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AI-Powered Transportation Planning for smarter & efficient transit networks
Optimize network performance, routing & scheduling using AI planning models — beyond the limitations of manual planning
Public transit route planning & scheduling is an NP-hard problem with billions of permutations & can take years for fastest computers to solve.
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Street Surge's AI-powered planning model solves complex multi-vehicle, multi-objective optimization problems, designing near-optimal, demand-driven transport routes & networks for enhanced accessibility & ridership. Model inputs:
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Granular Demand Matrix (upto 2000 TAZs)
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Operational Constraints: Route Length, Capacity, Charging Breaks, Driver Breaks, Dead Mileage
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Passenger Experience Constraints: Accessibility, Frequency, Transit Time penalty
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Existing Supply/Route Network: Metro, Tram, Bus routes which need to be complemented
Demand Driven Planning
Optimized for maximizing coverage of travel demand
Enhance Transit Accessibilty
Measure accessibility impact of the transit network
Faster Turnaround Times
Shorten project duration from months to
few weeks
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