抄録
Global warming and its mitigation measures such as GHG (Greenhouse Gas) reduction have been extensively discussed all over the world. The transport sector occupied about 20% within the GHG of Japan. Countermeasures in the road traffic are urgent, since about 90% of the GHG emission of the transport sector is emitted from automobiles. For the effective reduction of the GHG such as CO2, quantitative analysis is necessary. Though the emission from the individual vehicle depends on various factors such as engine rotational frequency, speed, and acceleration, that relation is complicated. Therefore, there is a limit on the modeling by the regression analysis. Then, the model which estimates the CO2 emission from the individual vehicle using fuzzy neural network is developed in this study. By including this model in the traffic simulation, the estimation of CO2 emission becomes possible. Therefore, it is possible to examine traffic countermeasures considering the environmental effect.
