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TRIP GENERATION ELECTIVE TRAFFIC & TRANSPORTATION
ANKIT KUMAR 2009EAL05 B.ARCH
FRAMEWORK FOR TRIP GENERATION • Fundamentals of Transportation • Trip generation • Activities • observations
Fundamentals of Transportation Trip generation activity, such as one based on the concept of economic base analysis, provides aggregate measures of population and activity growth. Land use forecasting distributes forecast changes in activities in a disaggregate-spatial manner among zones. The next step in the transportation planning process addresses the question of the frequency of origins and destinations of trips in each zone: for short, trip generation. The study of trip generation attempts to identify and quantify the trip ends related to various urban activity :– No. description other trip characteristics such as direction, length or duration – Relating trip ends to land use and socioeconomic characteristics through Regression analysis. – Relating trip ends to land area, floor area or other use measures such as Employment through trip rates. – Classifying trip ends by characteristics of the analysis unit generally referred to as cross -classification analysis.
Trip generation IT is the first step in the conventional four-step transportation forecasting process (followed by Destination Choice, Mode Choice, and Route Choice), widely used for forecasting travel demands. It predicts the number of trips originating in or destined for a particular traffic analysis zone. Every trip has two ends, and we need to know where both of them are. The first part is determining how many trips originate in a zone and the second part is how many trips are destined for a zone. Because land use can be divided into two broad category (residential and non-residential) . For the residential side of things, trip generation is thought of as a function of the social and economic attributes of households (households and housing units are very similar measures, but sometimes housing units have no households, and sometimes they contain multiple households, clearly housing units are easier to measure, it is important to be clear which assumption you are using).
At the level of the traffic analysis zone, the language is that of land uses " producing" or attracting trips, where by assumption trips are "produced" by households and "attracted" to non-households. Production and attractions differ from origins and destinations. Trips are produced by households even when they are returning home (that is, when the household is a destination). Again it is important to be clear what assumptions you are using.
People engage in activities, these activities are the "purpose" of the trip. Major activities are home, work, shop, school, eating out, socializing, recreating, and serving passengers (picking up and dropping off). There are numerous other activities that people engage on a less than daily or even weekly basis, such as going to the doctor, banking, etc. Often less frequent categories are dropped and lumped into the catchall "Other". Every trip has two ends, an origin and a destination. Trips are categorized by purposes, the activity undertaken at a destination location.
• Men and women behave differently on average, splitting responsibilities within households, and engaging in different activities, • Most trips are not work trips, though work trips are important because of their peaked nature (and because they tend to be longer in both distance and travel time), • The vast majority of trips are not people going to (or from) work. People engage in activities in sequence, and may chain their trips. In the Figure below, the tripmaker is traveling from home to work to shop to eating out and then returning home.
Types of trip • • • • • •
Journey, home based trip, non home based trip, trip production, trip attraction and trip generation.
Journey is an out way movement from a point of origin to a point of destination, whereas the word \trip" denotes an outward and return journey. If either origin or destination of a trip is the home of the trip maker then such trips are called home based trips and the rest of the trips are called non home based trips. Trip production is defined as all the trips of home based or as the origin of the non home based trips . Trips can be classified by trip purpose, trip time of the day, and by person type. Trip generation models are found to be accurate if separate models are used based on trip purpose. The trips can be classified based on the purpose of the journey as trips for work, trips for education, trips for shopping, trips for
recreation and other trips. Among these the work and education trips are often referred as mandatory trips and the rest as discretionary trips. All the above trips are normally home based trips and constitute about 80 to 85 percent of trips. The rest of the trips namely non home based trips, being a small proportion are not normally treated separately. The second way of classification is based on the time of the day when the trips are made. The broad classification is into peak trips and o_ peak trips. The third way of classification is based on the type of the individual who makes the trips. This is important since the travel behavior is highly influenced by the socio-economic attribute of the traveler and are normally categorized based on the income level, vehicle ownership and house hold size.
Factors affecting trip generation
The main factors affecting personal trip production include income, vehicle ownership, house hold structure and family size. In addition factors like value of land, residential density and accessibility are also considered for modeling at zonal levels. The personal trip attraction, on the other hand, is influenced by factors such as roofed space available for industrial, commercial and other services. At the zonal level zonal employment and accessibility are also used. In trip generation modeling in addition to personal trips, freight trips are also of interest. Although the latter comprises about 20 percent of trips, their contribution to the congestion is significant. Freight trips are influenced by number of employees, number of sales and area of commercial firms.
Three trip purposes are: - Many other types are possible 1) Home Based Work (HBW), only trips from home to work or visa versa. Most urban area peak hour trips are this type. 2) Home Based Other (HBO), any other kind of trip with one end at the home. 3) Non Home Based (NHB), any trip that doesn't either come from or go to a home. 4) Home to work (H2W) 5) Work to home (W2H) 6) Work to other (W2O) 7) Other to work (O2W) 8) Home to other (H2O) 9) Other to home (O2H)
Purposes of Regression /Correlation Analyses 1) Provides estimates of values of dependent variable from values of independent variable – Provides estimates of mean value of Y for each value of X 2) Obtain measures of error involved in using the regression line as a basis of Estimation. 3) Measure degree of association between two variables / strength of relationship
Growth factor modeling Growth factor modes tries to predict the number of trips produced or attracted by a house hold or zone as a linear function of explanatory variables. The models have the following basic equation: Ti = fi x ti Where (Ti) is the number of future trips in the zone and (ti) is the number of current trips in that zone and fi is a growth factor. The growth factor (fi) depends on the explanatory variable such as population (P) of the zone average house hold income (I) , average vehicle ownership (V). The simplest form of fi is represented as follows where the subscript " d" denotes the design year and the subscript "c" denotes the current year P i d x I i d x Vi d Fi= ________________ Pic x Iic x Vic
Regression methods The general form of a trip generation model is Ti = f(X1, X2, X3, …… Xi, ……. Xk) Where Xi's are prediction factor or explanatory variable. The most common form of trip generation model is a linear function of the form Ti = a0 + a1x1 + a2x2 +…. aixi…….+ akxk Where (ai)'s are the coefficient of the regression equation and can be obtained by doing regression analysis. The above equations are called multiple linear regression equation, and the solutions are tedious to obtain manually. However for the purpose of illustration, an example with one variable is given. Trip generation forms the first step of four-stage travel modeling. It gives an idea about the total number of trips generated to and attracted from different zones in the study area. Growth factor modeling and regression methods can be used to predict the trips.