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LEADING THE MOBILITY TRANSFORMATION

Shan Bao

Mcity > OUR WORK > Research > Shan Bao
  • An Investigation of Drivers’ Adaptation Behavior and Decision Making When Interacting with CAV Technologies

    An Investigation of Drivers’ Adaptation Behavior and Decision Making When Interacting with CAV Technologies

  • Examination of Operator-State Monitoring and Operator Engagement Approaches as Strategies for Mitigating Human-Factors Challenges Associated with Transfer of Control During Automated Driving

    Examination of Operator-State Monitoring and Operator Engagement Approaches as Strategies for Mitigating Human-Factors Challenges Associated with Transfer of Control During Automated Driving

  • Training Methods to Support Drivers’ Ability to Use AV Systems

    Training Methods to Support Drivers’ Ability to Use AV Systems

  • The Development of Augmented Vehicle Pedestrian Connection for Decision-Making in Autonomous Driving and Pedestrian Safety

    The Development of Augmented Vehicle Pedestrian Connection for Decision-Making in Autonomous Driving and Pedestrian Safety

  • Studying Interactions Between Drivers and Vulnerable Road Users at Intersections Using Existing Naturalistic Driving Data

    Studying Interactions Between Drivers and Vulnerable Road Users at Intersections Using Existing Naturalistic Driving Data

  • Interactive Human–Autonomous Vehicle Dynamics in Traffic: Modeling, Simulation, and Control

    Interactive Human–Autonomous Vehicle Dynamics in Traffic: Modeling, Simulation, and Control

  • How Does a Driverless Car Interact and Communicate with Pedestrians

    How Does a Driverless Car Interact and Communicate with Pedestrians

  • Identify and Testing UI Design Needs for AV-VRU Communications

    Identify and Testing UI Design Needs for AV-VRU Communications

  • Developing Safe Strategies for Automated Vehicle Failures through Text Mining and Human Factors Methods

    Developing Safe Strategies for Automated Vehicle Failures through Text Mining and Human Factors Methods

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