1. The Four-Step Travel Model
GEOG 111 & 211A – Fall 2006

2. Outline Background Role of Simulation General Process
Example of Most Popular Simulation Model
Examples of Other Ideas
Summary

3. Needs Identify Projects for the Region
Use Formal & Accepted Technique(s) to Estimate Project Impacts
Simulate the Region for the Next 20 Years
Create Scenarios for BEFORE and AFTER a Project or Group of Projects

4. How Do we use Simulation Models?
Create a Comprehensive Plan of how we want an area/region to be in the future
Propose projects designed to achieve the goals of the Comprehensive Plan
Test Scenarios implementing different projects and forecast their effects
Determine what projects should be continued to next stage
Present recommendations to decision makers

5. Project Types New Highways (e.g., bypass-ring roads)
New Management Activities (e.g., park & ride, signal systems )
New Land Uses (e.g., a new industry, a new residential neighborhood)
New Technologies??????? (maybe in management)

6. The Context
Urban Transportation Planning System (UTPS) & Urban Transportation Modeling System
TEA 21 made it also A Statewide Transportation Planning System
Technology should be added (see Pennplan)
Associate quantitative estimates with performance measures as in the monitoring part (see PennPlan)
Four-step scheme followed today in many MPOs
Four-step travel model is limited but popular!

7. technical development
Goals and
objectives
Land use
Trip generation
Trip distribution
Modal split
Traffic assign.
Calibrate models
Develop alternatives
Apply models
Land use
Trip generation
Trip distribution
Mode choice
Traffic assign.
Plan testing, evaluation
and selection
Analysis of future
alternative systems
Population
Land use
Economic activity
Transportation system
Travel volumes
Terminal and transfer
facilities status & use
Financial resources
Community values
Inventories and
data collection D A T
PennDOT
MPOs
TMAs
LDDs
Local gov’ts
Citizen participation
Transportation
organizations
Population
Land use
Economic
Traffic
Revenues
Areawide
forecast
Policy and
technical development
Plan implementation
Surveillance
Reappraisal
Procedural development
Service
Annual report
Continuing elements
Develop immediate
action plan
= Part of the Sequential
Demand Forecasting Process
Typical Process in Long Range Planning

8. The Sequential Forecasting Process & the Urban Transportation Planning System (UTPS) [adapted from Papacostas & Prevedouros, 1993]
Land use and
socioeconomic
projections
Trip
Generation 4 - S T E P
Trip
Distribution
Transportation
system
specification
Mode
Choice
Network
Assignment
Direct (user)
Impacts

9. Four step in large MPOs Inventory of facilities
Opportunity to think strategically
Show the impact of projects on air quality
Provide report of emissions inventory
Tool for policy assessment
PSRC example follows!

11. What Other Steps Are Required?
Forecast future development (business, roadways, and housing)
Model the area’s traffic network
Estimate model of the area’s traffic network in the future
Make changes to network characteristics in the future model
Compare network performance under different scenarios of project development

12. UTPS Outline Review the Data Inventory for a Region
Review one Procedure to Predict Future Volumes on a Highway
Summarize the Method Known as UTPS
Questions

13. UTPS 4-step Travel Model
Trip Generation
Trip Distribution
Modal Split
Traffic Assignment

14. Data (Inventory) Area of study definition & traffic analysis zones
Area of study description (highways, facilities, zoning, rules/regulations)
Who are the residents? (age, gender, education, employment, income of residents)
Where do people leave?
Where do people work, shop, etc?
Highway characteristics
Other information (plans for rezoning)

15. Travel Model Urban Travel Model (‘60s) General planning & programming
Also known as the Four - Step Process
A methodology to model traffic on a network
General planning & programming
Land use forecasting (where will residences and stores be?)
Four Steps:
Trip Generation Estimate Person Trips for each TAZ
Trip Distribution Distribute Person Trips from TAZ to TAZ
Mode Choice Convert Person Trips to Vehicle Trips
Traffic Assignment Assign Vehicles to the Network

16. Key Concepts of 4-step Block Block Group Tract i.e., a city block
TAZ: Traffic Analysis Zone
TAZ= a common sense subdivision of the study area
TAZs are used in trip generation and trip distribution
TAZs may be any shape or size, but US Census Blocks, Block Groups, and Tracts are often used (class: WHY?)
Block
Block Group
Tract
i.e., a
city block

17. 8-Zone Study Area with Traffic Analysis Zones (TAZs)2 1 3 z 5 4 6 8 7
Legend: x
= TAZ designations
study area boundary
z = all zones outside study area
TAZ boundaries

18. Key Concepts of UTPS Centroid Discussion
Every TAZ (Gate and Internal) has a centroid, usually placed roughly at the geographic center of the TAZ
All trips to or from a TAZ are assumed to start or end at the centroid
Discussion
Why do we use TAZs and centroids to model trips?

19. Key Concepts of UTPS Gate TAZs Network Gate TAZ (Study Area)
TAZs placed outside the Study Area where major roads cross the boundaries of the study area
Used to model External Trips (i.e., trips with an origin or destination) Note: Do we care when OD is outside the study area?
Gate TAZs represent all areas outside of the study area
Network
Gate TAZ
(Study Area)

20. Example: Computer schematic representation
Network & Links Numbered 22 23 20 21 18 19 16 17 13 14 15 8 9 10 11 12 5 6 7 3 4 2 1

21. Network and Nodes Numbered23 22 19 20 21 14 15 16 17 18 8 9 10 11 12 13 3 4 5 6 7 2 1

23. Centroid
Gate TAZ

26. Land Use/Economic Analysis
Considers general trends
Allocates population to geographic subdivisions
Assigns land uses
Each TAZ contains “observed” numbers for today’s analysis and predicted numbers for forecasting

27. OUTPUT = a map with TAZ’s and their characteristics – households, businesses, employers

28. Trip Generation Process
Collect Data, usually by Surveys and Census
Sociodemographic Data and Travel Behavior Data
Create a Trip Generation Model (e.g., regression)
Estimate the number of Productions and Attractions for each TAZ, by Trip Purpose
Balance Productions and Attractions for each Trip Purpose
Total number of Productions and Attractions must be equal for each Trip Purpose
We will discuss balancing later

29. Trip Generation Models
Regression Models
Explanatory Variables are used to predict trip generation rates, usually by Multiple Regression
Trip Rate Analysis
Average trip generation rates are associated with different trip generators or land uses
Cross - Classification / Category Analysis
Average trip generation rates are associated with different trip generators or land uses as a function of generator or land use attributes
Models may be TAZ, Household, or Person - Based

30. ITE Trip Generation Manual
Trip Rate Analysis Model
Univariate regression for trip generation
Primarily for Businesses
Explanatory variables are usually number of employees or square footage
Models developed using data from national averages and numerous studies from around the US

32. Possible geographic detail in trip generation with GIS & business data

33. Typical output from trip generation

34. Trip Distribution
Convert Production and Attraction Tables into Origin - Destination (O - D) Matrices
Destinations 1 2 3 4 5 6
Sum
Origins
Sum
T11 T12 T13 T14 T15 T16 O1
T21 T22 T23 T24 T25 T26 O2
T31 T32 T33 T34 T35 T36 O3
T41 T42 T43 T44 T45 T46 O4
T51 T52 T53 T54 T55 T56 O5
T61 T62 T63 T64 T65 T66 O6
D1 D2 D3 D4 D5 D6
TAZ P 15 13 26 18 8 93 A 22 6 5 52 2 1 3 4
Sum

35. Trip Distribution, Methodology
General Equation:
Tij = Ti P(Tj)
Tij = calculated trips from zone i to zone j
Ti = total trips originating at zone i
P(Tj) = probability measure that trips will be attracted to zone j
Constraints:
Singly Constrained
Sumi Tij = Dj OR Sumj Tij = Oi
Doubly Constrained
Sumi Tij = Dj AND Sumj Tij = Oi

36. Trip Distribution Models Example
TiAj / Cij
Gravity Model Tij is:
Tij = trips from zone i to zone j =
Ti = total trips originating at zone i
Aj = attraction factor at j
Ax = attraction factor at any zone x
Cij = travel friction from i to j expressed as a generalized cost function
Cix = travel friction from i to any zone x expressed as a generalized cost function
a = friction exponent or restraining influence
Sum (Ax / Cix) a

37. Gravity Model Process Create Shortest Path Matrix
How: Minimize Link Cost among Centroids
Estimate Friction Factor Parameters
How: Function of Trip Length Characteristics by Trip Purpose
Calculate Friction Factor Matrix
Convert Productions and Attractions to Origins and Destinations
Calculate Origin - Destination Matrix
Enforce Constraints on O - D Matrix

38. Shortest Path Matrix
Matrix of Minimum Generalized Cost from any Zone i to any Zone j
Distance, Time, Monetary Cost, Waiting Time, Transfer Time, etc.. may be used in Generalized Cost
Time or Distance Often Used
Matrix Not Necessarily
Symmetric (Effect of
One - Way Streets)
TAZ ID
TAZ ID
C11 C12 C13 C14 C15 C16
C21 C22 C23 C24 C25 C26
C31 C32 C33 C34 C35 C36
C41 C42 C43 C44 C45 C46
C51 C52 C53 C54 C55 C56
C61 C62 C63 C64 C65 C66 1 2 3 4 5 6

39. O - D Matrix Calculation
Calculate Initial Matrix By Gravity Equation, by Trip Purpose
Each Cell has a Different Friction, Found in the Corresponding Cell of the Friction Factor Matrix
Enforce Constraints in Iterative Process
Sum of Trips in Row i Must Equal Origins of TAZ i
Sum of Trips in Column j Must Equal Destinations of TAZ j
Iterate Until No Adjustments Required

40. O - D Matrix Example: Destinations 1 2 3 4 5 6 Sum Origins
T11 T12 T13 T14 T15 T16 O1
T21 T22 T23 T24 T25 T26 O2
T31 T32 T33 T34 T35 T36 O3
T41 T42 T43 T44 T45 T46 O4
T51 T52 T53 T54 T55 T56 O5
T61 T62 T63 T64 T65 T66 O6
D1 D2 D3 D4 D5 D6

41. Final O - D Matrix
Combine (Add) O - D Matrices for Various Trip Purposes
Scale Matrix for Peak Hour
Scale by Percent of Daily Trips Made in the Peak Hour
0.1 Often Used
Scale Matrix for Vehicle Trips
Scale by Inverse of Ridership Ratio to Convert Person Trips to Vehicle Trips
0.95 to 1 Often Used
Note: Other Mode Split Process / Models using Discrete Choice may be More Accurate

42. OUTPUT = the trip interchange matrix and the shortest path trees

43. Modal Split Use a model to convert trips into vehicle trips
Usually public transportation versus private car
Nomographs, Regression methods, Microeconomic Regression methods
Stated Preference (conjoint measurement) techniques for hypothetical options
Traveler objective and subjective constraints in selecting a mode

44. OUTPUT = a trip interchange matrix for each mode: car, public transportation, could also be pedestrian but not usual

45. Traffic Assignment Fourth Step in UTPS Modeling Inputs: Outputs:
Peak Hour, Passenger Vehicle Origin - Destination (O - D) Matrix
Network
Travel Time, Capacity, Direction
Outputs:
Peak Hour Volumes, Estimated Travel Times, and Volume to Capacity Ratios

46. Roadway Performance Functions
Traffic Flow and Travel Time
Linear Relationship
Non-Linear Relationship
Route Travel Time
Capacity
Free-Flow
Travel Time
Traffic Flow
Traffic Flow

47. Assignment Methods All or Nothing System Equilibrium
All traffic from zone i to zone j uses the (initially) minimal travel time path
Roadway performance not used
System Equilibrium
Assignment is performed such that total system travel time is minimized (UPS, Fed-EX).

48. Assignment Methods User Equilibrium Stochastic User Equilibrium
Travel time from zone i to zone j cannot be decreased by using an alternate route
Roadway performance used
Stochastic User Equilibrium
Same as User Equilibrium but accounts for user variability

49. Dynamic Assignment Methods
Assign Traffic by Time of Day
Estimate origins & destinations by time of day
Apply an equilibrium method
Sometimes incorporate departure time choice
Sometimes incorporate system performance characteristics
See also page 288 of Meyer & Miller, 2001 textbook

50. OUTPUT = traffic volumes (cars per hour) on each road, travel times on each link, congestion levels

51. Planning 4-step Procedure Summary
Land Use and Economics
Trip Generation
Trip Distribution
Modal Split
Traffic Assignment
Main Input=Sociodemographics of study area
Main Output=Traffic volumes and level of service on roads
Secondary input-output (many depends on application and software)

52. Output from traffic assignment

53. Output from traffic assignment

54. Southern California Association of Governments
Case Study
Southern California Association of Governments

59. SCAG Model Details & Context
Conformity using DTIM and EMFAC
The EMFAC
The DTIM

65. Questions?