Route Awakening
How dynamic, AI-driven simulations can transform long-range transit planning and improve rider satisfaction at scale.
Jeff had seen this movie before. As the fictional director of urban mobility strategy at AnyLogix Transit Solutions (a fictional multimodal transportation company), he was no stranger to unexpected service complaints or public frustration. When the buses ran late, when light-rail ridership dipped, or when bike-share docks overflowed at the wrong times, it was Jeff’s phone that buzzed. And lately, it hadn’t stopped.
The company, like many in the transit tech space, had relied for years on simulation software to help city clients plan and optimize their networks. These tools could model a single bus line or anticipate traffic at a given intersection. But they were limited, stuck in snapshot thinking. They couldn’t scale to model how a city moves over time: how a morning rush builds from a few commuters into a flood, how traffic signals ripple congestion downstream, or how the sudden appearance of a street performer on a plaza could change pedestrian pat…