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.
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.
Autonomous vehicles with specific capacities, speeds, and schedules that react to road conditions and passenger demand in real-time.
Individuals with unique origins, destinations, and "patience" logic. They make decisions on whether to board or wait based on crowding.
A simulated database of stops and routes where agents interact, allowing emergent phenomena like "bus bunching" to naturally occur.
Five distinct simulation environments tailored for different aspects of transport analysis, from basic mechanics to complex urban scenarios.
The fundamental microsimulation loop. Control arrival rates, bus capacity, and dwell times to observe basic queue formation and load balancing.
Introduce chaos factors and manipulate headway variables. Test the network's resilience against irregular traffic speeds and fluctuating demand curves.
Real-time visualization of key performance indicators. Monitor passenger wait time distributions and bus load factors via dynamic charts.
Gamified disaster scenario. Manage a fleet under extreme conditions. Balance budget vs. service quality while dealing with passenger patience limits.
The ultimate urban challenge. Utilize the Inspector tool to manage a dense network. Click entities for detailed states and optimize the entire metro grid for maximum efficiency and profit.
Test new route configurations and schedule changes in a risk-free digital twin environment before implementation in the real world.
A perfect tool for students and researchers to understand the non-linear dynamics of transport systems and queueing theory.
Identify bottlenecks and service gaps instantly. Use data-driven insights to improve passenger satisfaction and fleet efficiency.