Demand estimation of clean energy vehicles with fuzzy reasoning model

Abstract

Recently, Hybrid vehicles (HV) and electric vehicles (EV) are regarded as clean energy vehicles. In future low carbon city, the carbon dioxide emission should be reduced in urban transport section. Therefore, the urban transport system is regarded as a major issue in the smart city for future environmental sustainability. The study aims at investigating the introduction of clean energy vehicles (CEV) of trip makers in increase number of several low carbon vehicles. In the study, the vehicle ownership can be formulated respectively with fuzzy logic. The decision model of trip maker can be created to change the vehicles from petrol vehicle to electric vehicles as well as hybrid vehicles. Therefore, the demand estimation model for advanced type vehicles can be developed in terms of addition of travel mode types in the low carbon society. The model should be designed to formulate the singleton fuzzy reasoning in vehicle ownership of trip makers. The models may demonstrate the essential elements in traffic demand estimation of future smart cities. Finally, the results of the study can be effectively utilized to create the multi-agent models to describe the spatial distribution of hybrid vehicles and electric vehicles to reduce the carbon dioxide emission in the city.