Traffic & Transportation – II
Modal Split & Trip Distribution
Submitted to: Indu Priya Ma’am
M. A. Farmaan
IV – Semester
SPA - JNAFAU
Department of Urban & Regional Planning
Jawaharlal Nehru Architecture & Fine Arts University.
• The third stage in travel demand modeling is modal split.
• The trip matrix or O-D matrix obtained from the trip distribution is sliced into number of matrices representing each mode.
• First the significance and factors affecting mode choice problem will be discussed.
• Then a brief discussion on the classification of mode choice will be made.
• Two types of mode choice models will be discussed in detail. i.e. binary mode choice and multinomial mode choice.
• The chapter ends with some discussion on future topics in mode choice problem.
• The choice of transport mode is probably one of the most important classic models in transport planning.
• This is because of the key role played by public transport in policy making. Public transport modes make use of road space more
efficiently than private transport.
• Also they have more social benefits like if more people begin to use public transport , there will be less congestion on the roads and the
accidents will be less.
• Again in public transport, we can travel with low cost. In addition, the fuel is used more efficiently.
• Main characteristics of public transport is that they will have some particular schedule, frequency etc.
• On the other hand, private transport is highly flexible. It provides more comfortable and convenient travel.
• It has better accessibility also. The issue of mode choice, therefore, is probably the single most important element in transport planning
and policy making.
• It aspects the general efficiency with which we can travel in urban areas. It is important then to develop and use models which are
sensitive to those travel attributes that influence individual choices of mode.
Factors influencing the choice of mode:
The factors may be listed under three groups:
1. Characteristics of the trip maker:
The following features are found to be important:
(a) car availability and/or ownership;
(b) possession of a driving license;
(c) household structure (young couple, couple with children, retired people etc.);
(e) decisions made elsewhere, for example the need to use a car at work, take children to school, etc;
(f) residential density.
2. Characteristics of the journey:
Mode choice is strongly influenced by:
(a) The trip purpose; for example, the journey to work is normally easier to undertake by public transport than other journeys because of its
regularity and the adjustment possible in the long run;
(b) Time of the day when the journey is undertaken.
(c) Late trips are more difficult to accommodate by public transport.
3. Characteristics of the transport facility:
There are two types of factors.
One is quantitative and the other is qualitative.
Quantitative factors are:
(a) relative travel time: in-vehicle, waiting and walking times by each mode;
(b) relative monetary costs (fares, fuel and direct costs);
(c) availability and cost of parking
Qualitative factors which are less easy to measure are:
(a) comfort and convenience
(b) reliability and regularity
(c) protection, security
A good mode choice should include the most important of these factors.
Types of modal split models:
A. Trip-end modal split model: Traditionally, the objective of transportation planning was to forecast the growth in
demand for car trips so that investment could be planned to meet the demand.
• When personal characteristics were thought to be the most important determinants of mode choice, attempts
were made to apply modal-split models immediately after trip generation.
• Such a model is called trip-end modal split model.
• In this way different characteristics of the person could be preserved and used to estimate modal split.
• The modal split models of this time related the choice of mode only to features like income, residential density
and car ownership.
• The advantage is that these models could be very accurate in the short run, if public transport is available and
there is little congestion.
• Limitation is that they are insensitive to policy decisions example: Improving public transport, restricting parking
etc. would have no effect on modal split according to these trip-end models.
B. Trip-interchange modal split model:
• This is the post-distribution model; that is modal split is applied after the distribution stage.
• This has the advantage that it is possible to include the characteristics of the journey and that of the alternative modes
available to undertake them.
• It is also possible to include policy decisions.
• This is beneficial for long term modeling.
C. Aggregate and disaggregate model:
• Mode choice could be aggregate if they are based on zonal and inter-zonal information.
• They can be called disaggregate if they are based on household or individual data.
•The decision to travel for a given purpose is called trip generation.
•These generated trips from each zone is then distributed to all other zones based on the choice of destination.
•This is called trip distribution which forms the second stage of travel demand modeling.
•There are a number of methods to distribute trips among destinations; and two such methods are growth factor model and gravity model.
•Growth factor model is a method which respond only to relative growth rates at origins and destinations and this is suitable for short term trend
•In gravity model, we start from assumptions about trip making behavior and the way it is influenced by external factors.
•An important aspect of the use of gravity models is their calibration, that is the task of fixing their parameters so that the base year travel pattern
is well represented by the model.
•The trip pattern in a study area can be represented by means of a trip matrix or origin-destination (O-D)matrix.
•This is a two dimensional array of cells where rows and columns represent each of the zones in the study area.
•The notation of the trip matrix is given.
•The cells of each row i contain the trips originating in that zone which have as destinations the zones in the corresponding columns. Tij is the
number of trips between origin i and destination j.
•Oi is the total number of trips between originating in zone i and Dj is the total number of trips attracted to zone j. The sum of the trips in a row
should be equal to the total number of trips emanating from that zone.
•The sum of the trips in a column is the number of trips attracted to that zone. These two constraints can be represented as: OijTij = OiiTij = Dj If
reliable information is available to estimate both Oi and Dj, the model is said to be doubly constrained.
•In some cases, there will be information about only one of these constraints, the model is called singly constrained.
GROWTH FACTOR METHODS
THE GRAVITY MODEL
• A model that is usually used for trip distribution is that of the gravity function, an application of Newton’s fundamental law of
attraction (Oppenheim, 1980; Field and MacGregor, 1987; Ortuzar and Willumsen, 2001).
• Much of the discussion below is also repeated in cha pter 9 on journey t o crime since there is a common theoretical basis.
• In the original Newtonian formulation, the attraction, F, between two bodies of respective masses M1 and M2, separated by a
distance D, will be equal to
M1, M2 F = g ----------------- (14.2)D2
where g is a constant or scaling factor which ensures that the equation is
balanced in terms of the measurement units (Oppenheim, 1980).
• As we all know, of course, g is the gravitational constant in the Newtonian formulation. The numerator of the function is the
attraction term (or, alternatively, the attraction of M2 for M1) while the denominator of the equation, d2, indicates that the
attraction between the two bodies falls off as a function of their squared distance. It is an impedance (or resistance) term.
UNIFORM GROWTH FACTOR
• If the only information available is about a general growth rate for the whole of the study area, then we can only assume that it
will apply to each cell in the matrix, that is a uniform growth rate.
• The equation can be written as: Tij = f tij (8.2) where f is the uniform growth factor tij is the previous total number of trips, Tij is
the expanded total number of trips.
• Advantages are that they are simple to understand, and they are useful for short-term planning.
• Limitation is that the same growth factor is assumed for all zones as well as attractions.
Source: Traffic & Transportation Planning – L. R. Kadiyali.
Ltexhtml/nptel_ceTEI_L09.pdf - Modal Split.
/nptel_ceTEI_L08.pdf - Trip Distribution.