Forecasting fuel and electricity consumption is an important factor determining the direction of changes in road engineering solutions, traffic management, selection of routes for public transport and development more efficient car drive systems. With a reliable and easy-to-use computational tool, it is possible to reduce the consumption of primary energy sources and reduce the emission of toxic compounds in cities. An analysis of the impact of the selected variables describing traffic conditions on the fuel consumption has been included in this work, as well as the influence of the drive system hybridization. On this basis, the original, high accuracy fuel consumption model for the road-averaged input data has been presented, which enables taking into account the up-to-date traffic conditions. The presented in this paper model of the fuel consumption has been also extended for the regenerative braking systems. The final results of the analysis showed that modelling of the fuel and the energy consumption (including electric drives) of vehicles in city traffic, with an expected accuracy of 5%, can be successfully made using 5 specified variables describing traffic conditions. The original method of the input data collection, from the real world traffic, has been also presented. (C) 2019 Elsevier Ltd. All rights reserved.