Multimodal Mobility Systems
Shared Mobility and Public Transit
Multimodal urban mobility systems
Trip chain and hierarchy analysis (Macroscopic Multimodal Hierarchy, MMH)
Big data analytics and AI solutions
Artificial data generation to address real-world data scarcity
Demand-Responsive Transit (DRT) [in collaboration with Studio Galilei]
Joint optimization of planning and operations in DRT
Reinforcement learning algorithms for large-scale DRT operations
DRT for promoting equity and sustainability
Robotaxis
Parking and charging infrastructure planning
Integration of robotaxis into multimodal transportation systems
Purpose-Based Vehicles (PBVs)
Mobility Electrification
Electrification of shared mobility and public transit (e.g., battery electric bus planning)
Electric mobility hub network planning
Urban Air Mobility (UAM)
Evaluation of environmental and social impacts
Analytical and simulation-based modeling
Optimal planning and operations for logistics and passenger services
Automated Mobility
Dedicated lane and route planning for AV/non-AV mixed traffic (AV: Autonomous Vehicle)
Logistics systems utilizing automated trucks
Pavement and bridge management using AV sensor data
Infrastructure Management
AI applications for infrastructure decision-making processes
Reinforcement learning for joint optimization of monitoring, inspection, maintenance, and reconstruction across large-scale infrastructure networks (e.g., highways, bridges, railways, airports)
Automated infrastructure condition monitoring using AI and non-dedicated sensors
AI and robotics-based pavement repair systems [in collaboration with Rovoroad]
Life cycle analysis for reducing greenhouse gas emissions
Disaster Management
Pre-disaster and post-disaster infrastructure management strategies
Game-theoretical approaches to disaster response and recovery
Infrastructure planning under risks of sea level rise and wildfires
Graph-theoretical evaluation of mobility infrastructure vulnerability and resilience
Management of critical infrastructure systems