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Transportation Planning: Trip Generation

Transportation Planning: Trip Generation. CE 573 Lecture 9. Objectives. Trip generation concepts and factors Trip generation using regression. Trip Generation Terminology.

damian-blair
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Transportation Planning: Trip Generation

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  1. Transportation Planning:Trip Generation CE 573 Lecture 9

  2. Objectives • Trip generation concepts and factors • Trip generation using regression Michael Dixon

  3. Trip Generation Terminology • Journey (a.k.a. trip): one-way movement from a point of origin to a point of destination to satisfy the need or demand for activity • Home-based (HB) Trip: Home is the origin or destination • Non-Home-based (NHB): Neither end of the trip is the home of the traveler • Trip Production: Home end of a HB trip or origin end of a NHB trip Michael Dixon

  4. Trip Generation Terminology (continued) • Trip Attraction: non-home end of the HB trip and the destination end of the NHB trip • Trip Generation: total number of trips generated by households in a zone (HB and NHB), where the task remains to allocate NHB to various zones • Trip chaining: multiple trips are performed in sequence as a matter of efficiency, performing several activities Michael Dixon

  5. Classification of Trips—Trip Purpose • Homebased (HB) • Work (HBW) • School (HBS) • Shopping (HBSH) • Social and recreation (HBR) • Other (HBO) • Non-homebased (NHB)not classified into categories Michael Dixon

  6. Classification of Trips—Person Type • Income level • Car ownership • Household size • Household structure • group housing • single • family-head • family-worker Michael Dixon

  7. Trip Generation Studies • Household based • Zonal based Michael Dixon

  8. Factors affecting Trip Generation—Personal Trips (Production) • income • car ownership • household structure • family size • value of land • residential density • accessibility Michael Dixon

  9. Factors affecting Trip Generation—Personal Trips (Attraction) • office space • commercial space • educational space • number of employees • type of employment (e.g., government, retail, industrial) Michael Dixon

  10. Growth Factor Modeling • keep it within the context of the variables being forecast • Ti = a*X0 + b*X1 • Parameters (a = 2.5 trips/hh; b = 6 trips/hh) • Variables (X0 = no-auto hh’s; X1 = auto hh’s) • Base year X0 = 500 hh and X1 = 500 hh • Ti = 4250 trips generated • Forecast year everyone will own a car • Ti = 8500 trips  based on growth factor 1000/500 = 2 • Ti = 6000  based on changes in explanatory variables Michael Dixon

  11. Regression Analysis and Trip Generation—Zone Based • linear relationship between number of trips produced or attractedby a zone and average socioeconomic characteristics of households in zone Michael Dixon

  12. Regression Analysis and Trip Generation—Zone Based (cont.) • applicable if • zone characteristics reflect variation in trip making behavior • homogeneity • full spectrum of household conditions • dependent variable • total trips • average trips per household Michael Dixon

  13. Regression Analysis and Trip Generation—Household Based • Household-based: similar to zone-based except households are the sample (no longer dealing with zone averages of household characteristics) Michael Dixon

  14. Regression Analysis and Trip Generation—Household Based (cont.) • applicable because • reduced aggregation errormodeling the trip maker • independent of zone boundaries • care for • prediction of explanatory variables • non-linearities Michael Dixon

  15. Obtaining Zonal Totals • Zone-based regression • Household-based regression • If using zone average HH characteristics: • Ti = Hi * hh_trip_rate(hh_sizeave, incomeave) Michael Dixon

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