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5 Chapter 1 Introduction
6 Chapter 2 Overview of the Trip Generation Methodology for Infill Development
8 Chapter 3 Application of the Household Travel Survey Method
8 3.1 Background and Source of Surveys 9 3.2 Practitioner Need for Broad Applicability
9 3.3 Required Data for the Household Travel Survey Method 10 3.4 Linked-Trip Data
10 3.5 Geographic Units of Urban Area Data
12 Chapter 4 Example Adjustment Factors Using San Francisco Bay Area Travel Survey Data
12 4.1 Household Travel Survey Data
12 4.2 Defining General Urban and Urban Center Context 14 4.3 Weighting and Expansion of Survey Data
15 4.4 Estimated Mode Share by Land Use 15 4.5 Estimated Vehicle Occupancy by Land Use
16 4.6 Use of Local Travel Demand Model to Derive Adjustment Factors
17 Chapter 5 Selection of a Household Travel Survey as a Case Study
17 5.1 Criteria for Selecting a Metropolitan Area with a Suitable Household Travel Survey
17 5.2 Selection of a Metropolitan Area 18 5.3 Sufficiency of the Dataset 18 5.4 Next Steps in the Process
19 Chapter 6 Analysis of Household Travel Survey Data
19 6.1 GIS Analysis
19 6.2 Household Travel Survey Analysis
22 Chapter 7 Selection of Candidate Sites for Cordon Counts
22 7.1 Selecting Urban Infill Sites for Cordon Counts 23 7.2 Summary of the Data Collection Procedures
24 Appendix A Overview of Household Travel Surveys Assessed for Case Study
25 Appendix B Detailed Mode Share Tables for San Francisco Bay Area Example
C o n t e n t s
27 Appendix C Example Output Tables for San Francisco Bay Area Infill Area Mode Share and Vehicle Occupancy Adjustment Factors
30 Appendix D Detailed Mode Share Tables for the Washington, D.C., Case Study
32 Appendix E Output Tables for Washington, D.C., Infill Area Mode Share and Vehicle Occupancy Adjustment Factors
35 Appendix F Prioritization of Candidate Sites for Cordon Counts
37 Appendix G Example Data Summaries for Candidate Sites
45 Notes and Citations to Supplemental Technical Report
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This technical report supplements NCHRP Report 758:
Trip Generation Rates for Transportation Impact Analyses of Infill Developments. It is a consolidation of interim reports prepared during the development of the recommended methodology for estimating vehicular trip generation of infill development. Specifically, this report describes the procedure the research team used to extract data from HTSs and the use of the data to derive factors used in the methodology.
The objective of the research presented in NCHRP Report 758 is to develop an easily applied methodology to estimate automobile trip generation and mode shares of non-vehicular trips that can be used in the preparation of site-specific transportation impact analyses of infill devel-opment projects located within existing higher-density built-up areas.
C H A P T E R 1
Introduction
The following overview of the methodology is paraphrased from Chapter 3 of the report.
The research team selected an approach for estimating the trip generation of infill development categorized as “ITE rate adjustment based on empirical data,” as described in the main body of the report. This approach met the research objective and, to varying degrees, all of the selection criteria. One of the predominant reasons this approach was selected is because it can be applied to the land uses in the ITE Trip Generation Manual1 and has few, if any, restrictions on land use catego-ries and applicable geography. The approach of employing empirical data provides the practitioner with flexibility in that there are no limitations or constraints in regards to land use classification or geography. Conceptually, the approach can be described with the following simplistic equation:
= ×
Auto_Trips(INFILL) Auto_Trips(ITE) Adjustment_Factor(INFILL)
The recommended methodology applies adjustment fac-tors to data from the ITE Trip Generation Manual, resulting in a relatively straightforward conversion of data representa-tive of isolated automobile-dominated suburban land uses to data representative of dense urban areas served by extensive multimodal transportation systems. The selection process and subsequent development of the approach resulted in two ways to develop the adjustment factors employed by the approach:
1. Proxy site method – Adjustment factors are based on data collected at sites with similar characteristics and located in similar contexts as the proposed infill development site (the project being studied). The research team developed procedures for identifying proxy sites and obtaining the
required data to develop the adjustment factors applied in the methodology.
2. Household travel survey method – Adjustment factors derived from empirical data found in the database of a regional HTS. This method extracts data representing the desired infill land use and context within physical areas at the scale of the TAZ. Extraction of data representing spe-cific land uses is based on the activities and trip purposes recorded by the travelers during the survey.
As shown in Figure 2.1, the approach is made up of five primary steps:
1. Baseline ITE trip generation data are used to estimate the vehicular trip generation of the proposed infill development.
2. Baseline mode share and vehicle occupancy adjustment factors are used to convert baseline vehicle-trip estimates to baseline person trips.
3. An infill mode share adjustment factor representing the appropriate context is used to convert baseline person trips to infill person trips for those who travel by automobile.
4. An infill vehicle occupancy adjustment factor representing the appropriate context is used to convert infill person trips for those who travel by automobile to infill vehicle trips.
5. Infill vehicle trips are used in the evaluation of site traffic impacts.
This supplemental technical report describes the proce-dures used to develop the infill mode share and vehicle occu-pancy adjustment factors using the household travel survey method described in the main report.