Conducting a Trip Generation Study. When to Collect Data Not covered by the ITE land use classification Location is in CBD Significant multi-modal component.

Slides:



Advertisements
Similar presentations
1 Update on Bicyclist & Pedestrian Data Collection and Modeling Efforts Transportation Research Board January 2010 Charlie Denney, Associate Michael Jones,
Advertisements

Airport Forecasting. Forecasting Demand Essential to have realistic estimates of the future demand of an airport Used for developing the airport master.
Chapter 12 Inference for Linear Regression
Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 ~ Curve Fitting ~ Least Squares Regression Chapter.
© Copyright 2001, Alan Marshall1 Regression Analysis Time Series Analysis.
Trip Generation at the Site Level. Norman W. Garrick Trip Rate Analysis Typically used to estimate trips from sites rather than for whole cities or region.
1 Introduction to Inference Confidence Intervals William P. Wattles, Ph.D. Psychology 302.
Addressing Deer Vehicle Accidents at the Community Scale Elizabeth I. Rogers, Ph.D. Dean B. Premo, Ph.D. White Water Associates, Inc. Amasa, MI.
Statistical Analysis Regression & Correlation Psyc 250 Winter, 2013.
LECTURE 3 Introduction to Linear Regression and Correlation Analysis
Lec 8, Ch4, pp :Volume Studies Know the definitions of typical volume study terms Know typical volume count methods (through reading) Be able to.
Least Square Regression
Chapter 9 Chapter 10 Chapter 11 Chapter 12
Least Square Regression
PERFORMANCE MODELS Lecture 16. Understand use of performance models Identify common modeling approaches Understand methods for evaluating reliability.
The Islamic University of Gaza Faculty of Engineering Civil Engineering Department Numerical Analysis ECIV 3306 Chapter 17 Least Square Regression.
Fall 2006 – Fundamentals of Business Statistics 1 Chapter 13 Introduction to Linear Regression and Correlation Analysis.
GEOG 111/211A Transportation Planning UTPS (Review from last time) Urban Transportation Planning System –Also known as the Four - Step Process –A methodology.
Traffic Signal Warrants
Lec 26: Ch3.(T&LD): Traffic Analysis – Trip generation
Lec 7, Ch4, pp83-99: Spot Speed Studies (Objectives)
Lec 14, Ch.8, pp : Intersection control and warrants (objectives) Know the purpose of traffic control Know what MUTCD is and what’s in it Know what.
Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 171 CURVE.
Design Speed and Design Traffic Concepts
Unit 3: Sample Size, Sampling Methods, Duration and Frequency of Sampling #3-3-1.
Correlation and Regression Analysis
Time Series and Forecasting
Correlation and Linear Regression
Linear Regression.
Introduction to Linear Regression and Correlation Analysis
Relationship of two variables
The Importance of Forecasting in POM
Regression Analysis (2)
Trip Generation for Street and Highways Lecture 14 CE 4720 Norman Garrick.
© The McGraw-Hill Companies, Inc., 2000 Business and Finance College Principles of Statistics Lecture 10 aaed EL Rabai week
© The McGraw-Hill Companies, Inc., Chapter 11 Correlation and Regression.
Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education.
Statistical Analysis Regression & Correlation Psyc 250 Winter, 2008.
AP Stat Review Descriptive Statistics Grab Bag Probability
Using APC Data for NTD Reporting APC University, Houston, Texas 16 October, 2014 John D. Giorgis Director of Strategic Planning Federal Transit Administration.
Copyright © 2011 Pearson Education, Inc. The Simple Regression Model Chapter 21.
Y X 0 X and Y are not perfectly correlated. However, there is on average a positive relationship between Y and X X1X1 X2X2.
Environmental Modeling Advanced Weighting of GIS Layers (2)
Regression & Correlation. Review: Types of Variables & Steps in Analysis.
PERFORMANCE MODELS. Understand use of performance models Identify common modeling approaches Understand methods for evaluating reliability Describe requirements.
% Trip Generation Trip Internalization & Pass-by Software (TIPS)
Economics 173 Business Statistics Lecture 19 Fall, 2001© Professor J. Petry
Copyright © 2014, 2011 Pearson Education, Inc. 1 Chapter 21 The Simple Regression Model.
Health Indicators and how they affect Death Rates in Developing vs. Developed Countries Malini Sen Cori Williams Monica Neuman Jaron Abelsohn.
Copyright © 2011 Pearson Education, Inc. Regression Diagnostics Chapter 22.
CE Urban Transportation Planning and Management Iowa State University Calibration and Adjustment Techniques, Part 1 Source: Calibration and Adjustment.
366_8. Estimation: Chapter 8 Suppose we observe something in a random sample how confident are we in saying our observation is an accurate reflection.
Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education.
Copyright 2010, The World Bank Group. All Rights Reserved. Producer prices, part 2 Measurement issues Business Statistics and Registers 1.
Transportation Planning Asian Institute of Technology
Linear Regression Essentials Line Basics y = mx + b vs. Definitions
AP Biology Intro to Statistics
Part 5 - Chapter
Part 5 - Chapter 17.
Presented by Harry C. Elinsky, Jr. Filtech, Inc.
Correlation and regression
Part 5 - Chapter 17.
Development of New Supply Models in Maryland Using Big Data
Example of PCR, interpretation of calibration equations
University of Maryland, College Park
Correlation and Regression
Least Square Regression
Data Literacy Graphing and Statisitics
Presentation transcript:

Conducting a Trip Generation Study

When to Collect Data Not covered by the ITE land use classification Location is in CBD Significant multi-modal component Size of site is not within ITE data range Insufficient sample size Inadequate statistical confidence Inconsistent from sites included in existing database (age of res., worker shifts, diff. ind. Var.) Multi-use development Questioned by professionals or local officials

Sample Size Determination Establish local trip generation rate  at least 3 sites preferably 5 Validate ITE trip generation rate  at least 3 sites Combine local data with ITE data  at least 2 sites Submit data to ITE  at least on site

Site Selection Transferrable (dev. Size, development mix, location w/r to network and dev. Patterns) At least 85% occupancy At least 2 yrs old Independent variable data available Can isolate site for counting (no shared parking, no shared driveways, limited ped traffic from nearby, limited transit, no through traffic) Security Single land use activity No construction Owner permission

Independent Variable Selection Available Variable size would affect trip generation Should be accurate not estimated or derived Currently used in manual

Development Data Requirements Site description –Square footage/units –Percent occupancy –Site acreage –Location (CBD, suburban, rural) –Name and description of principal use Site plan Adjacent street traffic volumes

Survey Periods Automatic count –7-day period ideal –1-day period at a minimum –2-day preferable Manual counts –2-hours for each peak Season –No-variation then pick average day –Variation then pick 30th or 50th highest hour Time of survey should represent typical activity (good weather, no big sale, etc.)

Conducting the Study Directional volumes 15-minute periods Two or more days of peak period counts Adjacent street hourly traffic counts for establishing peak period time Concurrent counts Site data from owners Verify automatic counts with short-period manual counts If needed, vehicle classification and vehicle occupancy

Establishing a Local Trip Generation Rate of Equation Hypothesis for why local conditions are unique Confirm that local data justify local trip generation rate/equation 3 sites (5 preferable) Difference of average greater than +/- 15% Local data consistent Rate or equation satisfies statistical standards For ave: –At least 3 data points –Std/ave <= 1.10 For Equation: –At least 4 data points –R2 >=0.75

Validation of Trip Generation Rates/Equations for Local Use STEP 1: Collect data at 3 sites or more STEP 2: Analysis of the local data, comparing to ITE –ITE data valid if… Criteria 1: trip generation rate for local site within +/- std Criteria 2: at least one site rate higher and one lower OR all with 15% Criteria 3: local data generally fall within ITE scatter Criteria 4: common sense If all of the criteria of STEP 2 are not met then consider local rate or equation

Combining Trip Generation and Local Data Combine if ITE and local rates within 15% Does not give precise std or regression equation Sum trip ends(ITE) = weighted average * average X * number of studies Sum independent variable units (ITE) = average X * number of studies