Design ride-hailing pricing with fairness and pooling

Design and implement a pricing engine for a ride-hailing platform that maximizes company revenue while ensuring fairness to riders and drivers. Requirements: 1) Expose an API that, given a user request, returns multiple candidate routes for the rider to choose; 2) Compute a price for each candidate route using distance, duration, demand/supply, waiting time, and driver incentives; 3) Support carpooling: when a rider opts into pooling, compute the rider’s price considering shared segments and detours; 4) Enforce fairness constraints (e.g., caps on surge multipliers, equitable pricing across neighborhoods, transparent breakdowns); 5) Allow experimentation with pricing strategies and guardrails; 6) Handle real-time updates to demand and driver availability. Deliverables: a high-level system design covering components, data flows, and storage, plus pseudocode or code for the core price calculation function with inputs, outputs, and complexity. Discuss trade-offs, assumptions, and how you would validate fairness.