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OUTLINE OF CLASS: Origins and motivations The standard five-step model

OVERVIEW OF TRANSPORTATION DEMAND MODELS KSG HUT251/GSD 5302 Transportation Policy and Planning, Gomez-Ibanez. OUTLINE OF CLASS: Origins and motivations The standard five-step model Often called “UTPS” (Urban Transportation Planning System) model Passenger Freight Urban UTPS

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OUTLINE OF CLASS: Origins and motivations The standard five-step model

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  1. OVERVIEW OF TRANSPORTATION DEMAND MODELSKSG HUT251/GSD 5302 Transportation Policy and Planning, Gomez-Ibanez OUTLINE OF CLASS: • Origins and motivations • The standard five-step model Often called “UTPS” (Urban Transportation Planning System) model Passenger Freight Urban UTPS Intercity • Subsequent refinements • Disaggregate models and data • Simultaneous models • Stated vs. revealed preference • Virtual or micro simulation • “Back of the envelope” assessment

  2. EVOLUTION OF THE MODELS • Postwar metropolitan growth  planning for major new expressway systems • Early metropolitan studies 1953: Detroit 1956: Chicago (CATS) 1958: Pittsburgh • 1962 Federal Highway Aid Act “3 Cs”: Comprehensive, coordinated and continuing planning • 1990 Clean Air Act; 1991 Intermodal Surface Transportation Efficiency (ISTEA) Act Transportation and air quality improvement plans must be consistent • Subsequent refinements 1970s: Disaggregate models: widely adopted 1960s and 1980s: Simultaneous models: limited applications 1990s: Stated preference: still controversial 1990s-2000s: Virtual-micro simulation: still experimental (TRANSIM program sponsored by DOT, EPA, and DOE)

  3. COMPLICATIONS OF TRAVEL DEMAND P Q • REAL TIME AND SPACE DIMENSION Many distinct markets with different Ps and Qs • SERVICE QUALITY IMPORTANT Ps are multidimensional • SYSTEM INTERDEPENDENCIES “Cross elasticities” are high • TRANSPORTATION AFFECTS LAND USE Long run demand may be significantly different from short run demand

  4. STEPS IN UTPS MODEL LAND USE TRIP GENERATION TRIP DISTRIBUTION MODE SPLIT ROUTE ASSIGNMENT

  5. TRAFFIC ZONES

  6. TRAFFIC ZONES

  7. NETWORKS

  8. TRIP TABLE (with n zones) Oi = trips originating in zone i Aj = trips attracted to zone j Tij = trips between zones i and j

  9. TRIP TABLE DIFFERENT TRIP TABLES • BASE AND FORECAST YEARS Convention here: superscript “*” denotes forecast year; no superscript denotes base year data • BY PURPOSE Home-based work Home-based school Home-based shop Home-based other Non-home based • BY MODE Auto, transit, bike

  10. CALIBRATING DATA(BASE YEAR) • LAND USE INVENTORY BY ZONE • ORIGIN AND DESTINATION DATA (to build trip table) • US Census (work trips only; often used for up date) • Home interview survey (2 to 5 % sample typical) • Special surveys (taxis, trucks) • Cordon and screen line counts (cordon around CBD; screen lines across suburban corridors

  11. STEP 1: LAND USE FORECAST • EARLY: AD HOC • LATER: FORMAL MODELS • Empiric Land use in zone* = f(accessibility of zone*,…) • Lowry type Distinguish basic (export-oriented) from population-serving employment Basic employment located exogenously, residences of workers and poulation serving employment follows • CURRENT: SENARIOS

  12. STEP 2: TRIP GENERATION AND ATTRACTION (Using land use forecast, forecast Oi and Aj) Oi*= f(residential populationi*, auto ownershipi*, etc.) Aj*= f(square feet of officesj*, square feet of retail storesj*, etc.)

  13. STEP 3: TRIP DISTRIBUTION OR ZONAL INTERCHANGE (Using Oi* and Aj*, forecast Tij* ) • SIMPLE GROWTH FACTORS Tij* = k Tij • CORRECTED GROWTH FACTOR Tij* = k (Oi*/ Oi) Tij or Tij* = k (Aj*/ Aj) Tij • GRAVITY MODEL n Tij* = k Oi* [(Aj*/ Dij*b)/ (Aj*/ Dij*b)] j=1 Where Dij* is the “impedance” between zones i and j and k and b are empirically determined from the base year data

  14. STEP 4: MODAL SPLIT (Split Tij* into transit, highway, etc.) • TRIP END MODELS Transit’s share of Tij* = F(incomei, densityi, etc.) • DIVERSION CURVES 100% Percent using transit 0% 0.5 1.0 1.5 Ratio of transit time or cost to auto time or cost • DISAGREGATE MODELS

  15. STEP 5: ROUTE ASSIGNMENT • AD HOC • MINIMUM PATH Linear programming • CAPACITY CONSTRAINED MINIMUM PATH

  16. COMMON CRITICISMS OF UTPS(and responses) • STRUCTURE OF MODEL UNREALISTIC • LAND USE AND TRANSPORT USUALLY ASSUMED INDEPENDENT (may be true in some cases) • TRAVEL DECISIONS ARE SIMULTANEOUS NOT SEQUENTIAL (simultaneous modeling hard) • TRANSPORT OMITTED FROM SOME STEPS (only from trip generation and attraction) • TRANSPORT CHOICES DON’T FEED BACK ON PERFORMANCE OF TRANSPORT SYSTEM (usually iterate model until inputs and outputs consistent) • MODELS ARE EXPENSIVE TO CALIBRATE (for big decisions worthwhile; for small decisions can often use only one or two steps of model) • NO PEAK HOUR MODEL (time-of-day models in infancy)

  17. USES OF UTPS-LIKE MODELS TODAY

  18. REFINEMENTS:DISAGGREGATE DATA AND MODELS • Idea: Calibrate models with data on individual travelers rather than on zonal aggregates • Advantages: • Uses data more efficiently (avoids loss in variation that comes from aggregating individual data by zones) • Coefficients less likely to be biased • Estimated with logit or probit instead of ordinary regression (dependent variable is discrete) 1.0 x x x x x Probability of picking transit 0.0 x x x x x x x=observation relative convenience of auto vs. transit

  19. REFINEMENTS:DISAGGREGATE DATA AND MODELS • Typical logit specification Pm = eUm / eUi All modes i Where Pm = probability person will pick mode m Um = measure of “utility” of mode m e = base of the natural log Example: with two modes auto and bus Pauto = eUauto / (eUauto + eUbus ) Pbus = eUbus / (eUauto + eUbus ) Utility of a mode is assumed to be linear function of variables measuring • Performance of the modes (travel time and cost) • Socio economic characteristics of the travelers, and • Dummy variables for each mode

  20. REFINEMENTS:DISAGGREGATE DATA AND MODELS • Example: mode to work in SF (Essays, p. 20) Four modes: drive alone, carpool, walk to bus, drive to bus U = -0.0412 (travel cost in cents / traveler’s wage rate) -0.0201 (in vehicle time in minutes) -0.0531 (out-of-vehicle time in minutes) -0.89 (dummy for drive alone) -2.15 (dummy for carpool) -0.89 (dummy for walk to bus) • Derivation of value of travel time (useful as check on model reasonableness and for project evaluation) Value of time = (coefficient for time)/(coefficient for cost) = (lost utility/min)/(lost utility/$) = $/min. SF example above: In-vehicle time = (-0.0201)/(-0.0412/wage) = 0.49 wage rate Out-of-vehicle time = (-0.0531)/(-0.0412/wage) = 1.29 wage

  21. REFINEMENTS:SIMULTANEUOS MODELS • Idea: Eliminate sequential structure • 1960s: “Direct” demand models (with aggregated data) Tijpm = Trips from i to j by purpose p and mode m Tijpm = f(characteristics of zones i and j, service i to j, etc.) • 1980s: Nested logit models (with disaggregated data) Example: vacation destination and mode choice model in U.S. (Essays, p. 22) DEST 1 DEST 2 DEST 3 DEST 4 AUTO AIR RAIL BUS AUTO AIR RAIL BUS • Difficulties • Relatively data intensive Many choices and independent variables, so need many observations and much information per observation • Results sometimes very sensitive to specification

  22. REFINEMENTS:STATED PREFERENCE • Distinction • REVEALED PREFERENCE: revealed by actual behavior • STATED PREFERENCE: revealed by survey • Motivation: New modes of travel (example: high-speed rail in the United States) • Difficulties: Do respondents • Understand choice? • Take choice seriously? • Have incentives to misrepresent preferences? (Same issues as in debate among environmental analysts over contingent valuation)

  23. REFINEMENTS:VIRTUAL OR MICRO SIMULATION • Idea: Model individual travelers and activities to give more spatial and temporal detail and (hopefully) more accuracy POPULATION LIKE LAND USE FORECAST SYNTHESIZER ACTIVITY LIKE TRIP GENERATION AND ATTRACTION PLUS GENERATOR TRIP DISTRIBUTION ROUTE INNOVATIVE IN THAT HANDLES TRIP CHAINS AND PLANNER INTERMODAL BETTER; SOLVED BY MINIMIZING GENERALIZED COST TRAFFIC SIMULATOR THE STEP THAT WAS THE INSPIRATION EMMISSIONS ESTIMATOR

  24. TIPS FOR BACK OF THE ENVELOPE ASSESSMENTS • FIND THE RELEVANT TARGET Easier to assess whether target is too high or too low Obvious choices: proponent’s forecast or breakeven traffic • COMPARE WITH CURRENT TRAFFIC AND TREND How much more do you have to get? • CONSIDER ALTERNATIVE SOURCES Usual: (1) Normal growth, (2) induced traffic (stimulate market), (3) other modes, (4) other carriers • SEGMENT MARKET Usual: by O & D, purpose (passenger), commodity (freight), season or time of day • ASSESS QUALITY AS WELL AS PRICE Usual: travel time, frequency, reliability, etc. • COMPARE WITH SIMILAR MARKETS

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