Lec 9, TD part 2: ch5.4.1

1
Lec 9, TD part 2 ch5.4.1 H/O, pp.460-477 Trip
Generation

• TD Part 2 topics

• Estimating the number of trips generated by zonal
  activities
• Trip generation estimate by regression analysis
• Trip generation estimates by trip rates/unit
• Trip generation estimates by category analysis
• Method to balance trip productions and attractions

2
What is trip generation?

• It is the process by which measures of urban
  activity are converted into numbers of trips.
• In trip generation, the planner attempts to
  quantify the relationship between urban activity
  and travel.

It means both trip productions and trip
attractions.
3
A zone produces and attracts trips
Zone i

• of dwelling units

• Shopping center employees
• Etc.

Depending on the activities in the zone, it can
produce and/or attract trips. Transportation
planners estimate these trips first.
4
Three ways for estimating the number of trips
produced

• Regression models

Y dependent var. (trips/household) X1, X2, etc.
independent variables

• Trip rates, like of trips/1000ft2, ITEs trip
  generation rates (Fig. 5.10 of the text)

• Category analysis (cross-classification analysis)

5
Regression models (often, simple or multiple
linear models) advantages and disadvantages

• Easy and relatively inexpensive.
• Correlation among independent (explanatory)
  variables may create estimation problems ? If
  correlated, choose only the variable(s) that has
  the highest correlation with the dependent
  variable. Stepwise regression may help to find
  it.
• The assumptions of linearity and additive
  impacts on trip generation may be wrong.
• Best fit equations may yield counterintuitive
  results (see Eq. 5-11 of Meyer Miller).
• By using zonal averages, important socioeconomic
  variations within the zone may be obscured or may
  yield spurious results.

6
Regression models (cont) something you want to
be aware

• A high R2 (Coefficient of determination) by
  itself mans little if the t-test is marginal or
  poor,
• Just having a large number of independent
  variables does not mean very much. ? Choose only
  the independent variable that have highest
  correlation with the dependent variable and low
  correlation among the independent variables.
• Check the coefficients are logical or not. Trip
  generation is never negative in reality no
  matter what value the independent variable has.

• See the EXCEL file.
• Then, we will go through Example 1 to get some
  hints.

7
Trip generation rates
This is an example of trip generation rate
information taken from the ITE Trip Generation
Handbook. Some land use has a lot of data points
like this one, but others (many of them) have
only sparse data points. This handbook is
evolving and every year new data are added.
8
Category analysis (cross-classification analysis)
(Groups individual HHs according to common
socioeconomic characteristics, see p.275 of the
text)

• Less aggregated than trip rates and regression
  models
• See the list of advantages and disadvantages in
  the book to see why this is popular (p.277 of the
  text)

HB Trip Production example
See Examples 2 3.
9
Trip attraction

• Trip attraction rates can be made by analyzing
  the urban activities that attract trips.
• Trips are attracted to various locations,
  depending on the character of, location, and
  amount of activities taking place in a zone.
• Three tools are used for this end too, but
  obviously types of independent variables used are
  different.

We will do go over Example 4. Also see Table 11-5
( c) in the handout.
10
Control totals (ch5. P.277)

• The area-wide production and attraction must be
  the same. In general they are not the same after
  calculation because trip production and
  attraction are estimated separately by different
  models with different variables.

CTp control total of productions Pz trip
productions for each zone Pe trip productions
at each external station Ae trip attractions at
each external station
I-E trips (Pe)
I-I trips (Pz)
Compute the factor used to balance productions
attractions.
E-I trips (Ae)
(See Figure 5.11 of the text)