Dynamic network pricing to contain urban air pollution in stochastic environment

Abstract

Network pricing is an effective transportation demand management scheme to reduce traffic and control air pollution, particularly in CBDs. In this study, congested area cordon entry and Park-and-Ride (P/R) facility use are priced for automobiles. Increase in these prices may reduce private auto demand by impelling some of the auto passengers to use public transport from the origin of their trips, or encouraging them to park their cars at the P/R facilities and use buses, or pay the entrance fee and drive inside the cordon. A Markov decision process has been devised to find an optimal policy for pricing the P/R facilities and cordon entry in a city within a variable demand context. This process is sensitive to weather condition (more favorable atmospheric condition allows lower prices). It leads to a balance between the costs of pollution hazards to the public at large on one side and the cost imposed upon auto drivers to take the next best decisions and their travel times and costs on the other side, thus giving a resilient character to the city. The model has been applied to the network of a large urban area and the results are analyzed. Suggestions for further research end the discussion.