Time
Active (Launched 2024, in pilot phase)
Project Facts
- Duration 2024 – Present
- Field sites Hanoi Capital Region
- Principal investigator Assoc. Prof. Dr. Nguyen Ngoc Doanh
Objectives
- Simulate multi-scale urban transportation and air quality scenarios
- Enable citizens to make informed travel choices based on health, cost, and time
- Support municipal planners in forecasting the impacts of traffic interventions
- Promote behavior change and low-emission commuting through transparent data
Focus areas
- Real-Time Urban Mobility: Map traffic flow and congestion at city, district, and street levels with live updates.
- Air Pollution Exposure Modeling: Visualize CO₂ emissions, noise, and fine particulate exposure across different routes.
- Health-Conscious Trip Planning: Allow users to prioritize personal exposure (pollution, noise) in route choices.
- Policy Simulation and Green Transition: Test policy scenarios like road closures, electric fleet expansion, or lane changes before real implementation.
Methodology
- Multi-Layered Digital Twin Engine: Combines GIS, traffic sensors, and air quality data for city-wide visualization.
- Three Route Optimization Criteria:
- Time: Fastest options ranked first
- Cost: Most affordable transport modes ranked first
- Health: Routes ranked by exposure to pollution or user-generated emissions
- Real-time dashboards
- AI-Based Traffic & Emission Simulation:
- Model user-specific trips and calculate pollution impact, and adjust simulations with weather and time-of-day effects
Results
- Encourage eco-conscious and health-aware daily travel choices in Hanoi.
- Provide city departments with simulation tools to evaluate policies in silico before implementation.
- Improve understanding of how transportation contributes to personal and environmental health.
Partners & stakeholders
Target Users:
- Hanoi’s Department of Transport
- Public and private commuters
- Environmental and health researchers
- School communities and youth outreach programs
