Trip Generation

K. Ramachandra Rao

CEL 442: Traffic and Transportation Planning

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

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

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

Four-step model

Trip Generation

5

Four-step travel contd

6

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

7

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

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

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

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

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

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

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)

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)

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

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.

Trips by purpose

Trip Generation 19

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

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

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

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

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

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

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

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

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

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