Mobility Management

MIT Investigator(s): Jinhua ZHAO

Team Members:
  • Baichuan MOGraduate StudentMIT
  • Yunhan ZHENGGraduate StudentMIT
  • Yonah FREEMARKGraduate StudentMIT
  • Annie HUDSONGraduate StudentMIT
  •   SMART
  • Xin YANGPostdocSMART-FM
  • Hongmou ZHANGPostdocSMART-FM
  • Hui KONG*PostdocSMART-FM
  •   Collaborators
  • Mi DIAO Asst. ProfessorNTU
  • Hai WANGAsst. Professor SMU
  • Combine behavioral science and transportation technology to envision a future urban mobility system for Singapore that combines public transit, walking and bicycling, shared mobility and autonomous vehicles.

    Current phase of the project
    • Topic #1 Preference Formation for Autonomous Vehicle: Stated Preference Surveys Before and After Actual Trial Rides. The project aims to study the formation process of people's preference for autonomous vehicles (AV). In the short term, we will implement multiple stages of stated preference surveys before and after the trial ride of the AV prototypes to examine how people learn and adapt to the new transportation technology in the context of last mile modal choices.
    • Topic #2 Electroencephalograph (EEG) and Physiological Measures of Emotional Responses to Autonomous Vehicle using EEG Neuroheadset. The project aims to measure and analyze people’s emotional responses when riding autonomous vehicles in various traffic conditions. We will use electroencephalograph (EEG) neuro-headset as the main measurement and other physiological measures to corroborate.
    • Topic #3 Integrating Autonomous Vehicles with Public Transit Service: Last Mile Service to MRT Stations The project aims to design and test the new mobility scenarios in which Autonomous Vehicles are embedded in the public transit system. We will simulate the on-demand last mile service to/from Singapore MRT stations, testing a variety of business, operation, pricing and regulation models with different degrees of mixture between autonomous vehicles and public transit services.
    • Topic #4 Social mobility sharing: joint optimization of network efficiency and preference for human interaction.