Travel Demand
HW#3
Mohammad Almothffar
10/13/2016
Q1
An urban area consisting of four zones has the baseyear trip matrix
shown. The growth rates for the origin and destination trips have been
projected for a 25year period. Using Fratars (similar to doub
CEE 553 Travel Demand
Modeling
Topic 3 Trip Distribution
Modeling
TripDistribution Inputs and Outputs
Trip Distribution
Trip distribution is a process by which the trips
generated in one zone are allocated to other
zones in a study area.
This step esti
CEE 553
Travel Demand Modeling
Introduction and Overview
Why Are We Here Today?
What is the Goal for TDM?
Introduction/Overview: Travel Demand
Modeling
Why do we model travel demand?
How do we model travel demand?
Who uses model output?
Get the Big Pictur
I
N T E R D I S C I P L I N A R Y
L
I V E L Y
A
P P L I C A T I O N S
P
R O J E C T
Travel Demand
Forecasting
Interdisciplinary Lively Application Project
Title: Travel Demand Forecasting and Analysis for
South Texas
Authors:
Lei Yu and Della D. Bell
Depa
Trip Generation and
Attraction
Murillo, Kyle Emmanuel R.
Dela Cruz, Princess J.
Golechong, Genevieve Gillian R.
Lim, Farrah Mae Aileen M.
Santander, Zairel Allen A.
Travel Demand
Forecasting
Importance of Travel
Why do we live where you do?
Travel is bene
SAS OUTPUT
* Building Poisson Regression and Negative Binomial Model
https:/onlinecourses.science.psu.edu/stat504/node/223;
proc import datafile="C:\Users\Tams\Desktop\cat.csv" out=crash;
run;
Data E;
set crash;
run;
proc print data=E (obs=10);
run;
*List
Topic 2
Trip Generation Modeling
Introduction
Predicting the total number of trips generated (Oi)
and attracted (Dj) to/from each zone in the study
area from data on household socioeconomic
attributes.
Question: how many trips originate at each zone?
A
CEE 553 Travel Demand
Modeling
Topic 4 Mode Choice
Modeling
Introduction
Which mode (transit, walk, carpool, drive
alone, ) will be used?
Mode choice models attempt to replicate the
relevant characteristics of the traveler, the
transportation system, an
CEE 553 HW #2 Question #4 Solutions
Fall 2016
Develop the family of crossclassification curves
Determine the number of trips produced (by purpose) for a traffic zone containing 500 houses with an average
household income of $35,000. (Use high = 55,000; m
CEE 553 Travel Demand Modeling
Question #1
Vehicles per
household
0
1
2+
Area type
1. Urban: high density
2. Suburban medium
density
3. Rural: low density
HW #2
Fall 2016
Persons per household
1
2,3
4
100
200
150
300
500
210
150
100
60
Vehicles
available
Ua=
Ub=

0.30
0.30
Family Income (100$/week)
Between 1 and 2
Between 2 and 3
Between 3 and 4
Ca
Cb
+
3.23
I
Number of
Households
450
250
100
Ca ($)
Cb ($)
mean I
Ua
Ub
150
175
160
120
145
130
0.15
0.25
0.35
44.5
51.7
46.9
36.0
43.5
39.0
Number of h
Trip Distribution
Example/Slide 40 :
Trips Produced
Trips Attracted
A three zone city has the following trips produced in and
attracted to the three zones as follows. Determine the
number of zoneto zone trips in two iterations (Assume
Kij =1 for all zone
BASICS OF ITE TRIP GENERATION
AND ITS ROLE IN CALCULATING
TRANSPORTATION IMPACT FEES
Eric J. Tripi, P.E., PTOE
Iteris, Inc.
505 Belle Hall Parkway,
y, Suite 202
Mount Pleasant, SC 29464
2011 Growth and Infrastructure Consortium Conference
October 27th, 20
CHAPTER 8. TRIP DISTRIBUTION
NPTEL May 3, 2007
Chapter 8
Trip distribution
8.1
Overview
The decision to travel for a given purpose is called trip generation. These generated trips from each zone is
then distributed to all other zones based on the choice o
a)
Year
Pn=Population in the forecast year
n= 2000
Pb=Population in the base year b
P80=
250
2
P70=
240
5
t = population growth rate
P80
250
t=
=
P70
240
250
=
b= 1980
1.042
d=number of decades to extrapolate growth
(nb)
(20001980)
d=
=
10
10
=
2
Pn=Pbt
Column 1
Column 1
1
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.761079
R Square 0.579241
Adjusted R 0.526646
Standard E 0.722353
Observatio
10
X Va
6
5
ANOVA
df
Regression
Residual
Total
SS
MS
F
Significance F
1 5.746646 5.746646 11.01324 0.01056174
a) travel and access time are generic
cost divided by income and the number of cars in the household are specific
7 and 8 are alternative specific constants (modal penalties) for options 1 and 2. The third alternative is left as a
models work with the dif
Instructions
1.
In the worksheets below we solve the exercises corresponding to Chapter 10 of Modelling Transpor
2.
On each exercise follow the instructions given by the numbers
3.
The following cell styles define the status of the data in the workshee
Unfortunately the book had mistakes in both these examples. In the first exercise (15.1), the proportions pres
In exercise 15.2, the mistake is actually of a worse kind as with the data provided in the table for the values of
correctly for the new values,
Household type
No.
Income ($/month)
Inhabitants
0 cars
1 car
2 or more cars
Total
180
80
40
300
4000
18000
50000
4
4
6
Household type
% Households in
current year
Total Trips/day
current year
Growth Factor:
Income
0 cars
1 car
2 or more cars
Total
60%
27%
Instructions
1.
In the worksheets below you can find the exercises corresponding to Chapter 12 of Modelling Transp
2.
On each exercise follow the instructions given by the numbers 1
3.
The following cell styles define the status of the data in the work
= 0.5
= 0.0002
Pa Prob(U a U b )
Pa Prob( ta I tb )
Pa Prob( I
(tb ta )
/= 2500
Pa Prob( I 2500(tb ta )
(tbta)
10
9
8
7
6
5
4
3
2
I
25000
22500
20000
17500
15000
12500
10000
7500
5000
Pa
0.00
0.13
0.25
0.38
0.50
0.63
0.75
0.88
1.00
11
10
9
Instructions
1.
In the worksheets below we solve the exercises corresponding to Chapter 11 of Modelling Transport
2.
On each exercise follow the instructions given by the numbers
3.
The following cell styles define the status of the data in the workshe