test- A matrix of ones used as input instead of the BT/WIFI data. %RMSE between Null Test OD and BT/WIFI Daily Expanded OD: 135%

10 OD Expansion Methods Considered (2)
Iterative Proportional Fitting Method Use of a small value (0.1) for cells with zero values Row and column based doubly- constrained balancing process Resulted in large RMSE ~ 28 % when assigned TLFD and average TL statistics results similar to the raw BT/WIFI OD Travel Demand Seed Matrix and expand using CUBE Analyst Drive 3% RMSE when assigned RMSE ~35% between BT/WIFI expanded OD and travel demand model based OD Sensitive to land use changes in travel demand

11 BT/WIFI OD Expansion (1)
CUBE Analyst Drive Method A matrix estimation program that optimizes OD matrices for a given traffic assignment and input traffic count data Setup a feedback loop between highway assignment and Analyst Drive Logged %RMSE Monitored Avg. Trip Length TLFD

12 BT/WIFI OD Expansion (2)
Inputs BT/WIFI seed matrices with confidence levels ICP file analogous to the highway path file Traffic count targets/screenlines Trip end controls (in this case disabled) Turn penalties/prohibitions for the highway assignment Outputs Matrix output Assigned loaded network via highway assignment %RMSE measures

13 BT/WIFI OD Expansion Results (1)
Iterative Feedback RMSE and Volume/Count Ratio Logs

14 BT/WIFI OD Expansion Results (2) Origin-based “Heat” Maps for Managed Lanes Access Points Determination Raw WIFI/BT OD grouped by Logical Destinations Expanded WIFI/BT OD grouped by Logical Destinations

15 BT/WIFI OD Expansion Results (3) Total Trips by Interchange
Raw Origin and Destination Data Expanded Origin and Destination Data

16 BT/WIFI OD Expansion Results (4) Total Trips by City
Raw Origin and Destination Data Expanded Origin and Destination Data

17 Conclusions & Recommendations
BT/WIFI method of OD data collection results in reasonable sample rates CUBE Analyst Drive method, using a feedback loop between highway assignment and matrix estimation process, is an effective matrix expansion technique The null test and BT/WI expanded matrix differences prove that OD data collection is important. Null test travel patterns are different than OD expanded data Simple iterative proportional fitting may not be an effective method of OD expansion process

18 Questions/Discussion
Thank You! Questions/Discussion


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