Memphis and Shelby County. Metropolitan Planning Organization (MPO) Travel Demand Model. Tennessee-Kentucky Model User Group Meeting

Transcription

1 Memphis and Shelby County Metropolitan Planning Organization (MPO) Travel Demand Model Tennessee-Kentucky Model User Group Meeting October 26, 2006

2 Model Development Team Kimley-Horn and Associates, Inc. Cambridge Systematics HNTB NuStats

3 Model History in Memphis Originally Developed in Late 60s Last Major Model Update was in 1995 Existing Model Parameters Model Boundary Demographic Variables Submodels 1998 Household Travel Survey

4 Review Process Client Review Steering Committee Peer Review Committee

5 Documentation and Meetings 12 Documents 2 Face-to-Face Peer Review Meetings 2 Peer Review Conference Calls 3 Steering Committee Meetings 2 Expert Panel Meetings for Land Use and Demographics Update Meetings with Engineering and Technical Committee monthly

6 New Travel Demand Model Decision to Change Platform GIS Based Program (TransCad) Flexibility in Model Applications Ease of Database Manipulation Reporting Features and Tools Consistency with State and other MPOs

7 Land Use Coverage Traffic Analysis Zones

8 Development of TAZ Structure Expansion of Prior Zonal Coverage In the North (Tipton County) In the East (Fayette County) In the South (DeSoto and Marshall Counties) Census TIGER Line Files Geographic Features Transportation Facilities

9 Model Area Boundary

10 Traffic Analysis Zones

11 Development of TAZ Structure Special Generators Census Boundaries Tracts (Suburban/Rural) Block Groups (Urban/Suburban) Blocks (Urban) Centroid Connectors and the Network TAZs in Previous Model: 800 (app) TAZs in Current Model: 1,237

12 Development of Baseline Data Population and Household Variables Used Data from Census 2000 (SF1, SF3) Matched Census Geography to TAZs Employment Variables Used 2000 At-Place Employment Data Reconciled using BLS Grouped into Generalized Industry Categories (NAICS)

13 Development of Baseline Data 2004 Estimation Consultation with Planning Staff Comparison with Available Data (E.G., Building Permits)

14 Typical Model Processes (How the model works) 4-Step Travel Demand Modeling Process Trip Generation (How Many Trips?) Trip Distribution (Where Do You Want to Go?) Mode Choice (How Do You Want to Get There?) Trip Assignment (Which Route?) Data Requirements Base, Future, and Interim Year Models

15 Household Survey Key Features MPO Region Shelby County and Part of Fayette County, TN Part of DeSoto County, MS Memphis MSA (Census 2000 Figures) Ranked 44 Out of All the Other MSAs in Country by Population Population = 1,135,614 :: Households = 424,202 Type of Survey Travel Diaries with Detailed Activities Description One Day, 24-Hour Travel Record for Every HH Member Computer-Aided Interviewing (CATI) Procedures Conducted in 1998 (September-November)

16 Survey Sample # Households = 2,526 # Persons = 6,438 # Trips = 198,519

17

18 Trip Generation Trip Generation Submodels Internal Person Trip Productions and Attractions (P s and A s) External/Internal Vehicle Trips Special Generators Vehicle Availability Model

19 Trip Generation Trip Purposes 9 Internal Trip Purposes Journey to Work Home Based School Home Based University Home Based Shopping Home Based Social-Recreational Home Based Pick-up and Drop-off Home Based Other Non-Home Based Work Non-Home Based Non-Work

20 Vehicle Availability Models Models Multinomial Logit (MNL) Model Ordered Response Logit Model (ORL) Model Inputs Tested HH Characteristics Accessibility, Socio- Demographics (# Persons, # Workers, Income Level Dummies) Validation Validated Census Data Selected Model with Best Performance

21 Multinomial Logit (MNL) Model All Households (HHs) 0 Vehicle HHs Probability 1 Vehicle HHs Prob(n th alt) = Utility Equations: n e max i= 0 U n e U U i n 2 Vehicle HHs = b n0 + nv j= 1 b nj X 3+ Vehicle HHs nj

22 Vehicle Availability Model Coefficients of ordered response logit model Variable 0/1+ 1/2+ 2/3+ Constant Person HH Person HH Worker Workers Workers 1.76 LMed Income HMed Income High Income % Emp w/in 15 min

23 Trip Generation Application Results Trip Purpose Productions Attractions % Diff JTW 783, ,159-10% HBSc 343, ,993 9% HBU 56,147 46,202-18% HBSh 223, ,395 4% HBSR 238, ,492 7% HBPD 207, ,188-3% HBO 612, ,710-1% NHBW 138, ,692 3% NHBNW 512, ,675 12% Total 3,115,313 3,138,506-1%

24 External Trip Generation External-External Trips from Statewide Models External-Internal Trip Generation: E j = AT j D j B where: E j = Number of EI Trips Generated in Internal Zone j T j = Total Internal Trip Attractions Generated in Internal Zone j D j = Distance from Zone j to the Nearest External Station A, B = Model Parameters

25 External Station Classification Expressway Arterial Near Expressway Arterial Not Near Expressway Collector/Local

26 Trip Generation Special Generators Memphis International Airport Graceland Federal Express (Airport Hub)

27

28 Time of Day Model Figure 1. Percent of Trips by Time and Purpose Journey-to-Work Home-Based School/University Home-Based Other Non Home-Based All Trip Purposes Time Period Percent of Trips

29 Time of Day Model Percent of Trips by Purpose Time Period Journey-to- Work HBSchool/ HBUniversity Other Home- Based Purposes Non-Home- Based All Purposes 0:00-1: :00-2: :00-3: :00-4: :00-5: :00-6: :00-7: :00-8: :00-9: :00-10: :00-11: :00-12: :00-13: :00-14: :00-15: :00-16: :00-17: :00-18: :00-19: :00-20: :00-21: :00-22: :00-23: :00-24: Total 100.0% 100.0% 100.0% 100.0% 100.0%

30 Time of Day Model Time of Day Directional Trip Factors (Post-Mode Choice) Trip Purpose Direction AM Peak Midday Peak PM Peak Off-Peak 1 JTW % From Home % To Home HBSchool % From Home % To Home HBUniv % From Home % To Home HBShop % From Home % To Home HBPUDO % From Home % To Home HBSR % From Home % To Home HBO % From Home % To Home NHBW N/A NHBNW N/A

31 Time of Day Model Time of Day External Trip Factors Facility Type Direction AM Peak 1 Interstate 2 Other Principal Arterial Midday Peak PM Peak Off-Peak % of Daily % Inbound % Outbound % of Daily % Inbound % Outbound /8/9 Minor Arterial Collector/ Local % of Daily % Inbound % Outbound % of Daily % Inbound % Outbound

32 Trip Distribution Trip Distribution Model Components Intrazonal Travel Times Terminal Times Primary Destination Choice Intermediate Travel Times

33 Trip Distribution Primary Destination Choice Gravity Model T ij A F = P j ij i n ( A F ) j = 1 j ij Destination Choice Model P i = exp( U j exp( U i ) j )

34 Logit Destination Choice Model Utility of Choosing Destination Zone j = B 1 (impedance ij ) + B 2 ln (size variable) + B 3 (prod or attr zone dummy variable 1) + + B n (prod or attr zone dummy variable n-2)

35 Destination Choice Model for JTW Trips Variable Parameter Estimate Mode Choice Logsum Production-Attraction Dummies Production and Attraction Ends in CBD Production End is Urban Zone and Attraction End is in CBD Production End is Suburban/Rural and Attraction End is in CBD Attraction End Dummies Attraction End is an Urban Zone Attraction End is a Suburban Zone Attraction End is a Rural Zone Production-Attraction Highway Distance Power Series Distance Square of Distance Cube of Distance (Base) Multiplier for Size Variables Size Variables (Coefficients Shown Are Exponents of Estimates) Service Retail Industrial/Manufacturing Wholesale Office Government (Base) Attraction Zone Area in Square Miles

36 Destination Choice Model for NHBW Trips Variable Parameter Estimate Mode Choice Logsum 0.32 Attraction End Dummies Attraction End is a CBD/Urban Zone Attraction End is a Suburban Zone Production-Attraction Highway Distance Power Series Distance Square of Distance Cube of Distance Natural Log (Non-Home Based Work Modeled Attractions) 0.71

37 Journey to Work Stops Model Number of Stops Variable Constant Home-to-work chain vehicle household vehicle household vehicle household Presence of kids in household

38 Avg. Travel Time Comparison Purpose Model (min) Observed (min) JTW HBO HBPUDO HBSc HBSh HBSR HBU NHBW NHBNW

39 Mode Choice Multinomial Logit Model (Like Destination Choice Model) On-Board Transit and Household Survey Travel Modes Included

40 Mode Choice Modes included: Transit with Auto Access (Includes Bus and Trolley) Bus with Walk Access Trolley with Walk Access Non-Motorized (Including Walk/Wheelchair and Bicycle) Shared-Ride Drive Alone Spare Mode for Future Use

41 Survey Data Set Summary Mode JTW HBSc HBU HBSh HBPD HBSR HBO NHBW NHBNW All Bus - Auto Bus - Walk 1, ,531 Trolley - Auto Trolley - Walk Walk ,155 Bicycle School Bus Shared Ride 793 1, , ,792 8,024 Drive Alone 3, , ,676 All 5,749 2, ,503 1,397 1,283 4, ,135 20,960

42 Mode Choice On-Board Transit Survey Results Vehicle Ownership 100% 80% 60% 60% 40% 20% 0% 25% 11% 3% 1% None One Two Three Four or more

43 Mode Choice On-Board Transit Employment Status Survey Results Employed, Full time 42.6% Employed, Part tim e 18.4% Unemployed, Looking 16.2% Student 15.2% Retired 3.3% Unemployed, Not Looking 2.4% Homemaker 1.9% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

44 Mode Choice On-Board Transit Income Level Survey Results Less than $6,000 $6,000 - $18,000 34% 31.8% $18,001 - $30,000 18% $30,001 - $42, % $42,001 - $60,000 $60,001 - $90,000 More than $90, % 1.3% 0.5% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

45 Mode Choice On-Board Transit Age Survey Results 100% 80% 60% 40% 20% 0% 35.6% 19.5% 19.0% 15.6% 7.8% 0.9% 1.7% Under or older

46 Mode Choice On-Board Transit Ethnicity Survey Results 100% 88.9% 80% 60% 40% 20% 0% Black/American American 8.2% 1.2% 0.7% 0.6% 0.4% White Other Native American Hispanic Asian American

47 Freight Model Trip Gen Quick Response Freight (QRF) Manual Generator (Unit) Agriculture, Mining, and Construction Manufacturing, Transportation, Communications, Utilities, and Wholesale Trade Commercial Vehicle Trip Destinations (or Origins) per Unit per Day Four-Tire Trucks Single Unit Trucks Combination Trucks Retail Trade Office and Services Total Trucks Households

48 Freight Model (cont.) Trip Distribution - Gravity Model Calibrated to Classification Counts

49 Roadway Network Development Used network provided by MPO (with some cleaning) Developed data collection tool in TransCAD to enter in network attribute data Collected street data for all streets in network (through TRIMS and windshield data)

50 Network Collection Tool Allowed for data entry in the field by a two person team Could copy and paste data from one link to another Helped to minimize coding errors

51 TRIMS Image Data

52 Roadway Network Development Coordinated with TAZ development to ensure appropriate level of detail for both Developed centroid connectors in coordination with local staff Centroid connectors indicated auto/non-auto access Aerial photography and measurement data used to clean interchanges in network

53 Roadway Network Development One TransCAD file contained all years of development baseline, existing plus committed, long range plan, etc., by year Network contained link-dating that indicated when a particular section will open (or close) Changes in network carried over to all potential scenarios and years

54 Roadway Network Quality Control TransCAD tools such as Check Line Layer Connectivity were used Trip path tests and test loadings also were used to identify network issues Plots with network attributes (lanes, speeds, median type, etc.) were submitted for review Checks against available aerial photography

55 Capacity Equations Based on HCM and TDOT Data Doesn t use standard lookup tables completely based on attributes Live update lanes on a link, capacity updates Calculated hourly and daily capacity Calculated LOS A through LOS E

56 Capacity Equations The general form of the equation was: SF = c * N * fw * fhv * Fp * FE * fd * FSD* FCLT * FPark * (v/c)i Where the variables were: SF = Maximum service flow for desired level-of-service c = Capacity under ideal conditions (vehicles per hr per lane) N = Number of lanes fw = Factor due to lane and shoulder width fhv = Factor due to percent heavy vehicles Fp = Factor due to driver population FE = Factor due to driving environment fd = Factor due to directional distribution FSD = Factor due to signal density FCLT = Factor for continuous left-turn lane (for undivided sections) FPark = Factor for on-street parking (v/c)i = Rate of service flow for levels-of-service A through E

57 Capacity Equations

58 Lookup Tables No hardcoding of values Separates interface development from model development More efficient model adjustments/calibration Subsequent model updates don t necessarily need new code Data is more transparent and accessible

59 Lookup Tables

60 Network Development Highway Network Network

61 Network Development Highway Network Screenlines and Cutlines

62 Network Development Highway Network Area Types

63 Network Development Highway Network Code Facility Type Centerline-miles Daily Counts TOD Counts Class Counts Supplementary Counts 1 Rural Interstate Rural Principal Arterial Rural Freeway Ramp 11 6 Rural Minor Arterial Rural Major Collector Rural Minor Collector Rural Local Access Urban Interstate Urban Freeways/Expressways Urban Freeway Ramp Urban Principal Arterial Urban Minor Arterial Urban Collector Urban Local Access Total Rural Roads Total Urban Roads Total - All Roads

64 Network Development Transit Network way routes

65 Network Development Transit Network

66 Network Development Transit Network

67 4 Park and Ride Lots

68 Assignment Roadway and Transit Networks Level of Detail Data Collection Effort Quality Control All or Nothing Preload Heavy Commercial Vehicles External-External Trips Equilibrium Multi-Class Assignment Pathfinder Transit Assignment

69 Highway Assignment Validation Targets Table 1. Percent Difference Targets for VMT by Functional Classification Facility Type Target Freeways 8-12% Principal Arterials 18-22% Minor Arterials 27% Collectors 33% Table 2. Percent Difference Volume Targets by Functional Classification Facility Type Target (+/-) Freeway 7% Major Arterial 10% Minor Arterial 15% Collector 25% Local 25% Table 3. Percent Difference Volume Targets by Daily Volume Groupings (totaled over entire group) Volume Group Target (+/-) <1, % 1,000-2, % 2,500-5,000 50% 5,000-10,000 25% 10,000-25,000 20% 25,000-50,000 15% >50,000 10%

70 Highway Assignment Validation Targets Table 4. Percent of Links within a Specified Percent of Count by Facility Type Facility Type Target within Count Range Compared to Counts Freeway 75% 20% Freeway 50% 10% Major Arterial Major Arterial Minor Arterial Minor Arterial 75% 30% 50% 15% 75% 40% 50% 20% Note: Table 4 can be read as 75% of the freeway links need to be within 20% of counts, 50% of the freeway links need to be within 10% of counts.

71 Highway Assignment Global Results

72 Highway Assignment Global Results Screenlines and Cutlines

73 Highway Assignment Calibration/Trouble Shooting Globally Low Modeled Volumes versus Observed Volumes Assignment Bias Toward Interstate versus Non-Interstate Facilities (Particularly Pronounced in Urban Area)

74 Future Year Model Demographics Area Type Signals Highway and Transit Network

75 What s New About this Forecasting Process? Employed a Rigorous Analytical Model Integrated this Economic Model with the Benefits of Local Planning Knowledge Review by Expert Panel Review by Local Planners

76

77 45 Sub-County Areas (SCAs)

78 Memphis Forecasting Sequence NATIONAL FORECAST Integration of federal data REGIONAL FORECAST Industry linkages to U.S. SCA FORECASTS Allocation of regional forecasts To 45 sub-county areas (SCAs) Expert Panel Review/Revision TAZ FORECASTS Allocation of SCA forecasts to 1,237 traffic analysis zones (TAZs) Local Planners Review/Revision

79 Study Area Forecast Households Jobs

80 Forecast by Counties Shelby County Jobs Households

81 Forecast by Counties DeSoto County Jobs Households

82 Study Area Portion of Other Counties Portion of Fayette County Portion of Tipton County Jobs Households 0 Jobs Households

83 Study Area Portion of Other Counties Portion of Marshall County Jobs Households

84 Households

85 Households

86 Employment

87 Employment

88 MSA Forecast Results 2,000,000 Regional Population Forecast 1,000,000 Regional Employment Forecast 1,800, ,000 1,600, ,000 1,400, ,000 1,200, ,000 1,000, , , , , , , , , , Between 2004 and % Gain in Population 56% Gain in Total Employment

89 Future Year Signal Identification Capacity equations used intersection penalties, signal density, and signal coordination If you use signals, you have to forecast them.. somehow Basic warrant analysis flagged potential new signals User then used tool to accept/reject pending flags

90 Future Year Signal Identification Flags potential signals using basic warrant analysis on AM peak (using TDOT standards) Corridors are grouped into sections for capacity equations (Signal density and signal coordination)

91

92 Area Type Model Forecasted by 6 Categories CBD, CBD Fringe, Urban, Suburban, Rural and OBD (Outlying Business District) Forecasting Methodology No downgrade is possible New CBD zone must be adjacent to existing CBD zones New urban zone must be adjacent to the existing urban cluster New urban cluster will be created if the area is >10 square miles Existing or new OBD zones will become urban if they become adjacent to any urban zone No neighboring constraints on OBD, suburban, and rural zones Unique Algorithmic Features The forecasting process is conducted inside out, similar to an urban sprawl process, to avoid invalid neighbors If one zone can upgrade to more types, they are evaluated in priority order, so all possibilities will be considered CBD,CBD-fringe and urban zones are evaluated by recursively finding the fringe zones and finalize it step by step All future area types are decided based on final decisions already made e.g., not dependent on the particular evaluation order

93 Memphis Model Demo Introduction Installation Scenario Management Model Run Control Export Results Future Year Network Structure and Project Management Query Project Modify/Redefine Existing Project Add/Delete project Future Year Signal Forecasting Forecasting Signal Locations Signal Density Signal Coordination Reports Highway Transit Maps Highway Transit

94 Questions?

95 Contacts Mark Dunzo Phone: Kenny Monroe Phone: Zhiyong Guo Phone: Pramoda Gode Phone:

96 Presentation Copies Presentation Available At: _secure/tn_ky_usersgroup Username: Memphismodel Password: presentation