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Trip Distribution Modeling Part III

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Trip Distribution Modeling. Part III. CE 573 Transportation Planning ... Step 1: Set bj to 1.0, determine initial trip matrix, and solve ... with new ai ... – PowerPoint PPT presentation

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Title: Trip Distribution Modeling Part III


1
Trip Distribution Modeling Part III
  • CE 573 Transportation Planning
  • Lecture 14

2
Objectives
  • Growth factoring
  • Types of constraints
  • Methods

3
Growth Factoring
  • Concept
  • XFUTURE XNOW(growth factor)
  • Applications
  • Beyond regional scope
  • Gravity model inadequate
  • Too difficult to forecast independent variables

4
Definitions and Constraints
  • The trip matrix total T
  • Tij is the number of trips going from origin i to
    destination j.
  • TLDk is the number of trips in cost-bin k
  • Typical trip matrix constraints

5
Growth Factor Methods
  • t initial OD matrix
  • Uniform growth factor?Tij ttij.
  • Singly constrained growth-factor methods

OR
6
Growth Factor Methods (cont.)
  • Doubly constrained growth factors?have growth
    factors for origins and destinations (), where
  • instead of ai and bj being the growth factors for
    origin i and destination j, they are adjustments
    made to each O-D pair volume in order to achieve
    the target values Oi and Dj required by the
    growth factors for the origins and destinations

7
Growth Factor Methods (cont.)doubly constrained
  • BI-PROPORTIONAL ALGORITHM
  • Step 1 Set bj to 1.0, determine initial trip
    matrix, and solve for ai that meet origin
    constraints, given the latest bj values.
  • Recalculate Tij with new ai values
  • Step 2 Solve for bj that meet the destinations
    constraints given the latest ai values and the
    previous bj values.
  • Recalculate Tij with new bj values and the latest
    ai values.
  • m-1 indicates previous iteration

8
Growth Factor Methods (cont.)doubly constrained
  • Step 3 Keeping the bj values fixed solve for ai
    that satisfy origin constraints given the ai from
    the last iteration (iteration m-1).
  • m-1 indicates previous iteration
  • Repeat steps 2 and 3 until changes in ai and bj
    are sufficiently small.
  • Note This algorithm assumes that both sets of
    constraints can be satisfied simultaneously. In
    other words, the following must be true

9
Advantages and limitations of growth-factor
methods
  • Advantages
  • simple
  • Disadvantages
  • requires an initial O-D matrix
  • no consideration given to changes in transport
    costs
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