Download - Introduction to transport planning
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CIVI 474 / CIVI 6411Introduction to
Transportation Planning
Ciprian Alecsandru
Concordia University
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IntroductionWhat?
To develop forecasts of travel demand and traffic growth
Why?To make decisions concerning new or existingtransportation facilities
Goals?to achieve better level of service in traffic flow, improved
safety, savings in energy consumption, travel time savings,economic growth, increased accessibility, etc.
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Basic Elements of TPSituation Definition
understand current situation that gave rise to need for improvement (e.g. travelpatterns, traffic volumes, prior studies, scope of study, public hearings).
Problem Definitionidentify the objectives to be accomplished (e.g. reducing traffic congestion,improve safety, and maximize highway-user benefits). Measures ofeffectiveness are needed such as travel time, delay, and queue lengths.
Search for Solutionsbrainstorming stage to bring in ideas, designs, locat ions, systemconfigurations. Technology plays a role and this stage requires data gathering,field testing, cost estimation, and operating policies.
Analysis of Performanceto determine investment cost of project and annual cost for maintenance andoperation, to estimate travel demand, and to collect other information on triplength, travel by time of day, noise, air pollution, etc.
Evaluation of AlternativesChoice of ProjectSpecification and Construction
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Transportation Planning OrganizationsPolicy Committee
Elected or appointed officials. Makes basic policydecisions and acts as board of directors for thestudy
Technical CommitteeEngineering and planning staff for evaluations andcost analysis. It includes highway, transit andtraffic engineers, and specialists in land-useplanning, economics, and computer modeling.
Citizens Advisory CommitteeCommunity to express goals and objectives of
local communities.
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Urban Transportation Planning Horizons
Short-term emphasis (1 to 5 years) for bettermanagement of existing facilities such assignal timing, car pooling, dedicated travellanes etc.Long-term emphasis (10 - 20 years) for newhighways, freeway lanes, bus lines, rapidtransit systems, overall transportation
system analysis and improvement.
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Forecasting Travel DemandMajor objective
To determine the number of persons or vehicles per unittime that can be expected to travel a given section undera set of land use, socioeconomic, and environmentalconditions. This process is as much art as it is a science.
Factors influencing travel demandLocation and intensity of land use
Socioeconomic characteristics of people in study areaExtent, cost, and quality of transportation services
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Forecasting Issues
Making accurate forecasting of economicgrowth/declineDeveloping methods to accurately forecast thetravelers decision making process
Temporal (when to)Destination (where to)Mode (how to get there)Spatial (which route to take)
Complexity of system equilibration
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Traveler Decision-Making ProcessSocioeconomics
Household incomeHousehold sizeCar ownership
Age Activity Patterns
WorkEducationShoppingRecreation
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Origins of Modern Urban TransportationPlanning (UTP)
US Bureau of Roads, 1944 Scientific methods (standardization,
systematization) applied to planning ofinfrastructure, in response to automobilecongestion
Exported abroad (e.g. Canada, WesternEurope, Australia)
Goals of UTP Predict and provide for future demand for
mobility (supply-side approach) Increase mobility by increasing vehicle speeds,
separating modes, etc. Reduced pollution from faster vehicles Comprehensive approach to surface
transportation infrastructure (roads and rail) Increasing welfare Serving public interest
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The UTP Process
Data collection Four step travel demand model (prediction
of future volumes of car & transit vehicletraffic)
Cost-benefit analysis of infrastructureproposals
Implementation of infrastructure expansionto provide for anticipated future volumes
Travel Forecasting Process
4-step process
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Basic Definitions
Trip GenerationForecasts the number of trips that will be made.
Trip DistributionDetermines where the trips will go.
Mode ChoicePredicts how the trips will be divided among the availablemodes of travel
Network AssignmentPredicts the routes that the trips will take traffic flow on
highway or transit links.
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Initial PreparationDefine study area
Define area boundaries, should consider future growth.Subdivide the area into zones.
What is a zone?Transportation analysis unit (TAZ).Zones vary in size depending on density of urbandevelopmentSocioeconomic characteristics are homogeneousInternal trips are minimizedUse of physical, political, and historical boundariesUse of census tracts
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Zone Types
CBD: zone could be a single blockUndeveloped area: zone may be >10 sq.milesTypically, zones bound homogenousactivities (all residential, all commercial,and all industrial).Zones are grouped into larger units knownas districts (district may contain 10 zones).
A city of 1M may have 100 districts.
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O/D Trips Analysis
Requirements:Data Collection: economic activities (employment, income,land use type and density, travel characteristics, existingtransportation facilities, etc.)Population and Economic Data for each zoneTransportation Inventories: computerized network of streets(links, nodes, centroids, etc.)Travel Surveys: for complete understanding of the travelpatterns within the study area and for O/D estimation (needtrip origin, destination, length, mode, route)
Calibration: applies to mathematical models to estimatetravel demand in terms of socioeconomic factors, land use,etc.
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Step 1: TRIP GENERATIONThe objective of a trip generation model is toforecast the number of person-trips that willbegin from or end in each traffic zone withinthe region for a typical day of the target year.Each trip has two trip ends
Trip Generation Trip Distribution Mode Choice Network Assignment
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Classification of Trips
The zonal trips are estimated separatelyby trip purpose.Examples: work trips, shopping trips,social/recreational, medical, and others
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Trip Generation Trip Distribution Mode Choice Network Assignment
Trip TypesHome-Based Trips:
Are all trips that either begin or end at home of thetrip maker (e.g. H ome Based Work, HBS hopping , etc.)
Non Home-Based Trips: Are trips with both ends at a place other than tripmakers residence (NHBS)Separate trip generation models are usuallydeveloped for each trip purpose, because thetravel behavior of trip makers depends on the trippurpose, time of day, etc.
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Objectives of Trip Generation
To develop relationships between trip endproduction or attraction and land useTo use these relationships for estimating thenumber of trips generated in the future underdifferent land-use conditions
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Trip Generation Trip Distribution Mode Choice Network Assignment
Trip Generation Methods1. Cross-Classification2. Rates based on activity units3. Regression
Preference is given to methods that usedisaggregated analysis (based on individualsample units: persons, HH, income, vehicleunits)Regression analysis uses zonal aggregateddata
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Cross-Classification
Used to determine the number of home-based trips (FHWA)Income and auto ownership are used for tripgenerationRequires surveys to construct curvesdescribing the zonal characteristics
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Trip Generation Trip Distribution Mode Choice Network Assignment
Average Zonal Income vs. Households inIncome Category
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Example Dataset (trips per day)
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Trip Generation Trip Distribution Mode Choice Network Assignment
Households by Auto Ownership and Income Category
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Households by Auto Ownership and Income Category
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Trip Generation Trip Distribution Mode Choice Network Assignment
Trips per Household per Day by AutoOwnership and Income Category
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Trips per Household per Day by Auto
Ownership and Income Category
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Trip Generation Trip Distribution Mode Choice Network Assignment
Trips by Purpose and Income Category
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Method 1: Cross-ClassificationComputing Trips Generated in a Suburban Zone
Example:Consider a zone that has 60 dwelling units (houses)Zone average income per house is $44,000Find the number of trips per day generated by thiszone for each trip purpose using figures 12.2 to12.5
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Trip Generation Trip Distribution Mode Choice Network Assignment
Step 1Find the percentage of households in each income categoryRefer to figure 12.2
Avg. zone income $44,000
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Step 1: Results
Income Category %HH
Low (< $32,000)Medium ($32,000-$48,000)High (> $48,000)
94051Sum = 100 %
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Trip Generation Trip Distribution Mode Choice Network Assignment
Step 2For each income category, find the distribution of autoownership/HH using figure 12.3, below:
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Step 2: Results
Autos / HH FromStep 1IncomeCategory
0 1 2+ Sum % HH
Low 54 42 4 100 9Medium 4 58 38 100 40High 2 30 68 100 51
% or probability of HH with low income and 0 autos
Q: How many HH are with medium income and 1 auto in a zone with 60 HH?
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Trip Generation Trip Distribution Mode Choice Network Assignment
Number of HH by auto and income
Autos / HH
IncomeCategory
0 1 2+ Sum
Low 5Medium 24High 31
Sum = 60 HHNumber of HH with 1 auto and mediumIncome [=40%*58%*60 HH]
= M1
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Step 3
Find the number of trips / HH / day for eachincome-auto category using figure 12.4
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Step 3: Results Autos / HH
IncomeCategory
0 1 2+
Low 1 6 7
Medium 2 8 13
High 3 11 15
Number of trips generated by eachHH with medium income and 1 auto
M2=
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Step 4
Find the total number of trips / day in eachincome-auto categoryMultiply M1 by M2 (dot product) and round-up
Autos / HHIncomeCategory
0 1 2+ Sum
Low 3 14 2 19Medium 2 111 119 232High 2 101 312 415Sum 7 226 433 666
Total trips from zone
M3=
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Trip Generation Trip Distribution Mode Choice Network Assignment
Step 5Find trips by purpose using figure 12.5
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Step 5: Results: % trips by purpose
Trip Purpose Total Trips
IncomeCategory
%HBO %NHB %HBW Sum fromM3
Low 53.7 31.1 15.2 19
Medium 51 32 17 232
High 49.2 32.8 18 415
666
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Trip Generation Trip Distribution Mode Choice Network Assignment
Final ResultsTrip Purpose
IncomeCategory
HBOHome-BasedOther
NHBNon-Home-Based
HBWHome-BasedWork
Sum from M 3
Low 10.2 5.9 2.88 19
Medium 232
High 415Sum 333 216 117 666
Total number of home-based work trips per day
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Problem
?
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Trip Generation ApproachesCross-ClassificationRates based on activity unitsRegression
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Rates Based on Activity Units
Trip generation is determined for residential zoneswhere the basic unit is the household .Trips generated at the household end are referredto as productions
Are attracted to zones for different purposes (e.g. work ,shopping , school , and medical services , etc.)
An activity unit can be described by related measures(e.g. square feet of floor space or number ofemployees).Trip generation rates for attraction zones can be
determined from survey data or are tabulatedspecialized handbooks
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Rates Based on Activity UnitsTrip generation rates for attraction zones can bedetermined from survey data or the rates tabulatedin specialized handbooks can be used
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Rates Based on Activity Units
Trip generation rates for attraction zones can bedetermined from survey data or the rates tabulatedin specialized handbooks can be used
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Rates Based on Activity Units
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Trip Generation Approaches
Cross-ClassificationRates based on activity unitsRegression
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Trip Generation Trip Distribution Mode Choice Network Assignment
Recall: Least Square RegressionDevelop mathematical relationships from empiricaldataLinear regression method estimates a relationshipbetween a dependent variable (e.g. number of tripsgenerated from a given zone) and a set ofindependent variables (e.g. number of persons in aHH, HH income, auto ownership, etc.)
Solution comes from an optimization problem thatseeks minimizing the sum of square deviationsbetween observed and estimated values
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Linear Regression Models
To estimate the number of vehicle-based tripsVariables: socioeconomic and/or distributional(residential and commercial) characteristics
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Example 8.1 (Mannering et al.)
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Solution
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Trip Generation Trip Distribution Mode Choice Network Assignment
Use the given linear regression to estimate the number of vehicle trips before and after the family moves.
Probabilistic ModelsLinear regression not always realistic(fractions of trips)Use of probabilistic distribution functions toestimate the probability of making a certainnumber of trips (0, 1, 2, )Poisson regression
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Poisson Regression
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Example 8.4 (Mannering et al.)
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Solution
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