Pricing model to redistribute demand in urban transport
Paraná case
DOI:
https://doi.org/10.64876/radi.v26.5Keywords:
Time-based management, economic incentives, stochastic simulation, urban mobility, fare planning.Abstract
This study evaluates the impact of a mixed fare strategy on the public transport system in the city of Paraná, aiming to redistribute peak-hour demand through economic incentives. A quantitative methodology was applied, combining smartcard transaction data with user surveys and stochastic simulations using the Monte Carlo method. The results show that fare discounts of 30% and 40% significantly reduce passenger volumes during peak hours without generating new congestion periods. A segment of users with flexible travel schedules was identified as responsive to pricing incentives. The proposed strategy improves operational efficiency, reduces overcrowding, and optimizes resource allocation. These findings support the implementation of dynamic fare policies as a viable tool for demand management and service quality enhancement in intermediate cities.
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