Akademik Veri Yönetim Sistemi
International Symposium on Environmental Science and Technology, Shanghai, Çin, 2 - 05 Haziran 2009, ss.773-777
In past years, several emission models have been developed and presented in specific technical literature. Most of them calculate gas emission through the values of speed and acceleration in a standard urban driving cycle. Some other models consider the elementary component of vehicles movement, in order to characterize pollutants emission. In these models, speed is usually the kinematic variable considered, but sometimes acceleration is needed to describe changes over time. The model proposed in this work is made of a Dynamic Link Loading (DLL) model and an emission model. The DLL model is a mesoscopic one, and is part of a wider model, relevant to transportation networks, based on two submodels: the link model, proposed here, and the node model, for which the research is still in progress. The proposed model allows calculating explicitly speed and acceleration of the vehicles and, therefore, can be used favorably to our aim. In this work, to calculate vehicles' emission we used a model based on real driving conditions, rather than on driving cycles simulated in laboratory. An integrated model is used to calculate flow propagation along the bridge on Bosphorus, in Istanbul (Turkey), and pollutant emission and diffusion at the exit of the bridge. The bridge has 3 lanes for each direction, plus a reversible lane. It is 4 km long, and its capacity is 9000 vehicles/hour; we assumed its maximum density equal to 600 vehicles/km. The explicit calculation of vehicles cinematic parameters, like speed and acceleration/deceleration, through the proposed DLL model brings to more precise results in the simulation of traffic pollution phenomena. In fact, the most effective emission models require as input the acceleration, which the most common dynamic loading models usually do not calculate in an explicit way. On the contrary, the proposed integrated model calculates directly vehicles' speed and acceleration. Results can be easily used to simulate different scenarios and to estimate their performances. Consequently, it is possible to take effective planning interventions to control traffic flow, and reduce pollution, therefore approaching the system optimum.