Agent-Based Modeling System v2.0

TransitFlow
Simulation

Experience the future of public transport planning. Simulate complex bus networks, passenger behaviors, and emergent traffic phenomena using advanced Agent-Based Modeling on a simulated network database.

What is Agent-Based Modeling?

Traditional transport models often treat traffic as a fluid flow. TransitFlow takes a different approach. We use Agent-Based Modeling (ABM) to simulate the actions and interactions of autonomous agents to assess their effects on the system as a whole.

Bus Agents

Autonomous vehicles with specific capacities, speeds, and schedules that react to road conditions and passenger demand in real-time.

Passenger Agents

Individuals with unique origins, destinations, and "patience" logic. They make decisions on whether to board or wait based on crowding.

The Network Environment

A simulated database of stops and routes where agents interact, allowing emergent phenomena like "bus bunching" to naturally occur.

Simulating Agent Interactions...

Simulation Modules

Five distinct simulation environments tailored for different aspects of transport analysis, from basic mechanics to complex urban scenarios.

Applications & Benefits

Urban Planning

Test new route configurations and schedule changes in a risk-free digital twin environment before implementation in the real world.

Education & Research

A perfect tool for students and researchers to understand the non-linear dynamics of transport systems and queueing theory.

Operational Optimization

Identify bottlenecks and service gaps instantly. Use data-driven insights to improve passenger satisfaction and fleet efficiency.