Cube Voyagers Public Transport Module

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Cube VoyagersPublic TransportModule
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PTs Design Overview

• Provides a multi-user-class, multi-routing
  transit algorithm which
• Represents all the complexities of the public
  transport system
• Uses efficient techniques to determine what
  different traveler's would consider to be
  reasonable public transport routes.
• Allocates the demand between the various routes
  in a way similar to how travelers actually chose
  their routes

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Represents Complexity of PT Systems

• The route, where it stops (boarding and
  alighting both, only boarding, only alighting),
  and its variations (sub-routes) by period of the
  day. Details such as boarding delays at selected
  stops..
• The type of vehicle providing the service (bus,
  light rail, heavy rail, ferryetc.) and its
  capacity (seated and crush). (capacity restraint
  is provided in PT)
• Information about multiple PT operators and their
  operating/fare policies
• Full representation of circular routes
• Uses function of roadway speed, set travel times
  via time points, used fixed time.

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PT Methodology

• Compiles Data and Simplifies Network (Produces
  NET file)
• Enumerates Acceptable Discrete Routes for every
  I-J (RTE file)
• Finds least cost route
• Enumerates all other routes within defined limits
• Evaluates Routes and Performs Analysis
• Decisions on access and assignment to individual
  lines through a series of logit choice models.
• Route evaluation through a hierarchical logit
  choice model.

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PT Steps

• Enumeration finds a traveler's reasonable public
  transport routes from origin to destination
• Identifies full discrete routes
• The route should move progressively from the
  origin to the destination
• Travelers tend to select journeys that are
  simpler that are direct or involve few
  interchanges
• Travelers are unwilling to walk very long
  distances
• These principals are used to constrain the
  potentially huge computational task of
  identifying all reasonable routes
• The process can be considered analogous to a
  traveler using a map to reject routes which are
  very long relative to more direct alternatives
• Creates a dataset of the reasonable routes
  between each origin and destination by user class

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PT Steps

• Evaluation qualitatively judges the routes
  calculated in the route enumeration stage of PT
• The elements that can be used in this process
• Limit on the number of transfers
• The difference (actual percentage) difference
  between the minimum cost route and the evaluated
  route
• Limit on non-transit cost (walk/drive access)
• Limit on waiting and transfer times
• Limit on In-vehicle costs
• Specified by user class or market segment
• Provides attractive and reasonable routes along
  with their probability of being used and the
  costs of each of the routes.
• Calculates the probability of using each path
  using choice models at each decision point

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Route Choice Probability
Note you can visualize route choice percent
allocations to calibrate model parameters to
known or expected routing patterns (i.e. not
only does the skim make sense but does the
multi-path routing make sense)
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Tools to Build and Maintain a PT Model

• Networks
• PT System Data
• Access Links (Automatic and/or Manual Coding)
• Fare Systems
• Multiple User Classes
• Transfer Rules
• Wait curves
• Crowding
• Skims (Cost Time)

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Building Maintaining PT Networks

• Ability to create and edit PT Lines in Cube
  Graphics
• Ability to create and edit PT lines in Cube GIS
  with PT transit data stored in geodatabase
• Ability to open multiple PT line files at once
• AUTOMATIC UPDATES to PT lines to confirm to
  Highway Network edits
• Tools to copy and reverse PT lines
• Transit Line Manager for easier management

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Transit Line Manager
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PT System Data- Vehicle Characteristics

• Public Transport Fleets are grouped by
• Mode
• Operator
• Vehicle Type
• Vehicles are given perceived time factors to
  designate desirableness.
• Vehicles are given seated and crush capacities.
• Capacity curves are defined to establish
  penalties based on the volume to capacity ratio.
• Vehicle travel-times may be obtained from
• Factoring congested roadway speeds
• Speed variables in the network
• Route schedule time-tables

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PT System Data Manager
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Multiple User-Classes

• Each user-class may have unique factors which
  determine
• Which routes are reasonable
• How much walking?
• How many transfers?
• What are the access characteristics?
• What is the maximum cost?
• What is the maximum travel time?
• Which routes are desirable
• What is the perceived time for walking,
  transferring, waiting, riding (by mode)?
• Are there rebates or special fare systems?
• What is the sensitivity to crowding/capacity
  restraint?
• What is the value of time?
• What is the willingness to pay?

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User Class-Specific Factors

• MUMEXTRACOST (search beyond minimum cost)
• MUSTUSEMODE (a single or group)
• REBESTPATHCOST (alternate methods)
• RECOSTMAX (max cost considered)
• REWAITMAX (caps wait times)
• REWAITMIN (insures minimum wait time)
• RUNFACTOR by mode
• SERVICEMODEL (used in evaluation)
• SPREADCONST (multipath enumeration only)
• SPREADFACT (multipath enumeration only)
• SPREADFUNC (multipath enumeration only)
• VALUEOFTIME by mode
• WAITFACTOR by node (safety, amenities, etc)
• XFERCONST (mode to mode penalties)
• XFERFACTOR (mode to mode penalties)
• XFERPEN (can be negative)
• XWAITCURVE by node

• The FACTORS keywords are
• ALPHA (relative weight of walk to rest of
  journey)
• AONMAXFERS (controls route search with MAXFERS)
• BESTPATHONLY
• BRDPEN by mode
• CHOICECUT (multipath only)
• DELACCESSMODE (deletes access modes from paths)
• DELEGRESSMODE (deletes egress modes from paths)
• DELMODE (any modes out of path building)
• EXTRAXFERS1 (controls route search with MAXFERS)
• EXTRAXFERS2 (controls route search with MAXFERS)
• FARESYSTEM (obvious)
• FREQBYMODE (headways across modes or not)
• IWAITCURVE by node
• LAMBDAA (multipath only)
• LAMBDAW (multipath only)
• MAXFERS (maximum transfer cutoff)

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Fare System Representation

• All sorts of complex fare systems can be modeled
  by user class
• FREE No cost incurred
• FLAT One fixed cost per use
• DISTANCE Possible boarding cost unit cost per
  distance or cost lookup table
• FROMTO Fare zone matrix based on the start/end
  zones
• COUNT Counts number of fare zones crossed, sum
  number of zones crossed
• ACCUMULATE Each fare zone has a fare and when
  crossed adds to cost
• HILOW Fare result of the highest and lowest fare
  zone number crossed
• Simple TAZ-TAZ fare matrices

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Access Link Procedures

• Access and Transfer links can be input via
• Automatic generation through analysis of the
  network
• External file
• Network attribute
• Automatic generation of non-transit links
• Walk access to the stops, time and distance may
  be calculated along the network or using straight
  line connections.
• Automobile access to the stops are calculated
  along the network for kiss-and-ride or
  park-and-ride.
• Code park-and-ride lots and specify contributing
  zones or set maximum travel times or distances.
• Wait curves may be specified to calculate wait
  time for boarding and transferring. These may be
  unique by location, mode, or user-class
• Automated process limits increased to 999
  access/egress/transfer links can be generated for
  any give node for each mode

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Wait Curve Specification
Note you can visualize and implement up to 255
shapes of wait curves that can be applied by node
and further modified by waitfactor by mode
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Crowding Model

• Crowd modeling is an iterative process enabling
  the capacity of a Public Transport System to
  influence the travel times in the system and thus
  the routes found and their probability of use, as
  calculated during route evaluation.
• Two types of crowding model may be used
• Link travel time adjustment
• Wait time adjustment

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Ways to Implement the Crowding Model

• Link travel time adjustment
• The link travel time adjustment models passenger
  perceptions that travel time is more onerous when
  they have to stand (rather than sit), or when the
  vehicle is crowded. The adjustment is represented
  by a crowding factor, which is multiplied by
  in-vehicle time to give the perceived value of
  crowded in-vehicle time.
• Wait time adjustment
• In the context of a transit leg from a boarding
  point to an alighting point with several lines
  operating, demand (without crowding) is allocated
  using the service frequency model (SFM), or
  service frequency cost model (SFCM). The wait
  time adjustment redistributes the initial SFM or
  SFCM loadings whenever any line does not have the
  available capacity to take its allocated demand.
  This excess demand is reallocated to other lines
  which have spare unused capacity, and incurs
  additional wait time.
• The additional wait time (due to not being able
  to take the first service) may make this route
  less attractive, and so cause diversion of demand
  to other enumerated routes for the
  origin-destination pair.

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Skimming the PT Network (SKIMIJ)

• Available Skims
• COMPCOST Skims Composite Costs
• ValOfChoice Skims Value of Choice
• IWAITA/P Skims Initial Wait Times
  Actual/Perceived
• XWAITA/P Skims Transfer Wait Times
  Actual/Perceived
• CWDWAITA/P Skims Crowding Wait Times
  Actual/Perceived
• TIMEA/P(Mode) Skims Travel Time Actual/Perceived
• CWDCOSTP Skims Crowding Link Travel Times
  Perceived
• BRDPEN(Mode) Skims Boarding Penalty Perceived
• XFERPENA/P(Mode) Skims Transfer Penalty
  Actual/Perceived
• DIST(Mode) Skims Distance
• BRDINGS(Mode) Skims Number of Boardings
• BESTJRNY Skims Best Journey Times
• FAREA/P(Mode) Skims Actual/Perceived Fares in
  Monetary units
• EXCESSDEMAND Skims Excess Demand in Crowding
  Model
• EXCESSPROP Skims Excess Proportion in Crowding
  Model

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Report and Visualize PT Results Inputs

• Reports
• Graphics
• Record Processing

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PT Assignment Line Report
Note you can get summaries for totals or by
user-class for up to 10 user classes at a time
sorted by mode, operator or line name
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PT Assignment Graphics
On, Off and Through
Line Profile
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Advanced Analysis Techniques

• Select Link Analysis
• OD Matrix Estimation

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Select Link Analysis

• Allows the user to generate matrices of trips
  which satisfy a certain condition.
• Optionally the selected trips may be assigned to
  the network for further analysis and
  visualization.
• Selections may be any combination or exclusion
  of
• Traversed Links and/or Nodes
• Lines
• Modes
• Operators

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Examples of Select Link Queries

• The general form of the select link function is
• SELECTLINK (expression)
• MW1 SELECTLINK(L1023-1027)
• MW3 SELECTLINK(L101-102, 104-105, 107-109)
• MW1 SELECTLINK(LINERED1)
• MW2 SELECTLINK(LINEA, B)
• MW5 SELECTLINK(MODE3,5,7-9)
• MW7 SELECTLINK(OPERATOR3)
• MW2 SELECTLINK((L101-102 LINERED)
  (L201-202 LINEBLACK))
• For conditions using node selection (that is, N
  conditions) the TYPE keyword can take the
  following values
• THRU, to consider transit legs passing through
  the node
• BOARD to consider transit legs boarded at the
  node
• ALIGHT to consider transit legs alighted from at
  the node
• NTTHRU to consider nontransit legs passing
  through the node
• e.g. MW2 SELECTLINK((N123 TYPEALIGHT)
  (N123 TYPEBOARD))

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Demand Analysis

• The select process returns the demand for an I-J
  pair which satisfies a selection criterion.
• The proportion of demand meeting the criterion
  may be obtained by including the keyword
  PROBABILITYT in the expression. In a similar
  manner percentages may be obtained by using the
  keyword setting PERCENTT.
• e.g. MW3 SELECTLINK(LINETRAM1, PERCENTT)
  returns percentage values for each I-J pair which
  use the line TRAM1.
• The select link process may load the portion of
  total demand meeting a select link criterion,
  rather than loading the entire demand as
  specified by the PARAMETER TRIPSIJ.
• This is invoked by including the keyword and
  setting LOADT in the select link expression
• e.g. MW2 SELECTLINK(L303-307, LOADT)

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OD Matrix Estimation

• Cube Analyst can perform matrix estimation on the
  in conjunction with the PT Module.
• The process takes as Input
• Initial Matrix
• Partial Matrices
• Trip Ends
• Link Counts
• Line Counts
• Transit Line Ons/Offs/Throughs
• All Input observations are given a level of
  confidence. This allows data from different
  sources to be properly considered and weighted.