This preview shows page 1. Sign up to view the full content.
Unformatted text preview: The Pennsylvania State University The Pennsylvania State University
Department of Civil and Environmental Engineering CE 321: Highway Engineering Class # 40 – Trip Generation, Mode Choice and Traffic Assignment Spring 2008 Travel Demand Introduction Travel Demand Introduction Traffic forecasts for new construction Pavement Design Geometric Design (number of lanes, shoulder widths, etc.) Traffic forecasts for operational improvements
Estimate effectiveness of alternative improvement projects Considerations Considerations Overall regional traffic growth/decline
Provide sufficient level of service (LOS) Economic factors Trafficgenerating activities (work & shopping) Spatial distributions Traffic diversion Network or system effects Traveler Decisions Traveler Decisions Temporal decisions When to travel (e.g. what time) How often to travel (e.g. frequency per week) Destination decisions Modal decisions (car, bus, walking, etc.) Spatial or route decisions (origin & destination) Traffic Forecasting Traffic Forecasting Overview of Traffic Estimation Overview of Traffic Estimation Transportation Planning Process Transportation Planning Process Land Use Trip Generation* Trip Distribution Modal Split* Traffic Assignment* Land Use Descriptors Land Use Descriptors Character Intensity Location Trip Generation Trip Generation The purpose of trip generation estimation is to determine the number of trips to and from activities in an analysis area based on several different factors. Household trips instead of individual trips are modeled. Trip Generation Types Trip Generation Types Models seek to predict number of trips per hour or per day.
Work Trips Shopping Trips Social/recreational Trips Typical Trip Generation Model Typical Trip Generation Model Ti = b0 + b1 z1i + b2 z 2i + ... + bk z ki
Ti = number of vehicle-based trips of given type in some specified time-period made by household i; zki = characteristic k of household i; bk = coefficient estimated from data for characteristic k. Factors Affecting Trip Generation Factors Affecting Trip Generation Household Income Household Size and Composition Automobile Ownership Availability of Transit Density of Development Trip Generation Example 1 Trip Generation Example 1 Number of peakhour vehiclebased shopping trips per household = 0.12 + 0.09 (HH size) + 0.011 (HH income (1000’s)) – 0.15 (employment in HH neighborhood (100’s) HH has 6 members and annual income of $50,000. They currently live in neighborhood with 450 retail employees, but are moving to neighborhood with only 150 retail employees. Calculate number of vehiclebased trips made before and after move. Trip Generation Solution 1 Trip Generation Solution 1 Before Move: # trips = 0.12 + 0.09(6) + 0.011(50) – 0.15(4.5) # trips = 0.535 peakhour trips # trips = 0.12 + 0.09(6) + 0.011(50) – 0.15(1.5) # trips = 0.985 peakhour trips After Move: Trip Generation Example 2 Trip Generation Example 2 A neighborhood has 205 retail employees and 700 households with following characteristics:
HH size 2 3 3 4 Income $40,000 $50,000 $55,000 $40,000 Non-workers Workers in peak-hour departing 1 2 1 3 1 1 2 1 Type 1 2 3 4 Trip Generation Example 2 Trip Generation Example 2 There are 150 type 1, 200 type 2, 300 type 3, and 100 type 4 households. # shopping trips = 0.12 + 0.09 (HH size) + 0.011 (HH income (1000’s)) – 0.15 (employment in HH neighborhood (100’s) # social/recreational trips = 0.04 + 0.018(HH size) + 0.009 (HH income (1000’s)) + 0.16 (# nonworking HH members) Trip Generation Example 2 Trip Generation Example 2 Find: Total peak hour trips Method: Find # trips by purpose for each HH type Multiply by # HH of each type Add trips by type Type 1: 0.12+.0.09(2)+0.011(40)0.15(2.05)= 0.4325 trips/HH Shopping trips For 100 HH this yields 43.25 trips in peak period for shopping Type 2: 0.12+.0.09(3)+0.011(50)0.15(2.05)= 0.6325 trips/HH For 200 HH this yields126.5 trips Type 3: 0.687 trips/HH x 350 = 240.625 trips Trip Generation Example 2 Trip Generation Example 2 Total shopping trips: 441 vehicle based shopping trips in peak hour Using similar approach for social recreational trips: 542 vehiclebase social recreational trips in peak hour Work Trips: (Workers departing) x (#HH) for each type 1(100)+1(200)+2(350)+1(50) = 1050 vehiclebased work trips in peak hour Total peak hour trips: 441+542+1050=2033 This is a simplified approach, but gives you an idea of some of the influential factors we need to consider ...
View Full Document
- Spring '02
- Environmental Engineering