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Trip Generation
K. Ramachandra Rao
CEL 442: Traffic and Transportation Planning
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Outline Introduction
Regression Analysis
Cross-classification or category analysis
Forecasting variables in trip generation analysis
Trip Generation and accessibility
Stability and updating of trip generation parameters
Traffic and Transportation Planning
Trip Generation 2
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Introduction The approach to urban travel demand modelling
commonly employed by the transportation planning profession is embodied in a type of model generally known as the urban transportation modelling system (UTMS)
UTMS consists of four stages as shown in the figure previously is often referred to as four-stage or four-step model Trip Generation
Trip Distribution
Modal Split
Trip Assignment
Trip Generation 3
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The UTMS - Steps
1. Trip Generation:
What generates the trips? Trip productions.
2. Trip Distribution: For the trips generated, how are they distributed (shared) among the
various destination points?
3. Mode Choice or Mode Split
For a given set of travelers on each chosen route, what fraction takes which mode (car, bus, walk, rail, air, etc.)
4. Traffic Assignment
Which routes are taken by the travelers from any origin to any destination?
Traffic and Transportation Planning
Trip Generation 4
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Four-step model
Trip Generation
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Four-step travel contd
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Some basic definitions
Home-based (HB) Trip This is one where the home of the trip
maker is either the origin or the destination of the journey
Non-home-based (NHB) Trip This, conversely, is one where
neither end of the trip is the home of the traveller
Trip Generation This is often dened as the total number of trips generated by households in a zone, be they HB or NHB. This is
what most models would produce and the task then remains to
allocate NHB trips to other zones as trip productions.
Sojourn
Activity
Tour/Trip Chain
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Definitions contd
At least three different trip purposes are defined, home-based work trips (HBW),
home-based other (or non-work) trips (HBO), and
non-home-based trips (NHB) - NHB trips have neither trip end at home
The trips that are predicted by a trip-generation model
for each zone are often referred to as trip ends
associated with that zone
Trip ends are classified as productions
attractions
Origin and production and destination and attraction are
not identical
The home-end of a trip is always the production -- it is
the household and its activity demands that gives rise to,
or produce, all trips; 8
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Definitions contd
The non-home end is the attraction (for NHB trips, the
origin is the production and the destination is the
attraction)
The term production and attraction are not defined in
terms of directions of trips but in terms of the land use
associated with each trip end
Trip production is defined as a trip end connected with
a residential land use in a zone (or alternatively as home
end of an HB trip or as the origin of an NHB trip)
Trip attraction is defined as a trip end connected with
non-residential land use in a zone (or alternatively as the
non-home end of an HB trip or the destination of an NHB
trip)
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Home and nonhome based trips
Trip Generation 10
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Trip generation - details Journey: this is a one-way movement from a
point of origin to a point of destination Trip: an onward and return journey (literally) Trip and Journey are used interchangeably
Classification of trips: by purpose
Work trips
Education trips
shopping trips
social and recreational trips
other trips
By time of the day
By person type
Trip Generation 11
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Factors affecting trip generation In trip generation modelling we are typically interested not
only in person trips but also in freight trips
Trip productions: The following factors are some if the important factors considered in many practical studies for trip productions:
income;
vehicle ownership;
family size;
household structure;
value of land;
residential density;
Trip attractions: The most widely used factor has been roofed space available for industrial, commercial and other services
Trip Generation 12
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Factors affecting trip generation
Freight trip productions and attractions: These normally account for few vehicular trips; in fact, at most they amount to 20% of all journeys in certain areas of industrialised nations
Important variables include: number of employees;
number of sales;
roofed area of firm;
total area of firm.
Trip Generation 13
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Trip Generation Developing and Using the Model
Calibrated
Model Relating trip making
to socio-economic
and land use data
Estimated
Target year
socio-economic,
land use data
Predicted
Target year
No. of Trips
Survey Base Year
Socio-economic, land use
And
Trip making
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Origins and Destinations
A worker leaves Zone 1 in the morning to go to
work in Zone 8
This results in 2 trip ends:
One Origin for Zone 1 One Destination for Zone 8
1
8
Residential
Non-residential
Residential
Non-residential
When that same worker leaves Zone 8 in the
evening to go to home to Zone 1
This results in another 2 trip ends:
One Destination for Zone 1 One Origin for Zone 8
Total Number of Trip Ends
Zone 1: 2 Trip Ends (1 O, 1 D)
Zone 8: 2 Trip Ends (1 O, 1 D)
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Productions and Attractions
A worker leaves Zone 1 in the morning to go to
work in Zone 8
This results in 2 trip ends:
One Production for Zone 1 One Attraction for Zone 8
1
8
Residential
Non-residential
Residential
Non-residential
When that same worker leaves Zone 8 in the
evening to go to home to Zone 1
This results in another 2 trip ends:
One Production for Zone 1 One Attraction for Zone 8
Total Number of Trip Ends
Zone 1: 2 Trip Ends (2 Productions)
Zone 8: 2 Trip Ends (2 Attractions)
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Origins and Destinations??
Productions and Attractions??
Based on the convention of trip generation models
Origins and Destinations are defined in terms of the direction of the trip
Productions and Attractions are defined by the land use
Residential Land use PRODUCES trip ends
Non-residential land use ATTRACTS trip ends
This is a useful distinction because of how trip generation models are
typically developed
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Modeling Productions and Attractions
Trip generation models typically model separately, i) residential trip production, ii) non-residential trip attractions
1
Non-residential
Residential
For example, Trip Ends for Zone 1 would be reported
as 1. 1000 Production Trip Ends 2. 500 Attraction Trip Ends
This approach works for home based trips (HB). But falls apart when we start to consider non-home based trips (NHB). Special techniques are developed to deal with
the relatively small number of NHB that occurs.
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Trips by purpose
Trip Generation 19
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Models: Regression Given the high correlations that typically exist between trip
generation and the variables listed previously, ordinarily least squares is used to estimate models that predict trip generation as a linear function of more of these variables
The selection of the most appropriate form in a particular case is usually based on experience and preliminary investigations into the matter
Regression models can be of the following form Pi= 1.229 + 1.379 V; Aj = 61.4 + 0.93E
(Simple linear regression)
Ti = 0.135P + 0.145U 0.253C; (Multiple linear regression)
The variables considered in the regression models should be able describe the trip generation and are not correlated among them selves.
The correlation coefficient between two sets of data x, and y is calculated as:
Trip Generation 20
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Models: correlations The correlation coefficients are given by:
Trip Generation
nn
n
YXXY
YYXX
SSSS
SSr
YY
XX
YYXX
YX
XY
2
2
2
2
22
r < 0 r > 0
r = 0 21
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Models: Simple linear
regression The equation is of the form,
yi = 0 + 1x (simple linear regression)
yi = 0 + 1x1 + 2x2 + 3x3 + 4x4 + + kxk (multiple linear regression)
Estimation of parameters: finding the estimates of the values of regression coefficients ( 0, 1) etc - simple linear regression
Trip Generation 22
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Models: Simple linear
regression - statistics
10 2 R
Trip Generation
n
SS
SS
SS
SS
SSR
SS
SS
SS
SS
SSSSSS
SS
nSS
YY
YYYY
E
YY
E
YY
R
YY
E
YY
R
ERYY
YY
YY
2
2
2
2
22
1
1
1
variation dunexplainevariation explained
Coefficient of determination, R2
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Trip Generation example
A multiple linear regression model is estimated for shopping-
trip generation during a peak hour. The model is
No of. Peak-hr vehicle based shopping trips/household
= 0.12 +0.09 (household size)
+0.11 (annual household income in lakhs of rupees)
- 0.15 (employment in household neighbour hood in
thousands)
A particular household has six members and has an annual
income of Rs. 5 lakhs. They currently live in a neighbourhood
with 4,500 retail employees, but are moving to a new home in
a neighbourhood of 1,500 retail employees. Calculate the
predicted number of vehicle-based peak-hour shopping trips
the household makes before and after the move Trip Generation 24
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Trip rate analysis
Trip rate analysis refers several models that are based on the determination of the average trip production or trip attraction rates associated with important trip generators within the region
Trip Generation 25
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Trip Rate Analysis Method of Trip Generation
Trip-Rate Analysis
Trip rate is estimated on characteristics of the trip generators
with in the zone. Production rates are determined using the
characteristics of the residential land uses and attraction rates
using the characteristics of the nonresidential land uses
Example
The characteristics of the trip generator is given in 1000 SQ. FT.
And the trip generation rate for each generator is given as TRIPS PER 1000 SQ. FT.
For example
Residential: Total 1000 Sq. Ft. = 2744 1000 sq. ft., Trip Gen. Rate = 2.4 trips/1000 sq.ft
TOTAL NO. of TRIP from residential land use = 2744*2.4 = 6586 Trips
This method of trip generation is often used to do site impact studies
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Trip rate example A particular ward in a city has lots of
abandoned factory land (15 ha). This was converted into commercial (9 ha) and residential (6 ha) land use by the Municipal Corporation authorities. Trip rate analysis of this ward is estimated as a) residential land use: 2.4 person trips per 100 sq. m ; b) commercial land use: 6.4 person trips per 100 sq. m. Identify the productions from residential land use in vehicle trips if the average occupancy in residential and commercial areas are 1.8 and 1.6 respectively.
Trip Generation 27
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Trip Generation Control Totals Because trip productions and attractions are
calculated separately, one must ensure that the area wide production and attraction totals are the same
This can be corrected by multiplying each zones trip attractions by the ratio of total productions and attractions
This approach to the problem is based on the expectation that trip production models are better predictors of trip rates than the somewhat cruder trip attraction models
In addition the balancing procedure must take into account the number of trips attracted to external zones
Trip Generation 28
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Trip Generation Control Totals
Where CTp= control total for productions
Pz = trip productions for each station
Pe = trip productions at each external station
Ae = trip attractions at each external station
Az = number of trip attractions at zone by purpose
Balancing Factor, for data given
= (20,900 + 1750 175)/19800 = 1.135 Trip Generation
z
P
eezP
A
CTFactor
APPCT
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References Meyer, MD and Miller, EJ (2001), Urban Transportation Planning,
McGraw Hill, 2nd Edition
Ortuzar, JD and Willumsen, HCW (2001) Modelling Transport, John Wiley, 3rd Edition
Papacostas, CS, and Prevedouros, PD (2001) Transportation Engineering and Planning, Prentice-Hall, 3rd Edition
Mannering, FL, Kilareski, WP and Washburn, SC (2005) Principles of Highway Engineering and Traffic Analysis, John Wiley, 3rd Edition.
Khisty, CJ, and Lall, B.K. (2003) Transportation Engineering: An Introduction, Prentice-Hall of India, New Delhi, 3rd Edition
Traffic and Transportation Planning
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