Побудова графової моделі визначення екологічності транспортного процесу

Abstract

Uncertainty of data during environmental monitoring prevents with confidently and objectively assessing the current condition of the environment, the influence of factors affecting the fuel consumption of vehicles during operation. In addition, it creates a serious problem in assessing the dynamics of this condition, especially when it comes to relatively small levels of pollution that are on the verge of the sensitivity of systems and devices in the car. It is precisely these tasks that include the determination of atmospheric pollution by emissions from road transport in conditions of variable weather and climatic conditions, carrying out routine maintenance, changing a configuration of an engine or transmission. The article discusses: a) factors related to the characteristics and vehicle systems, with the maintenance of vehicles. This category focuses on fuel consumption and CO2 emissions, which depend on the technical and operational characteristics of the vehicle, its weight and aerodynamics, tires and auxiliary systems, the quality and timeliness of maintenance and repairs; b) factors related to the environment and traffic conditions (weather conditions, road morphology and traffic conditions); c) factors related to a driver of a vehicle (driver qualifications, driving style). Optimization of factors related to vehicle systems and their characteristics has been performed; by using fuel of optimum quality and driving efficiently, you can achieve savings in fuel (financial) consumption and CO2 emissions. The article proposes the solution to a complex problem of managing the transport process while minimizing fuel consumption and CO2 emissions from passenger cars, depending on the road and climatic conditions and the driver's qualifications, based on the theory of fuzzy sets. This approach made it possible to largely compensate for the lack of objective information about the process due to its uncertainty by subjective expert data.