CE 303 - Transportation EngineeringTransportation Planning

Lecture 2 - Trip Generation

Fig. 2.1 Trip ends, production and attractions. Fig. 2.2 Trip generation

An urban region is first divided into zones to study its travel requirements. A zone can be residential, non residential or both residential and non residential. Residential zones generate trips while non-residential zones attract trips. However, a zone which is both residential and non residential will produce and attracts trips. To estimate the future (target year) trips generated by a zone it is necessary to know the present (base year) trip generating rates. Using mathematical models the total trips produced by or attracted by each zone can be determined to estimate the total trips generated by an urban region.

Residential zones themselves are too large to be considered to determine the travel patterns. Residential zones have households as the smallest entities to ease the travel analysis.

2.1 Zones and households

Individual travel patterns are difficult to trace in a region. Therefore, a region is divided into easy travel analysis zones. In older models a zone is the smallest entity for trip making interest. Models were calibrated using overall zonal characteristics.

The zonal characteristics (attributes) like zonal population, average zonal income, average vehicle ownership, average adults per household are used in the analysis.

Zonal averages in a residential zone do not show variability of the attributes within the zone. This affects accuracy of estimated trip levels. Eg. Income levels differ from household to household. Therefore, households are used as the smallest entities in modern trip production models. Zone based models are known as aggregate models and Household based models are known as disaggregate models.

2.2 Trip productions and attractions

Trips generated in a model for each zone are trip ends denoted by Qi associated with that zone. The trip ends are either origins or destinations. Generated trips can be either trip productions or trip attractions. The rule is, residential zones produce trips (Pi) and non-residential zones attract trips (Aj).

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2.2.1 Trip purpose

The next information that has to be extracted in the trip generation analysis is the purpose of the trip. This can tell the planner a trip’s destination and the travel mode. By purpose, the trips are commonly classified as,

(i.) Work trips(ii.) School trips

(iii.) Shopping trips(iv.) Social trips(v.) Recreational trips.

2.3 Trip generation models

It is necessary to develop a mathematical model which is able to estimate the trips generated by a zone using the zonal attributes. The commonly used mathematical models are, (1.) Regression, (2.) Trip rate analysis and (3.) Cross classification models.

2.3.1 Regression models

In a regression analysis model the trip generation is given as a dependant variable by inputting the zonal trip attributes as the independent variables. An example is the simple linear regression model,

Y = 0 + 1*X1 + 2*X2 + 3*X3 + 4*X4 (2.1)Y is the dependent variableX1, X2, X3, X4 etc. are independent variables.0, 1, 2, 3, 4 etc. are the model parameters.

The trip generation regression models do not necessarily have to be linear regression models. But linear regression models are commonly used in the estimation of trip generation. A regression model has to be calibrated using observed data. That means the constants 0 , 1 , 2 , 3 ,4 etc. have to be determined by regression using observed values of the independent variables (attributes). The zonal trips generated can be estimated by inputting the zonal attributes to the calibrated model.

Example: The zonal trip production per day in any zone of an urban region is given by the regression model,

Y = 0 + 1*X1*(2X2 + 3X3 + 4X4) (2.2)Where, X1 = zonal population

X2 = average zonal income X3 = average vehicle ownership X4 = average adults per household0 = 150, 1 = 3.5 2 =.003 3 =1.5 4 = 1.7.

Calculate the number of trips generated per day by each zone which have the following zonal attributes,

Zone i X1 X2 X3 X4

1 1750 Rs 40000 1.8 2.72 2240 Rs 20000 0.6 5.83 1980 Rs 35000 1.2 3.6

Answer.Trips production per day, by Zone 1 =150+ 3.5* 1750* (0.003*40000+1.5*1.8+1.7*2.7) = 118301by Zone 2 =150+ 3.5* 2240* (0.003*20000+1.5*0.6+1.7*5.8) = 131548by Zone 3 =150+ 3.5* 1980* (0.003*35000+1.5*1.2+1.7*3.6) = 127801

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2.3.2 Trip rate analysis

The trip rate analysis is simpler than regression models. Trip rate analysis is a combination of several models that are developed by determining the average trip production or trip attraction rates associated with the important trip generators within the zone. An example of these trip generators is the land use. Table 2.1 gives the trip rate analysis of a region based on land use.

Table 2.1 Floor space – Trip generation rates grouped by generalized land use categories in downtown Pittsburgh. (Ref. Fundamentals of Transportation Engineering by CS Papacostas. p 254)

Land use category Floor space Person trips Trips 1000 m2

Residential 254926 6574 25.8Commercial - Retail 625423 54833 87.7Commercial - Wholesale 241455 3162 13.1Commercial - Services 1254748 70014 55.8Manufacturing 129321 1335 10.32Transportation 129507 5630 43.47Public Buildings 276572 11746 42.47

Another trip rate analysis that can be developed for the same region is person trips per hectare of land use by zones.

Table 2.2 Person trips per hectare by land use and zone. (Ref. Fundamentals of Transportation Engineering by CS Papacostas p 255)

Personal trips per hectare

Zone Residential

Commercial Manufact

uring

Transportation

Publicbuildings

Publicopenspace

Average

Retail Wholesale

Services

Usedland

Allland

1 128 850 135 445 353 73 595 5 128 1002 108 423 90 258 183 25 265 3 75 503 93 563 115 505 83 35 375 10 80 554 75 670 73 385 73 25 245 5 65 435 55 463 60 365 55 13 90 5 43 206 45 485 48 338 53 18 48 3 35 137 38 380 40 328 35 15 10 3 28 8

Average 60 565 328 78 65 23 115 5 50 23

The average personal trips per hectare of land use can now be used to estimate the personal trips generated in any other zones.

Example: Four zones of an urban region have the following areas of land use. Calculate the trips produced and attracted by the zones using the trip rates given in Table 2.2.

Land use category Area (ha)Zone 1 Zone 2 Zone 3

Residential 2500 150 50Commercial Retail 375 900 150

Wholesale 450 500 200Services 150 250 200

Manufacturing 125 0 2500Transportation 80 250 350Public buildings 230 1500 125Public open space 300 350 100

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AnswerFirst calculate the trips generated by land use.

Land use category Area by land use(ha)Zone 1 Zone 2 Zone 3

Residential 150000 9000 3000Commercial Retail 211875 508500 84750

Wholesale 147600 164000 65600Services 11700 19500 15600

Manufacturing 8125 0 162500Transportation 1840 5750 8050Public buildings 26450 172500 14375Public open space 1500 1750 500Total 559090 881000 354375

Sort out trip productions and attractions by residential and non residential trip generation.

Type of trips Personal tripsZone 1 Zone 2 Zone 3

Production 150000 9000 3000Attractions 409090 872000 351375Total 559090 881000 354375

There are many ways in which the trip rates can be arranged. Tables 2.3 to 2.5 show hypothetical examples of different trip rates that can be developed to determine trips generated.

Table 2.3 Example of person-trip attraction rates.

Trip purpose

Trips per

house-hold

Trips per employee

University High school OtherNon

retail

Retail

CBD Shop center Other

Home based work - 1.70 1.70 1.70 1.70 - - -Home based shop - - 2.00 9.00 4.00 - - -Home based school - - - - - 0.90 1.60 1.20Home based other 0.70 0.60 1.10 4.00 2.30 - - -Non home based 0.30 0.40 1.00 4.60 2.30 - - -

Table 2.4 An example of traffic generation rates for residential areasResidential traffic

generatorMorning peak (trips/unit) Afternoon peak (trips/unit)

In Out Total In Out TotalSingle family residence 0.23 0.58 0.81 0.60 0.40 1.00Multifamily apartments 0.08 0.49 0.57 0.46 0.23 0.69

Table 2.5 An example of trip rates for various commercial activities

Commercial trip generatorTrips per 100 m2 GFA* at

peak hour of operationTrips per 100 m2 GFA* at afternoon peak street-hour

Drive in restaurants 276.6 116.3Sit down restaurants 37.7 26.9Food stores 15.1 12.9Neighbourhood shopping centres 16.1 15.1Automobile service stations 30.1 24.8Motels 0.9 0.6Office buildings 2.5 2.5Hospitals 1.1 0.8* GFA – Gross Floor Area of Buildings.

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2.3.3 Cross classification models

Cross classification is an extension of simple trip rate analysis models. They are zone based models but in trip generation they are used as disaggregate models. In residential trip generation households are further subdivided into categories or classes that highly correlate with trip making. Trip rates associated with each category of households are estimated by statistical methods. These rates which are assumed to remain stable over time are used to estimate trip generation in similar zones. An example of home based non work calibrated trip production rates are given in Table 2.6.

Table 2.6 Example of home based non work trip production rates for cross classification

Area type Vehicles available per household

Trips per household per dayNo of persons per household

1 2-3 4 5+

Urban high density

0 0.57 2.07 4.57 6.951 1.45 3.02 5.52 7.90

2+ 1.82 3.39 5.89 8.27Suburban medium density

0 0.97 2.54 5.04 7.421 1.92 3.49 5.99 8.37

2+ 2.29 3.86 6.36 8.74

Rural low density

0 0.54 1.94 4.44 96.821 1.32 2.89 5.39 7.77

2+ 1.69 3.26 5.76 8.14

Example: An urban zone contains 200 hectares of residential land, 50 hectares of commercial land and 10 hectares of park land. The zone’s predicted target year household composition is as follows,

Vehicles per household

Number of householdsNo of persons per household

1 2-3 4 5+0 100 200 150 201 300 500 210 50

2+ 150 100 60 00

Using the calibrated cross classification rates given in Table 2.6 estimate the total home based non work trips that the zone produces during a typical day of the target year.

AnswerThis is a high density zone (large residential area). The total trip productions Pi of the zone i estimated by summing up the contributions of each household type is given by,

where Nh is the number of households type h and Rh is the corresponding trip production rate. Thus, the trip productions by each house hold type is given by,

Vehicles per household

Number of trips generated by household type Total by household typeNo of persons per household

1 2-3 4 5+0 100 x 0.57 200 x 2.07 150 x 4.57 20 x 6.95 12961 300 x 1.45 500 x 3.02 210 x 5.52 50 x 7.90 3499

2+ 150 x 1.82 100 x 3.39 60 x 5.89 00 x 8.27 965Grand Total 5760

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2.4 Trip generation procedure

The trip generation procedure requires travel characteristics. There are two main sets of travel characteristics. They are, residential and non residential. They are obtained from zonal socioeconomic and land use projections.

Fig 2.3 shows a flow chart illustrating an example of a procedure for estimating the trip productions and trip attractions in a zone. Note that the analysis has also included special trip attraction sites. These could be airports, major shopping centres, hospitals and universities which have unique trip attraction characteristics.

Fig. 2.3 Example of procedure for prediction of trip attraction and trip production

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