SimMobility: Pax

MIT Investigator(s): Moshe BEN-AKIVA, Christopher ZEGRAS and Joseph FERREIRA


Team Members:
MIT
  • Youssef ABOUTALEBGraduate studentMIT
  • Rounaq BASUGraduate studentMIT
  • Siyu CHENGraduate studentMIT
  • Daniel L ENGELBERGGraduate studentMIT
  • He HE Graduate studentMIT
  • Yifei XIEGraduate studentMIT
  •   SMART
  • Kakali BASAKSenior Software ManagerSMART-FM
  • Karina Pertiwi HERMAWAN SMART ScholarSMART-FM
  • Thi Diem Trinh LEResearch ScientistSMART-FM
  • Quy Duy NGUYEN PHUOC PostdocSMART-FM
  • Simon OHPostdocSMART-FM
  • Meng ZHOUPostdocSMART-FM
  • Chetan ROGBEERPrincipal Software EngineerSMART-FM
  • Lukasz KREFTSenior Software EngineerSMART-FM
  • Hong Phuoc LEResearch EngineerSMART-FM
  • Ding Eli LIM*Software EngineerSMART-FM
  •   Collaborators
  • Gary TANAssoc. Prof.NUS
  • Mi DIAO*Asst. Prof.NUS
  • Raymond ONG Asst. Prof.NUS
  • Qiang MENGProf.NUS
  • Develop and integrate state-of-the-art behavioral models with simulation tools to predict the impact of different mobility portfolios, including flexible mobility on demand services and autonomous mobility, on travel demand and activities, both for passengers and freight, and on transportation networks and land-use.

    Short-term
    • Calibration of SimMobility short-term, extending the current work to public transportation data and the entire Singapore network while proposing innovative methods to handle the complexity of such extensions.
    • Develop flexible traffic, fleet and information control modules that will enable the design and testing of innovative ITS solutions.
    • Implement a Performance Measures Module for the analysis of traffic performance indicators (including safety and environmental indicators).
    • Revise and extended the existing pedestrian simulation module to integrate with the existing multi-modal framework.
      Mid-term
    • Implement a rescheduling plan model (i.e. in terms of en-route choice, changes in modes, departure times and trip making) using a publish-subscribe mechanism of events.
    • Representation of individual day-pattern choices in the current version of the pre-day component using the already developed two-stage model and based on customized day pattern generation from a probabilistic grammar approach.
    • Uncertainty and sensitivity analysis of the parameters involved in the mid-term simulator using existing methodologies.
      Long-term
    • Further development and testing of the SimMobility platform long-term components that relate to land use, residential and commercial real estate, and their sensitivity to transportation infrastructure and various accessibility and mobility measures.
    • Use of SimMobility platform to analyze the real estate and housing market implications of alternative scenarios for introducing enhanced mobility options.
    • Formulation and calibration of enhanced behavioral models for firm (re)location and job assignment.
    • Further investigation of socio-economic differences, household constraints, and neighborhood characteristics that can improve our understanding of observed activity spaces, daily activity patterns, and non-work destination choices.
    • Scenario analysis: testing the model system’s capability to reflect multi-dimensional uncertainty in forecasts of various possible interventions (such as AMOD).
      Development
    • Development of innovative computational design and implementation methods to ensure the efficient use of the long-mid-short term models.
    • Design and implementation of a flexible structure for model plug-and-play, a unified user interface and visualization portfolio.
    • Development and maintenance of supporting tools for the open-source release of SimMobility.
    • Calibration of integrated SimMobility (long-mid-short term).
    • Simulation of the greater Boston area and evaluation of the impacts of behavior and scenario differences between different cities.
      Behavioral Models
    • Incorporate new modes in the estimation of the model using data available from FMS.
    • Extend the modelling framework of the needs-based approach with regard to the generation of distinct activity-travel patterns by individual travelers.
    • Extend the probabilistic grammar rule-based framework for the development of a customized choice set of day patterns by incorporating accessibility measures.
    • Extend the modelling framework of the adaptive route choice model to allow routing policy choices at intermediate locations in addition to the origin (interactions with FMS and SimMobility).
      Public Transportation
    • Implement mass rail transit (i.e. MRT) with key details of train movements in a simulation platform such as SimMobility mid-term and short-term. Efforts are being made to acquire relevant data to simulate the supply side of MRT.
    • Implement a multi-modal access/egress based public transport route choice model in the SimMobility mid-term simulator using an estimated model.
    • Implement public transport passenger movements in SimMobility short-term for an accurate representation of dwell times, waiting times, etc.
    • Extend the demand, supply and data models within DynaMIT to bus and mass rapid transit (interactions with FMS, SimMobiliyt and DynaMIT).
      Scenario Analysis
    • Technology Scenarios - New Modes: Objective is to extend both demand and supply modeling for the scenario analysis of new modes, namely (1) existing transportation services: car sharing, and on-demand services; and (2) innovative transportation solutions: FMOD and AMOD (interactions with FMS, SimMobility, DynaMIT and Behavioral Models).
    • Policy Scenario
    • Freight Scenario