A Complexity Reduction Method for Road Pricing Based on Demand Distribution

Various road pricing systems have been researched and implemented in many countries to reduce traffic congestion. The authors have also proposed a road pricing method based on demand distribution. The proposed method uses demand information to solve the combinatorial optimization problem for maximizing the total income of road providers under the constraint of specific traffic capacities. However, the previous work takes a long time to determine prices because it searches all combinations of departure and arrival places for appropriate prices. The searched combinations include unavailable routes. Therefore, this paper presents a complexity reduction method for the existing road pricing method based on demand distribution. The proposed method employs a technique of the compressed sparse row (CSR). The authors evaluated the proposed method and confirmed that the proposed method can reduce the calculation time in various road models.