CE 413 CE 513 Chapter 3 Estimating Transportation Demand Worksheet 2 you will find all the answer for this homework in Lector’s_2_chap_3_part_1 and part_2

CE 413 CE 513 Chapter 3 Estimating Transportation Demand Worksheet 2 you will find all the answer for this homework in Lector’s_2_chap_3_part_1 and part_2 Summer
2020
CE 413/CE 513 TRANSPORTATION SYSTEMS EVALUATION
Homework #2 – Due in Class 06/01/2020
NAME:
1. Indicate True (T) or False (F):
(2 points)
a. The 4-step network level transportation planning approach is suitable to
estimate travel demand along a corridor.
b. Traffic assignment does not refer to the estimation of zonal trip productions and
attractions.
c. A logit model is not used to estimate modal utilities.
d. Mobility does not represent the operational performance of a transportation
system.
e. Maximization of consumer surplus does not represent the objective of
maximization of benefit of public projects.
f. Ton-miles cannot be used as a measure of freight transportation demand.
g. A change in the level of service (or quality) of a transportation system cannot be
represented by a shift in the supply curve.
h. Cross-sectional models can be used to model demand functions.
2. The utility function values for automobiles and transits are 1.25 and -0.65, respectively.
Compute the number of trips by automobiles and transit, given the total trips to be 800?
(2 points)
Page 1 of 2
3. Consider a transportation company that provides a demand responsive transit service to elderly
and handicapped in a rural county on contract with a county government. List four performance
measures from the perspective of the county government.
(2 points)
4. If the aggregate demand function for an airline (DC to New York City) is V = 300 – 0.4P and
the supply function is P = 100 + 0.1V, where V is the number of trips demanded per year and
P is the price per trip in dollars. Determine:
(i)
Equilibrium price and equilibrium demand,
(ii)
Latent demand at the equilibrium price found in part (i),
(iii)
The price elasticity of demand when demand is 270.
(4 points)
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1/24/2018
Transportation Decision-making – Principles of Project Evaluation and Programming
Estimating Transportation Demand, Part 1
1
Estimating Transportation Demand
What is Demand?
Demand: The extent to which consumers seek a
product or service
Transportation Demand: The number of trips that
individuals/firms are prepared to make under a
given set of conditions (trip price, trip time, cost,
security, comfort, safety, etc.).
– The need generated by socio-economic activities
– A derived demand (work, shopping, returning
home, picking up or delivering goods, etc.)
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Estimating Transportation Demand
Passenger Transportation Demand by Mode
Air
Water
Rail
Auto
Bicycle
Walk
Bus
Other
3
Estimating Transportation Demand
Freight Transportation Demand by Mode
Air
Water
Rail
Truck
Pipeline
4
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Estimating Transportation Demand
5
Estimating Transportation Demand
What is a “modal share” of transportation demand?
Distribution of total travel demand among the
various modes.
Example, modal share of travelers between two cities
Walk
Travel Mode
Cycle
Auto
Bus
Rail
Air
0
20
40
60
Modal Share (Percentage)
80
100
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How do We Measure
Transportation Demand?
7
Estimating Transportation Demand
Units of Transportation Demand
• Number of vehicles
Point A
Point C
• Number of passengers
• Number of trips
5 mi.
• Number of vehicle-miles
• Number of passenger-miles
8 mi.
Point B
• Number of trip-miles
• Amount of freight (tons)
Point D
• Number of freight ton-miles
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Estimating Transportation Demand
Importance of Transportation Demand in Systems Evaluation
(Why do we need to estimate demand?)
• A basis for predicting the need for a proposed
system.
• A basis for deciding to go ahead with a proposed
project or policy change.
• Influences the proposed size of the project or the
scope of proposed operational policies.
• A basis for quantifying the benefits (positive
impacts) of the proposed facility.
• A basis for quantifying the costs (adverse impacts)
of the proposed facility.
9
Estimating Transportation Demand
Transportation Demand in Context of Classical
Economics
• Transportation Demand
The amount of trips that travelers or firms are
willing to undertake.
• Demand functions or demand models
Mathematical expressions that describe
transportation demand.
V = f(X1, X2, … Xn)
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Estimating Transportation Demand
Demand functions or demand models
V = f(X1, X2, … Xn)
X1, X2, … Xn are the variables that affect transportation
demand.
Of these variables, some are mode-specific (example, trip
price, trip comfort, trip time, etc.).
Others are generic (example, trip-maker’s income).
Multi-attribute vs. single-attribute demand functions.
The most common variable (or attribute) is Trip Price.
11
Estimating Transportation Demand
Demand functions or demand models
The most common variable is trip price.
Therefore, the most common demand function is as
follows:
V = f(Price)
Trip
Price (p)
V = f(Trip Price)
p1
1
2
p2
V1
V2
Quantity of trips
demanded, V
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Estimating Transportation Demand
Trip
Price (p)
V = f(Trip Price)
1
p1
2
p2
V1
V2
Quantity of trips
demanded, V
• When trip price increases, the demand for trips
decreases
• When trip price decreases, the demand for trips
increases
• In Economics, this is known as The Law of Demand
• Any exceptions? Yes. For abnormal goods and services,
the Law of Demand does not apply.
13
Abnormal demand curves
Estimating Transportation Demand
Price
(p)
Quantity of trips
demanded, V
Abnormal Goods
and Services
Giffen Goods
(Inferior, but staple
goods and services).
Veblen Goods
(a good made more
fashionable by a higher
price).
Note: In this course, we are only interested in transportation demand as a normal good!
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Estimating Transportation Demand
Shifts in the Transportation Demand Function
• Recall the basic, single-attribute demand function
• V = f(Price)
Trip
Price (p)
V = f(Trip Price)
1
p1
2
p2
V1
V2
Quantity of trips
demanded, V
• Is it possible to have a change in demand even when the
price is fixed?
• In other words, can we have a “shift” in the demand curve?
15
Estimating Transportation Demand
Shifts in the Transportation Demand Function
What Causes Shifts in the Demand Curve?
(a) A Shift in the Right Direction
Cause: A competing good or service is made less attractive to the customer
Example:
For auto travel,
– increased auto security,
safety;
-reduced transit comfort,
safety, and security, or
– higher transit prices
can cause an increase in
auto demand even when
auto trip price is constant
Price (p)
DA
Example,
Auto Trip
Price
DB
Increased Transit Price;
Reduced Transit quality of service;
Increased Auto quality of service)
p
Base Case (Example, Auto Demand)
VA
VB
Quantity demanded, v
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Estimating Transportation Demand
(a) A Shift in the Left Direction
Cause: A competing good or service is made more attractive to the customer
Example:
For auto travel,
– decreased auto security,
safety;
– increased transit comfort,
safety, and security, or
– reduced transit prices
can cause a decrease in
auto demand even when
auto trip price is constant
Price (p)
DA
Example,
Auto Trip
Price
DB
Reduced Transit Price;
Enhanced Transit quality of service;
Reduced Auto quality of service)
p
Base Case (Example, Auto Demand)
VC
VA
Quantity of Auto Trips
demanded, V
17
Estimating Transportation Demand
Classification of Demand Models
Single attribute vs. multiple attribute demand models
Single attribute: only one variable
Demand = f(X)
Examples:
Demand = f(Trip Price)
Demand = f(Trip Time)
Multiple attribute: more than one variable
Demand = f(X1, X2, …, XN)
Examples: Demand = f(Trip Price, Time, Safety, Comfort, etc.)
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Estimating Transportation Demand
Classification of Demand Models
Aggregate vs. disaggregate demand models
Aggregate demand models: the variables are combined
for all travelers and pertain to the areas (regions, cities,
towns, etc.)
Overall Demand = f (Characteristics of the demand-generating regions)
Characteristics include population, regional area, number or total
area (sq. ft.) of industries, shops, schools, etc.),
Disaggregate demand models: the variables are for
each individual traveler
Demand = f (Characteristics of individual traveler)
Characteristics include income, occupation, etc.
f is often an econometric discrete choice models (logit, probit, etc.)
Overall demand = sum of demand of individual travelers
19
Estimating Transportation Demand
Classification of Demand Models
Deterministic vs. stochastic
Deterministic demand models: the exact outcome (travel demand)
can be predicted with certainty.
– Makes the demand estimation process simple
– May not be realistic
Stochastic demand models: the exact outcome (travel demand) is
not known with certainty
– The estimated demand falls between a certain minimum and
maximum, and is governed by a probability distribution
– Each demand level has a certain probability of occurring
– Makes the demand estimation process
relatively complicated
– More realistic in real world where there
20
are so many uncertainties
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Estimating Transportation Demand
Classification of Demand Models
Time Series vs. Cross-sectional Models
26,000
34,000
42,000
53,000
61,000
2002
2003
2004
2005
2006
2001
72,000 trips/day
2009
Y in 2009?
Pop = 2.3m
REGION 1
Ave Income=
31k
Area of
Business = 4.1k
61,000
Pop = 2.9m
Ave Income=
33k
REGION 2
Area of
Business = 4.7k
Given this set of information for population living in
region, average annual income in region and area used
for business in region (in acres),
53,000
Pop = 2.8m
Ave Income=
33k
REGION 3
Area of
Business = 4.5k
How do we estimate daily demand in Year 2009 for
Region 1?
72,000
Pop = 3.0m
Ave Income=
35k
REGION 4
Area of
Business = 4.7k
34,000
Pop = 2.4m
Ave Income=
31k
REGION 5
Area of
Business = 4.2k
42,000
Pop = 2.6m
Ave Income=
32k
REGION 6
Area of
Business = 4.4k
21
Estimating Transportation Demand
Example of demand estimation using time series
2001
26,000
34,000
42,000
53,000
61,000
2002
2003
2004
2005
2006
72,000 trips/day
2009
Y in 2009?
REGION 1
Given this set of information for population living in region, what is the demand
in Year 2009 for Region 1?
120
Population (in 1,000)
Perform linear regression,
y = 9.2x + 25
R² = 0.9968
100
Y (in 1,000s) = 9.2 (year – 2001) + 25
80
For year = 2009,
60
Y = 98.6
40
Travel demand in 2009 = 98,600 trips/day
20
0
0
2
4
6
8
10
22
(Year ‐ 2001)
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Estimating Transportation Demand
Example of demand estimation using cross-sectional data
26,000
2001
Pop = 2.3m
REGION 1
Area of
Business = 4.1k
Pop = 2.9m
REGION 2
Area of
Business = 4.7k
Pop = 3.5m
Ave Income=
31k
53,000
72,000
Pop = 3.0m
Ave Income=
35k
REGION 4
Area of
Business = 4.7k
34,000
Pop = 2.4m
Ave Income=
31k
REGION 5
Area of
Business = 4.2k
42,000
trips/day
Pop = 2.6m
Ave Income=
32k
REGION 6
Area of
Business = 4.4k
Ave Income=
40k
61,000
Ave Income=
33k
Area of
Business = 4.5k
Area of
Business = 5.3k
Ave Income=
33k
Pop = 2.8m
REGION 3
Y in 2009?
2009
Given this set of information for
population living in region, average
annual income in region and area
used for business in region (in
acres),what is the demand in Year
2009 for Region 1?
Perform multiple linear regression,
Y (in 1,000s)
= -197.8 + 37.0 (Pop in millions) + 3.4 (Ave Income in
thousand dollars) +8.2 (Area of Business in thousand
acres)
For 2009, pop = 3.5m, ave income = $40k, area of
business = 5.3k acres:
Y = 111.2
Travel demand in 2009 = 111,200 trips/day
23
Estimating Transportation Demand
Example of demand estimation using panel data
2001
26,000
Pop = 2.3m
REGION 1
Area of
Business = 4.1k
Pop = 2.9m
REGION 2
Area of
Business = 4.7k
2002
Y in 2002?
Pop = 3.5m
Ave Income=
31k
Area of
Business = 5.3k
61,000
Ave Income=
33k
53,000
Area of
Business = 4.7k
Ave Income=
40k
Ave Income=
35k
Given this set of information for
population living in region, average
annual income in region and area
used for business in region (in
acres),what is the demand in Year
2009 for Region 1?
Pop = 2.4m
Pop = 2.8m
REGION 3
Area of
Business = 4.5k
Pop = 3.0m
REGION 4
Ave Income=
33k
72,000
Perform multiple linear regression,
Y (in 1,000s)
= -197.8 + 37.0 (Pop in millions) + 3.4 (Ave Income
thousand dollars) +8.2 (Area of Business in thousan
acres)
For 2009, pop = 3.5m, ave income = $40k, area of
business = 5.3k acres:
Y = 111.2
24
Travel demand in 2009 = 111 200 trips/day
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Estimating Transportation Demand
Classification of Demand Models
• Further classification of Crosssectional demand models:
H
C
– Demand estimation based on
end point attributes only, vs.
– Demand estimation based on
attributes of entire network.
H
C
25
Estimating Transportation Demand
Demand Estimation Based only on Attributes of Corridor/Project
or its End Points
Examples
1
2
1. Air travel demand
V12 
Z
1  1e  2 / Q
Z is a measure of socio-economic activity
Q is schedule frequency
Beta’s are model parameters to be estimated
2. Intercity passenger demand models
Kraft-SARC model, McLynn model, Baumol-Quandt model:

V12m  0 P1 P ,1 P2 P ,2
 I
 I ,1  I ,2
1
I2
 t
 t ,m ,1  t ,m ,2
m ,1
t m,2
 c
t ,m,1 t ,m,2
m ,1
cm,2

P is population, I is income, t is the time taken by mode m, c is the
average passenger cost of taking mode m, betas are the model
parameter to be estimated
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Estimating Transportation Demand
Demand Estimation Based only on Attributes of Corridor/Project or its
End Points
1
Examples
2
3. Transit demand
V12   0T 1 p 2 A3 I 4
V12 = transit ridership/hr between 1 and 2
T = transit travel time (hrs)
C = transit fare ($)
A = cost of auto trip ($)
I = average income per capita ($)
 = model coefficients to be estimated
27
Estimating Transportation Demand
Demand Estimation Based only on Attributes of Corridor/Project or
its End Points
H
C
Is it enough to estimate demand for a link based only on attributes of the end points?
A
H
C
B
D
E
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Estimating Transportation Demand
Demand Estimation based on Attributes of Entire Parent Network
Trip Generation:
What factors generate and .. Trips in a zone.
2. Trip Distribution:
What are the origins and destinations of these trips?
3. Traffic Assignment
Which routes are taken by the trips an origin to a destination?
4. Mode Choice or Mode Split
For a given set of travelers on each route, what fraction takes which
mode (auto, bus, walk, rail, air, etc.)
This is known as the 4-step Transportation Planning Model (TPM)
29
Estimating Transportation Demand
Classification of Demand Models
Classification by the Functional Form of the Demand Model
Generally, V = f(X)
where X is:
– (for disaggregate demand), is a factor (or vector of factors) that
affects the individual travel demand, such as trip price, time, safety,
comfort, etc.
– (for aggregate demand), is a factor of vector of factors that affect
the overall travel demand, such as population, average income,
employment levels, etc.
– for a time series demand model (often aggregate), is simply the
time in years
The Big Question: What is the shape of f?
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Common Functional Forms
Linear
Power
V
V
Demand = aXb, b>1
X
X
Demand = a + bX
V
Demand = aXb, b
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