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)

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

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

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

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

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

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

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

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

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

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

Modeling Daily Demand, Jerusalem 6.00-8.59 9.00-11.59 12.00-14.59 15.00-18.59 Population, Employment, Car Ownership Matrix Construction Matrix Construction Matrix Construction Matrix Construction Segment Segment Segment Segment Network Simulation Network Simulation Network Simulation Network Simulation

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)

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

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

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

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

Three Possible Level of Hybridization

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

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

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

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

Contact(s) Gaurav Vyas Additional contact Technical Principal Systems Analysis Group Gaurav.Vyas@wsp.com Additional contact Peter Vovsha, PhD Peter.Vovsha@wsp.com Yehoshua Birotker, JTMT birotker@jtmt.gov.il