Establishment of any new development generates additional trips that may have negative effects on the existing traffic network. To assess the impact of the development traffic on the transport network and to identify reasonable solutions Traffic Impact Assessment (TIA) is performed. In the absence of sophisticated travel demand model TIA is carried out manually. In manual process, total trip generated from the development site is estimated by multiplying the trip rate with the development size. In this process the task can be completed very easily, but the accuracy of the calculation depends on the reliability of the trip rates used in the calculation. As Bangladesh does not have standard trip rates, TIA is generally performed by using trip rates obtained from the Institute of Transportation Engineers’ “Trip Generation” report, which is ideal for Western countries. In this research, trip rates of shopping centers in Dhaka city are estimated.This study conducts only for trip attraction rates of shopping centers having different sizes and located at different places (Dhanmondi, Gulshan and Siddheswari) in Dhaka city. In order to do so number of persons and vehicles entering the shopping centers in every fifteen minutes interval during peak periods are counted then converted for an hour. From the survey data, it is found that the trip attraction rates of small shopping centers are much higher than that of medium size shopping centers. Macroscopic model is also developed from the survey data. The macroscopic modelrelates the attraction rates of the shopping centers as a function of the physical features such as gross floor area, number of car parking, number of shops and availability of restaurants(available or not) in the shopping centers.

1. Presented by
S. M. Rahat Rahman
Ahsanullah University of Science and Technology, Dhaka,
Bangladesh.
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2. DETERMINATION OF TRIP ATTRACTION RATES
OF SHOPPING CENTERS IN DHAKA CITY
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3. WHY TRIP RATE IS IMPORTANT ?
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• Trip rate is important to develop trip generation model, which is
one of the part of travel demand forecast model.
• The purpose of trip generation model is to determine the number
of trips that are made from a TAZ (produced) and to a TAZ
(attracted) by the people.

4. •To determine the peak hour trip rate of the shopping centers
•To determine the trip attraction patterns with various parameters
•To determine trip rates variations with respect to size of shopping centers
•To develop a “Travel Demand Forecast Model”
•To assess the Traffic Impact
OBJECTIVE OF THE STUDYOBJECTIVE OF THE STUDY
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5. • Gross floor area
• Number of shops
• Shopping mall employee
• Number of parking spaces
• Availability of parking space
• Availability of restaurants
• Size of shopping center
• Socio-economic characteristics for
a zone
FACTORS AFFECTING TRIPFACTORS AFFECTING TRIP
ATTRACTION OF SHOPPING CENTERSATTRACTION OF SHOPPING CENTERS
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6. • Selection of shopping centers (Based on
gross area/ Location)
• Surveyed shopping centers:
Type 2: Medium Shopping Centers (MM)
Type 3: Small Shopping Centers(SS)
• Survey Time: 5 pm – 8 pm (in week days)
• Data collected:
>> People and vehicle entering and leaving
the shopping center in every 15 minutes
interval.
>> Information of different physical
features
MM
SS
SS
SS
MM
MM
STUDY METHODSTUDY METHOD
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7. Type
Name of the Shopping
Center
person trips/1000
ft2
/hour
person
trips/shop/hour
Type 2 (M)
Gulshan Pink City 3.83 3.975
Plaza A. R. 4.53 4.72
Fortune Shopping Mall 6.38 1.63
AverageAverage 4.913 3.442
Type 3 (S)
Aarong 18.38 432
A.R.A. Center 12.66 6.9
Navan Baily Star 15.81 6.187
AverageAverage 15.617 148.362
Table : Trip attraction rate of shopping centers based on different physical features
DEVELOPING THE TABLE FOR TRIP RATEDEVELOPING THE TABLE FOR TRIP RATE
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8. Macroscopic
model
Data:
- Floor Area
- Availability of parking
- Availability of
restaurant
Data:
- Total numbers of shop
- Availability of parking
- Availability of
restaurant
Y = 35.480 + 0.077 X1 + 63.136 X2 +
23.739 X3 (Model - 1)(Model - 1)
RR22
=0 .786=0 .786
Y = 34.036 + 0.10 X1 + 53.984 X2 +
23.778 X3 (Model - 2)(Model - 2)
RR22
= 0.850= 0.850
RegressionRegression
REGRESSION MODELREGRESSION MODEL
Y = Trip Attraction Rate of the Shopping
Center
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9. CONCLUSIONCONCLUSION
• Trip attraction rate of Type 1 (Large Shopping Centers)
shopping center.
• Trip attraction rate of other activity centers (Hospital,
Residential Building, Office Building)
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10. CONCLUSIONCONCLUSION
• Trip attraction rate of Type 1 (Large Shopping Centers)
shopping center.
• Trip attraction rate of other activity centers (Hospital,
Residential Building, Office Building)
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