1. Steps Closer to ABM: Example from Jerusalem
Gaurav Vyas, Peter Vovsha, Surabhi Gupta (WSP USA)
Danny Givon, Yehoshua Birotker, Issa Zananiri, Amir Mossek, Eitan Bluer (JTMT)

2. 4-Step vs ABM 4-step Models: Easier to develop
Ability to understand general travel pattern
Commuting patterns
Limited scope of transportation policies:
Explosion in number of matrices
Limited behavioral realism

3. 4-Step vs ABM Activity Based Model:
Ability to capture individual travel patterns
Behaviorally realistic
Wide spectrum of transportation policies

4. ABM If ABMs are better, why 4-step models are still in use?
Long development cycle
Substantial budget
Additional data requirement
Learning curve for users:
Data preparation, model understanding, output processing

5. Transitioning to ABM?
Possibility to take advantage of individual behavioral aspects:
Population synthesizer
New family of travel models  Hybrid
Hybrid Model
4-step model
ABM

6. Hybrid Model Practical compromise between 4-step and ABM:
Shorter development cycle
Moderate resources for development
Provide many advantages of ABM while preserving simplicity of existing 4-step model system
An intermediate stop on the way to a complete ABM
Learning curve
Input preparation

7. Directions of Hybridization
Individual microsimulation
Jerusalem Hybrid Model
Improve trip generation and
car ownership by having more variables
Conventional 4-step
Tour-based concept
Consistency of HB and NHB trip generation & distribution, round-trip TOD

8. Classification of key structural features
Microsimulation trip-based
Aggregate trip-based (conventional 4-step)
Microsimulation tour-based (conventional ABM)
Aggregate tour-based
Microsimulation
Aggregate
Trip-based
Tour-based

9. Typical Hybrid Model Trip-based Tour-based Population synthesizer
Microsimulation trip-based
Microsimulation tour-based
Microsimulation
Aggregate trip-based
Aggregate tour-based
Aggregate
Mode choice
Assignments

10. Jerusalem Hybrid Model
Hybrid model as the first step of the ABM development
ABM development close to completion
Two models developed using same socio-economic, land-use data, and transportation network

11. General Model Structure, Jerusalem
PopSyn
Matrix Construction
Car Ownership
Employment
Microsimulation
Trip Purpose
Trip Generation
Seed Matrix
Aggregate
Trip Distribution
Impedance
Counts
Matrices by
Segments
Network Simulation
Split-Assignment

12. Modeling Daily Demand, Jerusalem
Population, Employment, Car Ownership
Matrix Construction
Matrix Construction
Matrix Construction
Matrix Construction
Segment
Segment
Segment
Segment
Network Simulation
Network Simulation
Network Simulation
Network Simulation

13. Trip purposes in Individual Trip Production Model
11 Trip purposes by direction:
Home-to-Work (HW+)
Work-to-Home (WH-)
Home-to-Education (HE+)
Education-to-Home (EH-)
Home-to-Maintenance (HM+)
Maintenance-to-Home (MH-)
Home-to-Discretionary (HD+)
Discretionary-to-Home (DH-)
Non-home based as stops on work tours (NHB1)
Non-home based as at-work trips (NHB2)
Non-home based as non-work trips (NHB3)

14. Individual Trip Production Model
Rich set of explanatory variables:
Population sector, gender, age, employment status, student status, occupation, income, household composition, car ownership, accessibilities
Similar to ABM activity participation model

15. Estimation Results: Auto AM Mandatory
Variables HW HE WH EH
Constants by sector and gender
Arab Female
-1.930
-1.918
-9.000
-3.891
Arab Male
-1.553
-2.050
-3.405
Ultra Orthodox Female
-3.197
-1.674
-4.806
-4.904
Ultra Orthodox Male
-3.268
-1.399
-3.504
Secular Female
-2.264
0.071
-6.091
-5.758
Secular Male
-2.352
-0.007
-4.466
-6.106
Age
Arab
Linear
0.040
0.033
Squared
-0.001
Ultra Orthodox
0.089
0.008
Secular
0.052
-0.060
If Employed more than 35 hours per week
0.860

16. Estimation Results: Auto AM Mandatory
Variables HW HE WH EH
Female and presence of 0-4 yrs old child in hh
-0.355
Occupation (if worker)
Clerical Worker
-0.210
-9.000
Service, Selling Agent
-0.377
Academic Professional
-1.247
Manager
Skilled Agriculture
Manufacturing, construction and other skilled worker
0.191
Non-professional employee
-0.250
-0.821
Household Income
0-3,500 NIS
-0.184
-0.245
19,000+ NIS
0.192
Household size
-0.102

17. Estimation Results: Auto AM Mandatory
Variables HW HE WH EH
Car sufficiency levels
Zero cars
-1.440
-2.840
-1.946
-0.701
Cars less than number of adults
-0.323
-0.637
Age categories
age>15 and if Student
-0.203
-0.442
7-15 years
-1.146
0.219
-9.000
-2.745
0-6 years
0.000
0.396
-1.676
Accessibility from home
For Work by Transit
-0.111
For work by non-motrized
-0.040
For Education by Transit
-0.160
For Education by non-motrized
-0.010
Interactions
Both WH+ and EH+
-2.835
Both WH- and EH-
Both WH+ and WH-
0.388
Both EH+ and EH-
1.824

18. Three Possible Level of Hybridization

19. 1=Light trip-based hybrid
Tour-based
Trip generation by direction
Car ownership
Microsimulation
Aggregate
Population synthesizer
DAP
HB mode choice
Assignments
NHB trip generation
NHB trip distribution
NHB trip mode choice
HB trip distribution
HB Trip TOD choice
NHB TOD choice

20. 2=Light tour-based hybrid
Trip-based
Tour-based
Car ownership
Microsimulation
Aggregate
Population synthesizer
DAP, tour/stop frequency
Convoluted trip distribution
Mode choice
Assignments
Tour TOD
Tour distribution

21. 3=Heavy tour-based hybrid
Trip-based
Tour-based
DAP, tour/stop freq.
Microsimulation
Aggregate
Population synthesizer
Mode choice
Assignments
Work & school location choice
Car ownership
Tour primary destination
Tour TOD choice
Stop location

22. Conclusions
Hybrid models are practical compromise between 4-step and ABM
Extent of Hybridization depends on the MPOs requirement
A good Hybrid model is a “stop” on the way to ABM, not a deviation

23. Contact(s) Gaurav Vyas Additional contact Technical Principal
Systems Analysis Group
Additional contact
Peter Vovsha, PhD
Yehoshua Birotker,
JTMT