Optimal dynamic investment allocation on construction of intelligent transportation infrastructure and road maintenance with environmental costs

This paper presents the optimal dynamic investment allocation on intelligent transportation infrastructure construction and road maintenance with considering environmental costs. We propose a stochastic optimal control problem with uncertain traffic volume, aiming to minimize the expected system total cost, which consists of the fixed travel cost, the congestion delay cost, the congestion environmental cost and the road maintenance environmental cost. By adopting Hamilton-Jacobi-Bellman equation, we propose the optimal dynamic strategy for investment allocation, which is a feedback control and determined by two observable variables, i.e., traffic volume and road network capacity. We also conduct a case study of Beijing, China, for the proposed dynamic strategy. The numerical results demonstrate that our strategy can lower the congestion delay and related environmental cost significantly, which is enough to remedy the possible increase in the road maintenance environmental cost. Comparing with traditional strategies, the new dynamic strategy provides closely 100% of the benefit cases.