Developing a Method Selection Tool for Travel Forecasting (2017) / Chapter Skim
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Final Report Project No.
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Final Re FIGURE 2 The TMI transport forecasts Twenty-e agencies highlight also the i demand m port : PLANNING P P survey als ation foreca , and the rem ight percen use other m not only the mportance o odels. RIORITIES FO o reported t sts.
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Final Report Project No. 08-94 9 TABLE 1: ROLE OF TRAVEL DEMAND MODELS IN DEVELOPING AGENCY'S TRAFFIC/TRANSIT/FREIGHT FORECASTS TRAVEL DEMAND MODEL ROLE COUNT PERCENT We do not have a travel demand model.
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Final Re FIGURE 3 Importan methods project co sketch-pl emission scenario Transpor Figure 4. limited st more wit Transpor challenge destinatio sensitivit port : SHARE OF A tly, transpor and tools (e sting, air di anning and s (4%)
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Final Re FIGURE 4 Special N The TMI the Unite provide a confirm t methods) Travel D The curre passenge literature Tradition Passenge These are and Simu predict th are typica (NCHRP demand f 2012)
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Final Report Project No. 08-94 12 Trip Production (Regression)
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Final Report Project No. 08-94 13 In a study by Mishra et al.
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Final Report Project No. 08-94 14 socioeconomic data is at the aggregated zonal level.
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Final Report Project No. 08-94 15 Systems Group, Inc., 2010)
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Final Report Project No. 08-94 16 terms of replicating travel survey and traffic count data.
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Final Report Project No. 08-94 17 The methods chosen for these applications will often vary based on whether the planning purpose is to produce a short- or long-range forecast.
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Final Report Project No. 08-94 18 STOPS is intended for use by capable travel forecasting professionals.
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Final Report Project No. 08-94 19 on the literature review and model framework, a survey of public decision-makers, and additional research in support of this project.
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Final Report Project No. 08-94 20 research estimated the share of nonfreight truck traffic at approximately 5.6% of total vehicle miles traveled (VMT)
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Final Report Project No. 08-94 21 models, microscopic simulation models, deterministic operation models, emissions models, safety models, and sketch-planning tools)
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Final Report Project No. 08-94 22 and planners in various MPOs and state DOTs with direction on the appropriate applications of DTA tools for transportation decision-making.
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Final Report Project No. 08-94 23 model inputs can be arduous.
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Final Report Project No. 08-94 24 Project-level forecasting ranges from site-specific approaches to full-scale travel models, depending on project size and complexity.
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Final Report Project No. 08-94 25 software design accommodates schedule and budget constraints and other requirements for defining the most appropriate methods to answer these planning questions.
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Final Report Project No. 08-94 26 The recommended methods are presented as individual methods or packages of methods, as appropriate and to meet the needs of the planning program or plan.
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Final Report Project No. 08-94 27 land-use, economic, transportation, quality-of-life, and equity performance measures.
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Final Report Project No. 08-94 28 Step 3 -- Performance Measures In the third step, the user chooses performance measures of interest to her or his agency.
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Final Report Project No. 08-94 29 CATEGORY MEASURES METRICS FREIGHT TRANSPORT MEASURES Mobility Demand Mode Shares Traffic Measures Congestion Commodity flows Number of commercial vehicle trips Freight miles traveled by mode Freight travel times Truck volumes Truck speeds Truck delay hours COMMUNITY MEASURES Land Use Schools Environmental Justice Social Equity Access to services Access to schools Travel costs for minorities and lowincome populations Travel costs by income group HEALTH AND SAFETY MEASURES Active Transportation Safety Bike miles Nonmotorized volumes Number of vehicle collisions Step 4 -- Constraints Budget and schedule are two crucial factors that constrain the possibilities for developing any new method.
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Final Report Project No. 08-94 30 Having an agency answer additional questions about their current methods allows the tool to provide more-customized responses, which contrasts with developing an easier-to-use tool that would provide more generic responses.
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F F inal Report IGURE 5: STEP 6 Passenger Tr Compo • Aggregate Mod • Trip Production • Trip Production • Trip Attraction • Trip Distribution • Mode Choice ( • Time of Day (F • Disaggregate M • Population Syn • Daily Activity P • Tour Frequency • Destination Ch • Mode Choice M • Time of Day Ch • Parking Locatio • Transit Pass O -- LIST OF METHO avel Demand nents els (Cross-Class) (Regression)
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Final Report Project No. 08-94 32 The outcome of the guidance is a menu of methods recommendations.
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Final Report Project No. 08-94 33 data needs in broad terms and includes a cost needed to acquire these data if the agency does not currently have access to these data sources.
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F Method Sele IGURE 6: DECISI ction for Tra ON-ENGINE ER D vel Forecasti IAGRAM ng 34 Project No.
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Final Report Project No. 08-94 35 This diagram represented in Figure 6 comprises four parts: User Inputs.
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Final Report Project No. 08-94 36 Application Architecture The research team implemented the software tool as a browser-based web application that runs on modern web browsers (e.g., Chrome, Firefox, Internet Explorer, Safari)
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Final Re Final Us Wirefram The best wizard -- menu of into this functiona wirefram challenge the range software paid to th Page elem breadcrum color, fon ultimate "recomm FIGURE 7 Wirefram iterations phase. Co port er Functio es description an online to options or o early prototy lity.
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Final Re 1.
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Final Re FIGURE 9 After site either beg Previous FIGURE 10 The follo Profile A user sh profile id of resour presents port : USER LOGIN authenticat in a new m session wor : LANDING P wing section ould set a p entifies the ces that are the cost adju SCREEN ion, the agen ethod select k is automat AGE AFTER U s assume a rofile for the population o directly or in stment facto cy user arri ion session ically saved SER AUTHE new scenari region of in f the region directly rel rs for each 39 ves at the si (scenario) or and presen NTICATION o has been s terest befor or state; thi ated to the s population r te's landing edit/delete ted in the tab tarted and d e beginning s informatio ize of the re ange.
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Final Report Project No. 08-94 40 TABLE 6: REGION OR STATE POPULATION ADJUSTMENT FACTORS REGION OR STATE POPULATION LOWER LIMIT UPPER LIMIT COST ADJUSTMENT Over 25,800,000 Population 25,800,000 30,900,000 2.7 18,900,000 to 25,800,000 Population 18,900,000 25,800,000 2.6 15,800,000 to 18,900,000 Population 15,800,000 19,800,000 2.5 10,900,000 to 15,800,000 Population 10,900,000 15,800,000 2.4 9,800,000 to 10,900,000 Population 9,800,000 10,900,000 2.3 6,900,000 to 9,800,000 Population 6,900,000 9,800,000 2.2 5,800,000 to 6,900,000 Population 5,800,000 6,900,000 2.1 4,900,000 to 5,800,000 Population 4,900,000 5,800,000 2.0 4,000,000 to 4,900,000 Population 4,000,000 4,900,000 1.9 3,300,000 to 4,000,000 Population 3,300,000 4,000,000 1.8 2,600,000 to 3,300,000 Population 2,600,000 3,300,000 1.7 2,100,000 to 2,600,000 Population 2,100,000 2,600,000 1.6 1,600,000 to 2,100,000 Population 1,600,000 2,100,000 1.5 1,300,000 to 1,600,000 Population 1,300,000 1,600,000 1.4 1,000,000 to 1,300,000 Population 1,000,000 1,300,000 1.3 900,000 to 1,000,000 Population 900,000 1,000,000 1.2 800,000 to 900,000 Population 800,000 900,000 1.1 700,000 to 800,000 Population 700,000 800,000 1.0 600,000 to 700,000 Population 600,000 700,000 0.9 500,000 to 600,000 Population 500,000 600,000 0.8 400,000 to 500,000 Population 400,000 500,000 0.7 300,000 to 400,000 Population 300,000 400,000 0.6 200,000 to 300,000 Population 200,000 300,000 0.5 100,000 to 200,000 Population 100,000 200,000 0.4 50,000 to 100,000 Population 50,000 100,000 0.3 Less than 50,000 Population 10,000 50,000 0.2
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