Presented by S. M. Rahat RahmanAhsanullah University of Science and Technology, Dhaka, Bangladesh.

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DETERMINATION OF TRIP ATTRACTION RATES OF SHOPPING CENTERS IN DHAKA CITY

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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.

•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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• 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 TRIP FACTORS AFFECTING TRIP ATTRACTION OF SHOPPING CENTERSATTRACTION OF SHOPPING CENTERS

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• 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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Type Name of the Shopping Center

person trips/1000 ft2/hour

person trips/shop/hour

Type 2 (M)

Gulshan Pink City 3.83 3.975Plaza A. R. 4.53 4.72

Fortune Shopping Mall 6.38 1.63

Average Average 4.913 3.442

Type 3 (S)

Aarong 18.38 432A.R.A. Center 12.66 6.9

Navan Baily Star 15.81 6.187AverageAverage 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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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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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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