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AI for Smart Mobility: Multimodal Routing & Transit Optimization

Artificial intelligence is revolutionizing public transport by creating smarter, more efficient routes and improving the overall rider experience.

mysimulator teamUpdated June 2026≈ 3 min read▶ Open the simulation

AI for Smart Mobility: Multimodal Routing & Transit Optimization

Improve public transit and multimodal journeys with demand-aware routing, headway control, ETA accuracy, and rider experience.

AI can reduce wait times, improve reliability, and optimize multimodal routes across bus/rail/micro-mobility by combining forecasts, optimization, and real-time control.

Personalized suggestions (accessibility, bike, cost).

Real-time crowding info and alerts.

Headway regularity control to reduce bunching.

live demo · related simulation● LIVE

Graph builder for multimodal network.

ETA models per segment; demand forecasts per stop/interval.

Headway control policies; routing algorithms with constraints.

Frequently asked questions

What is the purpose of integrating GTFS/RT data with telemetry to build a network graph?

Integrate GTFS/RT and telemetry; build n.

How should ETA and demand models be trained and validated?

Train ETA and demand models; validate against ground truth.

What is the role of deploying a trip planner with real-time ETAs?

Deploy trip planner with real-time ETAs; add crowding info.

How are headway control and dispatch policies implemented within the simulator?

Pilot headway control and dispatch policies on key routes.

▶ Try it live

Everything above runs in your browser — open Earthquake Wave Propagation Simulation and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Earthquake Wave Propagation Simulation simulation