Examples:

1. Accessible Route Planning: Using accessibility data integrated with the network map, generative AI can suggest routes suitable for people with specific needs (wheelchair accessibility, lift availability). It could even generate visual aids highlighting accessible features along the route.

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2. Real-Time Disruption Response: In case of unexpected delays or disruptions, generative AI can analyse transit authority APIs and network maps to suggest alternative routes or modes of transportation in real-time, minimising inconvenience for travellers. It could even generate personalised notifications with clear instructions and estimated travel times for suggested alternatives.

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3. Multimodal Trip Planning: By integrating data from different transportation options (e.g. bike share, car rentals), generative AI can create seamless multimodal itineraries. This could involve suggesting the best combination of public transport, walking, cycling or car rentals to reach a desired destination efficiently, considering factors like travel time, cost and user preferences.

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4. Personalised Stop Information: Generative AI can go beyond basic stop names on a map. It could provide dynamic information about points of interest, amenities and accessibility features near each stop, catering to the specific interests of the traveller.

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5. Interactive Route Visualisation: Generative AI can create dynamic and visually appealing route visualisations that go beyond static maps. Imagine 3D visualisations of the journey, highlighting key landmarks or providing estimated travel time for each leg of the trip.

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By using generative AI with public transportation network data, travel becomes more personalised, adaptable and visually engaging for visitors navigating unfamiliar cities.