Transcript .: A Study on the Local Trip Generation Characteristics of Government Office Complexes

A Study on the Trip Generation
Characteristics of Government
Office Complexes
Reigna Jewel Ritz M. Macababbad
Dean D.S. Bartolome
Institute of Civil Engineering
University of the Philippines, Diliman, Quezon City
Jose Regin F. Regidor, Dr. Eng.
Associate Professor, Institute of Civil Engineering,
University of the Philippines, Diliman, Quezon City
A Study on the Trip Generation Characteristics of Government Office Complexes
INTRODUCTION
Trip generation data is a crucial input to determine the
impacts of different land use on transportation and
along its surrounding road networks.
Trip Generation
Figure 1. Conceptual framework of the study
A Study on the Trip Generation Characteristics of Government Office Complexes
In the Philippines, transport professionals adapt the
ITE Trip Generation manual as guide for trip
generation rates. However, the Philippines
compared to the United States has its own distinct
trip generation characteristics thereby necessitating
the estimation of local trip rates that would be
applicable to the Philippine setting.
This study focuses on estimation of trip generation
rates for government office complexes.
A Study on the Trip Generation Characteristics of Government Office Complexes
OBJECTIVES
To review existing trip generation rates for
offices;
To examine the trip generation characteristics of
government office complexes;
To estimate trip generation rates for government
office complexes; and
To compare these local trip generation rates to
ITE rates.
A Study on the Trip Generation Characteristics of Government Office Complexes
METHODOLOGY
Data are obtained through basic survey of the site
characteristics.
A total of eight government offices conform to ITE
Land Use Code 733 or government office complex
which consist of more than one building and meet
set criteria such as:
(1)
(2)
(3)
(4)
national / central office of government unit
have definite entry and exit points
exhibit Monday to Friday work schedule for office
transactions
transactions are mainly administrative in nature.
A Study on the Trip Generation Characteristics of Government Office Complexes
Gross Floor Area (GFA)
and number of
employees are the
identified independent
variables.
Two approaches are
used in quantitative
analysis: weighted
average rate and
regression equation.
Figure 2. Sample of Accomplished Survey Form.
A Study on the Trip Generation Characteristics of Government Office Complexes

Weighted Average Trip Rate

Regression Analysis

A linear trend line is fitted in the data plot wherein the
coefficient of x is the trip rate and the R2 values indicate
the relationship of independent and dependent variables.
A Study on the Trip Generation Characteristics of Government Office Complexes
RESULTS AND ANALYSIS
Qualitative
The study sites have other
factors that tend to
influence the trip rate and
these are:
Transport mode choice;
Table 1. Transport mode choice of
employees
Mode Choice
Office
Private
Public
(%)
(%)
Office A
40
60
Office B
20
80
Office C
15
85
Office D
50
50
Office E
20
80
Office F
30
70
Office G
40
60
Office H
20
80
Average
29
71
A Study on the Trip Generation Characteristics of Government Office Complexes
Nature of activities or
businesses conducted
within the offices;
The number of visitors
that each office attracts;
Accessibility of site; and
Presence of other land
use near the study sites.
Table 2. Average number of visitors
per day of offices
Office
Office A
Office B
Office C
Office D
Office E
Office F
Office G
Office H
Ave. No. of
Visitors per day
400
50
50
200
30
125
116
180
A Study on the Trip Generation Characteristics of Government Office Complexes
Figure 3. Physical Location of Study Sites.
A Study on the Trip Generation Characteristics of Government Office Complexes
Peak periods were
assumed from the work
shift of employees
shown in Table 3.
Table 3. Work Shift of Employees for
the Different Offices.
Work shift of at least
90% of Employees
Office A Flexi
Office B Flexi
Office C Flexi
Office D 8:00 am to 5:00
Office E Flexi
Office F 8:00 am to 5:00
Office G Flexi
Office H 8:00 am to 5:00
*** Flexi start time 7 :00 to 9:00
end time 4:00 to 6:00
Office
A Study on the Trip Generation Characteristics of Government Office Complexes
Quantitative
Table 4. Data summary of end trips for three scenarios
TOTAL END TRIPS
Office
Office A
Office B
Office C
Office D
Office E
Office F
Office G
Office H
GFA (100
m2)
Total No. of
Employees
Ave. No. of
Trip Tickets
Served per
day
236.1
53.5
34.3
196.9
121.3
142.1
112.5
205.1
1359
249
355
1749
248
1067
1550
1140
10
6
21
20
10
6
35
28
Ave. No. of
Visitors per
day
400
50
50
200
30
125
116
180
Case 1
Case 2
Case 3
NO. OF
EMPLOYEES
CASE 1 +
TRIP
TICKETS
CASE 2 +
NO. OF
VISITORS
2718
498
710
3498
496
2134
3100
2280
2758
522
794
3578
536
2158
3240
2392
3558
622
894
3978
596
2408
3472
2752
A Study on the Trip Generation Characteristics of Government Office Complexes
A. Gross Floor Area and Trip Ends
TOTAL
PERSON
TRIPS
TRIP RATE
(person trips / GFA)
TOTAL GFA
(100 m2)
TOTAL
PERSON
TRIPS
TRIP RATE
(person trips / GFA)
TOTAL GFA
(100 m2)
TOTAL
PERSON
TRIPS
TRIP RATE
(person trips / GFA)
1101.7
15434
14.01
1101.7
15978
14.50
1101.7
18280
16.59
4000
4000
4500
3500
3500
4000
3000
3000
3500
2500
2000
1500
1000
500
3000
2500
Trip ends
Trip ends
Trip ends
TOTAL GFA
(100 m2)
2000
1500
0
y = 13.612x
R² = 0.4982
50
100
150
200
Total GFA (100 sqm)
Figure 4. WATR & RE for Case 1
2000
1500
1000
1000
500
500
0
0
0
0
2500
250
50
100
150
200
Total GFA (100 sqm)
y = 14.018x
R² = 0.4789
Figure 5. WATR & RE for Case 2
250
0
50
100
150
200
Total GFA (100 sqm)
250
y = 16.245x
R² = 0.5763
Figure 6. WATR & RE for Case 3
****WATR & RE – Weighted Average Trip Rate and Regression Equation
A Study on the Trip Generation Characteristics of Government Office Complexes
B. Employees and Trip Ends
TOTAL
PERSON
TRIPS
TRIP RATE
(person trips / EMP)
TOTAL
EMPLOYEES
TOTAL
PERSON
TRIPS
TRIP RATE
(person trips / EMP)
TOTAL
EMPLOYEES
TOTAL
PERSON
TRIPS
TRIP RATE
(person trips / EMP)
15434
7717
2
15978
7717
2.1
18280
7717
2.4
4000
4000
4500
3500
3500
4000
3000
3000
3500
2500
2500
2000
1500
1000
500
y=
R² = 1
2000
1500
500
1000
1500
No. of Employees
Figure 7. WATR & RE for Case 1
2000
2000
1000
1000
500
500
0
0
0
2500
1500
0
0
2x1
3000
Trip ends
Trip ends
Trip ends
TOTAL
EMPLOYEES
y = 2.0611x
R² = 0.9988
500
1000
1500
No. of Employees
Figure 8. WATR & RE for Case 2
2000
0
y = 2.3511x
R² = 0.9854
500
1000
1500
No. of Employees
Figure 9. WATR & RE for Case 3
****WATR & RE – Weighted Average Trip Rate and Regression Equation
2000
A Study on the Trip Generation Characteristics of Government Office Complexes
C. Estimated Peak Hour Rates
For both independent variables, the peak hour factors
are obtained by considering Case 3 which represents
more likely scenario of a typical workday, the
percentage of trips caused by employees and the start
or end time of the employee’s work shift.
Table 7. A.M. and P.M. peak hour trip rates
Independent Variable
100 square meters of GFA
Employees
A.M. Peak
(person trips)
4.98
0.72
P.M. Peak
(person trips)
4.15
0.6
A Study on the Trip Generation Characteristics of Government Office Complexes
Comparison of ITE and Estimated Rates
Table 8. Comparison between ITE and estimated trip rates using GFA
Independent
Variable
Trip Generation
Rate Source
Land Use
Unit
Weekday
A.M. Peak
P.M. Peak
Size of
Independent
Variable
Number of
Studies
100 m 2 GFA
ITE (1997)
Code 733
Research Data
(Estimated Trip Rate)
Government Office Complex
Government Office Complex
Person trips / 100 m2 GFA
26.92
16.59
Directional Distribution
Directional Distribution
(50% entering, 50% exiting)
(50% entering, 50% exiting)
2.43
4.98
Directional Distribution
Directional Distribution
(89% entering, 11% exiting)
(98% entering, 2% exiting)
3.09
4.15
Directional Distribution
Directional Distribution
(31% entering, 69% exiting)
(2% entering, 98% exiting)
130.06
1101.7
1
8
A Study on the Trip Generation Characteristics of Government Office Complexes
Table 9. Comparison between ITE and estimated trip rates using employees
Independent
Variable
Trip Generation
Rate Source
Land Use
Employees
ITE (1997)
Code 733
Research Data
(Estimated Trip Rate)
Government Office Complex
Government Office Complex
Unit
Weekday
A.M. Peak
P.M. Peak
Size of
Independent
Variable
Number of
Studies
Person trips / Employee
6.09
Directional Distribution
(50% entering, 50% exiting)
0.55
Directional Distribution
(89% entering, 11% exiting)
0.70
Directional Distribution
(31% entering, 69% exiting)
2.4
Directional Distribution
(50% entering, 50% exiting)
0.72
Directional Distribution
(98% entering, 2% exiting)
0.6
Directional Distribution
(2% entering, 98% exiting)
575
7717
1
8
A Study on the Trip Generation Characteristics of Government Office Complexes
CONCLUSIONS
The trip generation characteristics of the eight
government office complexes in Quezon City were
examined through site characteristic surveys.
Estimates of trip generation rates for this type of land
use were obtained for the A.M. and P.M. peak hours
using the gross floor area and the number of
employees as independent variables.
The number of employees was found to be a better
estimator of trip generation than GFA.
A Study on the Trip Generation Characteristics of Government Office Complexes
The estimated trip generation rates stated in terms of
person trips is more suitable for Philippine use.
Suitability as well as degree of reliability was
established through comparison with ITE rates;
including the fact that more samples were obtained
from this study.
A Study on the Trip Generation Characteristics of Government Office Complexes
REFERENCES
[1] ALMEC Corporation (2005) Baseline study on the present status and issues on the MMUTIS
master plan projects in Metropolitan Manila.
[2] Clark, I. (2007) Trip rate and parking databases in New Zealand and Australia.
http://www.flownz.com/site/flowtransport/files/publications/aitpm%20Ian%20Clark%20Pa
per1%20final%20170807.pdf
[3] Institute of Transportation Engineers (2004) Trip Generation Handbook, Second Edition,
Washington, D.C.
[4] Institute of Transportation Engineers (1997) Trip Generation, 6th Edition, Washington, D.C.
[5] Institute of Transportation Engineers (1984) Using the ITE Trip Generation Report, Carl H.
Buttke, Ed., Washington, D.C.
[6] Institute of Transportation Engineers (1988) Transportation and Land Development, Stover,
V.G. and Koepke, F.J., Eds., Prentice Hall, Englewood Cliffs, New Jersey.
[7] Metro Manila Urban Transportation Integration Study (1997) Transportation demand
characteristics based on person trip survey. MMUTIS Technical Report No. 4, Manila,
Philippines.
[8] Regidor, J.R.F. (2006) A review of trip and parking generation rates in the Philippines.
Symposium on Infrastructure Development and the Environment 2006, SEAMEO-INNOTECH
University of the Philippines Diliman, Quezon City, Philippines, 7-8, December 2006
[9] Regidor, J.R.F. (2007) Traffic congestion begins with trip generation. Third Professorial Chair
Colloquium, University of the Philippines Diliman, Quezon City, Philippines, 4 July 2007
A Study on the Trip Generation Characteristics of Government Office Complexes
Thank you for your attention!
