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In this paper, research is done in the influence of different terrain and traffic conditions on road sections on the driver?s driving performances, i.e. on the car energy efficiency and CO2 emission. A methodology aimed at determining to which extent unfavorable traffic and/or terrain conditions on a road section contribute to the driver?s worse driving performances, and also to determine when the driver?s aggressive driving style is responsible for greater fuel consumption and greater CO2 emission is proposed. In order to apply the proposed methodology, a research study was carried out in a cargo transportation company and 12 drives who drove the same vehicle on five different road sections were selected. As many as 284014 of the instances of the data about the defined parameters of the road section and the driver?s driving style were collected, based on which and with the help of machine learning a prediction of the scores for the road section and the scores for the driver?s driving style was performed. The obtained results have shown that the proposed methodology is a useful tool for managers enabling them to simply and quickly determine potential room for increasing the energy efficiency of the vehicle fleet and decreasing CO2 emission.

Due to the great market competition, transport companies face the need to reduce their vehicle fleet costs. The vehicle fleet managers’ actions on the driver’s driving style to achieve fuel consumption savings are measures to increase the fleet’s energy efficiency. The authors developed a model for evaluating driving style using a type-2 fuzzy logic system. The model comprehensively considers three parameters: engine speed, accelerator pedal position, and acceleration/deceleration. These parameters can precisely describe the driving style and additionally have a strong influence on fuel consumption. The model output is the driver’s score, representing the influence of driving style to fuel consumption. The model is tested in the company whose drivers have attended the eco-driving training course. Each driver’s driving style was monitored for 15 days to obtain trustworthy assessments regarding driving style. The result was twofold: firstly, we point out the importance of simultaneous observation of all three defined parameters to get reliable driver’s score in terms of driving style, and secondly, it is established that drivers have significantly different driving styles regardless of whether they have attended the same eco-driving training. The established differences in driving styles have a direct impact on the obtained differences in fuel consumption among drivers. The proposed model can significantly reduce fuel consumption depending on the driving style and increase the vehicle fleet’s energy efficiency.

This paper analyzes the effects of intercity bus suspension system oscillatory parameters on driver?s ride comfort and road damage. The analysis has been carried out through simulation by means of validated in-plane bus model with six degrees of freedom ex-cited by real road roughness signal. Low root-mean-square values of the weighted vertical acceleration (less than 0.315 m/s2) have been achieved by shock-absorbers with lower damping coefficient and softer suspension system springs. Low values of dynamic load coefficient provide low shock-absorber damping and softer springs. However, low crest factor values for both axles are accomplished for high shock-absorber damping and softer springs in bus suspension system. Results from this analysis could be used as reference for selecting proper oscillatory parameter values when designing road-friendly bus suspension system which in turn would increase vehicle energy efficiency. Presented methods, results and analyzes are the part of wider methodology for assessing the impact of bus suspension system on fuel consumption and CO2 emission.

Companies with own vehicle fleet for freight transport try to carry out the requested transport volume, with lowest possible transportation and maintenance costs. In order to make energy efficient and rational, the vehicle fleet operation the influence of the maintenance management has been considered in this paper. In this sense, a concept of maintenance management with a comprehensive approach has been developed. Within proposed concept the interdependent influences between vehicle maintenance process, transport process and environment as well have been described in detail, and the maintenance management activities on the strategical, tactical and operational level have been presented. The proposed concept was implemented in a company with vehicle fleet. Improvements were made in the vehicle fleet operation, which contributed to the reduction of transport and maintenance costs, whereby the requested transport volume in the observed period was performed.

The paper refers to the importance of maintenance management to increase the vehicle fleet energy efficiency. The fleet maintenance management influences as the vehicle maintenance process itself as well as the primary transport process but also their environment. In order to increase fleet energy efficiency by means of a more efficient maintenance management, it is indispensable to observe maintenance process, transport process and the environment. Since the implementation effects of such measures can be measured by different indicators, this paper analyses the influence of indicators in all three mentioned areas on management decision-making. In this sense, appropriate indicators have been defined and subsequently used in fleet maintenance management. To determine levels and intensities of interdependence as well as relative weight of selected indicators two methods have been combined: Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). A model was proposed with indicators' interdependence whose relative weights were calculated. The proposed model has been implemented in several companies with road vehicle fleets. Collected results show the perceived evaluation by company managers in view of maintenance management process influence onto their fleet energy efficiency. Besides, by proposed model implementation we have obtained equally managers' evaluation upon effectiveness and efficiency of the maintenance management within studied companies.