Agenda. Analysis Tool Selection and Mesoscopic Dynamic Traffic Assignment Models Applications:

Transcription

1 Four Case Studies

2 Agenda Analysis Tool Selection and Mesoscopic Dynamic Traffic Assignment Models Applications: Traffic diversion caused by capacity reduction (Fort Lauderdale, FL) Impacts on traffic due to changes in arterial network (Tampa, FL) Road closures for Maintenance of Traffic (MOT) (San Antonio, TX) Analyzing managed lanes performance (Dallas, TX)

3 Role of Traffic Analysis Tools Improve decision making process Evaluate and prioritize planning/operational alternatives Improve design and evaluation time and costs Present/market strategies to the public/stakeholders Monitor performance FHWA Traffic Analysis Toolbox Volume I: Traffic Analysis Tools Primer

4 How big is the Scope study area? What is the available Cost budget? How much time Schedule do we have? What Ultimate are the answers Study the client needs? Goal

5 Scope Schedule Cost Ultimate Study Goal

6 Mesoscopic DTA Models Simulate movements of trips with some level of resolution (packets or vehicles) Discretely model queues in the network Traffic flow performance is evaluated using aggregate macroscopic flow relationships (i.e., Greenshield) Aggregation/disaggregation processes used alternatively to combine queue and flow performance measures.

7 Advantages of the Application Ready-to-use regional networks and trip tables from regional models Ability to model large sub-areas with reasonable resources Level of analysis consistent with planning level designs Excellent tool for planning level decision making process

8 Benefits For Decision Makers Tool contemplates regional impacts (like regional travel demand model) with better degree of definition Less resource-hungry than micro-simulation for large corridors Less assumptions to feed the data needs of microsimulation Easier and quicker analysis of alternatives More flexible and disaggregated than travel demand models

9 Traffic diversion caused by capacity reduction (Fort Lauderdale, FL)

10 Southeast Regional Planning Model (SERPM 7.0) Activity-Based Model (ABM) AM & PM Peaks 6:30 AM to 9:30 AM 3:30 PM to 6:30 PM 30-Minute Intervals using ABM Matrices Subarea Network 10

11 SE 17 th Street - Steps for Analysis Use Dynamic Traffic Assignment / Traffic Impact Analysis (DTA/TIA) mesoscopic tool Run 3 Scenarios Validation (No Build) Lane Reduction without Provision of Alternate Route Lane Reduction with Provision of Alternate Route Assess Measures of Effectiveness (MOEs) Volumes Travel Times Vehicle-Miles-Travelled (VMT) Vehicle-Hours-Travelled (VHT) 11

12 SE 17 th Street - Validation 12

13 SE 17 th Street - Validation 13

14 SE 17 th Street - Validation Time Slice AM Peak PM Peak % 18.6% 2 8.9% 17.4% RRRRRRRR %RRRRRRRR = 100 NN ii=1 CCCCCCCCCC ii NN % 16.8% % 21.5% % 23.4% % 23.8% RRRRRRRR = NN CCCCCCCCCC ii MMMMMMMMMM 2 ii=1 ii NN SERPM 7 Allowable %RMSE Range for: Count Values < 5,000 = 45% - 55% All Links with Counts = 32% - 39% 14

15 SE 17 th Street - Validation SE 17th Street East of Cordova Road (PM-EB) Time Slice Time Field Model Output Difference GEH 1 3:30 PM :00 PM GGGGGG = 2 MMMMMMMMMM CCCCCCCCCC 2 (MMMMMMMMMM + CCCCCCCCCC) 3 4:30 PM :00 PM :30 PM FDOT / FHWA Criteria: >85% of links must have GEH statistic value <=5 6 6:00 PM

16 SE 17 th Street Traffic Diversion Analysis No Build Lane Reduction without Provision of Alternate Route (Scenario #1) One lane in each direction assigned to exclusive transit No capacity improvements Assumes relocation of Port checkpoints on Eisenhower Blvd and SE 24 th St. to provide alternate route along SE 24 th St Lane Reduction with Provision of Alternate Route (Scenario #2) Build upon Scenario #1 Assumes completion of interrupted section of SE 20 th St Assumes relocation/removal of Port checkpoints to provide additional alternate route along SE 20 th St 16

17 SE 17 th Street Traffic Diversion Analysis SE 17 th Street Scenario #2 Additional Alternate Route Scenario #1 Alternate Route 17

18 SE 17 th Street Traffic Diversion Results Link No Build Scenario 1 Difference SE 17th Street East of Federal Highway 9,870 7,460-2,410-24% SE 17th Street East of Cordova Road ,680-1,720-18% Average -21% Link No Build Scenario 2 Difference SE 17th Street East of Federal Highway 9,870 7,270-2,600-26% SE 17th Street East of Cordova Road 9,400 6,770-2,630-28% Average -27% 18

19 SE 17 th Street Travel Time Results Travel Time From Federal Highway to 0.1 M. East of Eisenhower Boulevard (PM-EB) Travel Times, (min) No Build Scenario 1 Scenario Time Slice 19

20 Impacts on traffic due to changes in arterial network (Tampa, FL)

21 Tampa Bay Regional Planning Model (TBRPM) Time-of-Day Four-Step TDM AM Peak Analysis (6:30 AM to 9:00 AM) 30-Minute Intervals Subarea Network 21

22 Tampa Bay - Steps for Analysis Develop mesoscopic subarea model Run base (existing) model Run w/phase I network modifications Run w/phase II network modifications Run Selectlink analyses on impacted ramps Determine traffic impact on Selmon expressway Determine T&R Impact 22

23 Downtown Tampa Arterial Network Changes Phase 1 Phase 2 Legend Base Proposed Impact 23

24 Tampa Bay Results Phase I DTA Diversion Analysis (Phase I minus Base) 24

25 Tampa Bay Results Phase I Expressway Ramp Traffic Analysis Model Summary Year: 2015 Before After Morgan St Description PHASE I Traffic Demand Downtown Development Traffic Demand On-Ramp Percent Share 100% Impact 100% WB Average Daily Traffic 1,500 Traffic Diverted 1,500 24% Traffic Flow Morgan St On-Ramp Morgan St On- Ramp Tampa St On Ramp Local Short Trip 100% 76% 18.0% 6.00% 1,500 1, Toll Traffic Exit 5 (Plant Ave) West Mainline Toll Gantry Exit 5 (Plant Ave) West Mainline Toll Gantry 5.9% 94.1% 5.9% 94.1% 89 1, ,327 Toll Transactions Lost Transactions Toll Transactions Lost Transactions Summary 100.0% 94.0% 6% 1,500 1, New Transactions Revenue Transactions Revenue % Plant Ave 3,800 2,100 Plant Ave 3,795 2, % West Mainline 31,200 37,500 West Mainline 31,115 37, % System Total 109, ,800 System Total 109, , % Lost 0.08% 25

26 Tampa Bay Results Phase II DTA Diversion Analysis (Phase II minus Base) 26

27 Tampa Bay Results Phase II Expressway Ramp Traffic Analysis Model Summary Year: 2015 Before After Morgan St Description PHASE II Traffic Demand Downtown Development Traffic Demand On-Ramp Percent Share 100% Impact 100% WB Average Daily Traffic 1,500 Traffic Diverted 1,500 20% Traffic Flow Morgan St On-Ramp Morgan St On- Ramp Tampa St On Ramp Local Short Trip 100% 80% 15.0% 5.00% 1,500 1, Toll Traffic Exit 5 (Plant Ave) West Mainline Toll Gantry Exit 5 (Plant Ave) West Mainline Toll Gantry 5.9% 94.1% 5.9% 94.1% 89 1, ,341 Toll Transactions Lost Transactions Toll Transactions Lost Transactions Summary 100.0% 95.0% 5% 1,500 1, New Transactions Revenue Transactions Revenue % Plant Ave 3,800 2,100 Plant Ave 3,796 2, % West Mainline 31,200 37,500 West Mainline 31,129 37, % System Total 109, ,800 System Total 109, , % Lost 0.07% 27

28 Tampa Bay Results Phase II cont. Scenario 2015 Traffic Switch from Current Morgan St On Ramp Morgan St Ramp Use Other Local Re-routed to Street and Not Use Tampa St Ramp the Toll Road Selmon Expressway Daily Transaction Selmon Expressway Daily Revenue Plant Ave West Mainline System Total Plant Ave West Mainline System Total Before 1,500 3,800 31, ,100 $ 2,100 $ 37,500 $ 139,800 After 1, ,796 31, ,025 $ 2,098 $ 37,415 $ 139,704 % Change 20% 0.12% 0.23% 0.07% 0.12% 0.23% 0.07% Note Selmon Expressway daily transaction and revenue are based on "Tampa-Hillsborough Country Expressway Authority Comprehensive Traffic and Revenue Study 2011", by Wilbur Smith Associates. Morgan St Ramp traffic volume is based on 2009 counts used in the regional travel demand model. Reflect traffic impact of the Phase 2 network changes. 28

29 Road closures for Maintenance of Traffic (MOT) (San Antonio,TX)

30 San Antonio Travel Demand Model (TDM) Daily Four-Step TDM Determined Spatial and Temporal Limits for IH10/IH35 DTA MOT Analysis 30

31 San Antonio DTA Determined temporal analysis period based upon daily counts profile Split 24-hour Matrices to Create 3-hour Matrix 3-hour Capacities 31

32 San Antonio DTA Analyzed Base + 3 Closure Scenarios w/different Alternatives 16 Analyses Total Further refined Subarea for MOEs Vehicle-Hours-Travelled Congested Speeds 32

33 San Antonio DTA - Results % Difference from Base Condition for each MOT Scenario Percent Alternative Difference VHT_1 1A 7% 1B 24% 1C 14% 1D 91% 1E 11% 1F 4% Ranked Alternatives Congested Speed Segment Base 1A 1B 1C 1D 1E 1F IH-10 0% 0% -3% -28% 0% 0% IH-10/35-11% -15% -15% -22% -7% -7% IH-35 0% 0% 0% -20% 0% -4% Percent Alternative Difference VHT_1 1F 4% 1A 7% 1E 11% 1C 14% 1B 24% 1D 91% 33

34 Analyzing managed lanes performance (Dallas, TX)

35 Project Location/General information 13-mile managed lanes in heavily congested corridor (IH 35E to US 75, 13.3 miles) 35

36 Dallas-Fort Worth Regional Travel Demand Model for the Expanded Area (DFX) Four-step trip-based travel demand model 10,000 square mile area in North Central Texas (13 counties) TOD Model AM (6:30 AM to 8:59 AM), PM (3:00 PM to 6:29 PM); Off-Peak (9:00 AM to 2:59 PM and 6:30 PM to 6:29 AM) 36

37 Modeling Approach Economic Review Revised Demographics Regional Travel Demand Model Collected Traffic Data Counts, Class, &Speed Stated/Reveal Preference Data Corridor Macro Toll Diversion Model (Static) Sub-Area Mesoscopic Toll Diversion Model (Dynamic) Corridor Toll Diversion Model

38 LBJ Managed Lanes Corridor Toll Model Corridor Macro Toll Diversion Model (Static) 38

39 LBJ Managed Lanes DTA 150 Count Locations 15-min counts during AM period (6:30 AM to 8:59 AM) Ten (10) matrices estimated using DODME Sub-Area Mesoscopic Toll Diversion Model (Dynamic) 39

40 DODME Run DTA Output: Packet Log File Analyze Packet Log Output: Correction Factor Check: Calibration Targets Changes from matrix on last iteration Recompile time-varying trip table Factor packet volumes with correction factors Converged? STOP

41 LBJ Managed Lanes DTA Time Slices

42 LBJ DTA HEVAL Sample Results Change in Speed Time Slice VHT VMT -40.0% 70,000 MPH % 1 6:30-6: % 19, , % 60, :45-7: % 44, , % 50, :00-7: % 60, , % 4 7:15-7: % 54, ,500 40, % 5 7:30-7: % 39, ,900 30, % 6 7:45-8: % 22, ,600 20, % 7 8:00-8: % 16, ,400 10, :15-8: % 10,100 80, % :30-8: % 7,100 73, % :45-9: % 5,400 48,500 Change in Speed VHT

43 DTA Model General Approach Subarea Extraction Any Voyager Network Review & Clean-up are mandatory Matrix Slicing Four-Step Models: DODME ABM Models: As-is DTA Check Convergence HEVAL by Time Segment

44 THANK YOU VERY MUCH