Optimal stochastic control for parking systems: occupancy-driven parking pricing

Efficient parking management can mitigate both traffic and parking congestion, and reduce the social costs and environmental impact. Parking pricing and information provision relying on parking sensors jointly serve as a dynamic stabilized controller for traffic demand management. Optimal parking pricing is formulated as a stochastic control problem. We obtain measurements of parking occupancy in real time and are used to update the optimal parking prices considering stochasticity on demand and travelers´ parking choice. The stochastic control formulation is solved using dynamic programming. There exists a critical occupancy for each time period, beyond which the parking prices should be set effective (namely, not free of charge). The numerical experiments show that the optimal parking policies based on stochastic control models can deal with different demand levels and generally outperforms the deterministic pricing schemes.