An increasing number of motor vehicles are connected with negative environmental impacts in relation to their operation. Among the main negative effects are exhaust gas emissions production. The annual increase in passenger cars and emissions from them deteriorates air quality daily. Traffic junctions also have a negative impact on increasing emissions production by exhaust gases. This situation may be caused by vehicle speed fluctuation, mainly when they get closer or leave. This study focuses on the emissions produced by exhaust gases after a road vehicle starts. The research was performed with a combustion engine vehicle on a route 30 m long. The vehicle was simulated in three different ways of starting (uphill, on ground level/plain and downhill). The values of carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC) and nitrogen oxides (NO_X) were observed, as well as the vehicle’s operation performance during start-ups. The research results showed that the lowest emissions production is when the vehicle is starting downhill. There, the emissions increased up to a distance of 9.7 m from the start. After reaching this distance, the emissions decreased and the vehicle speed continued to increase. While the vehicle started uphill, the emissions increased up to the distance of 16.8 m. After reaching this distance, the emissions began decreasing. Due to this fact, this type of testing is assessed as “the worst” from the emissions production point of view. The research demonstrates the relations between a road gradient representing starting on a plain surface and a vehicle’s emissions produced by the exhaust gases. It is known that exhaust emissions are higher predominantly at junctions. They depend considerably on vehicle speed and driving continuity on a route. This research helps to quantify all the data and, thus, to provide a possibility of further solutions in the future as a tool for emissions reduction in cities and close to traffic intersections.

The aim of this paper is to familiarize the reader with the general application of MCDM methods on a specific example of City Logistics in order to find the optimal solution for operation of the territory. In its introductory part, methods used for quantitative evaluation of variant solutions are briefly described, and then the so-called Forces Decision Matrix Method (FDMM) including the determination of criteria weights using pairwise comparison of variants according to individual criteria on the specific example is applied. In the final part of the paper, the advantages and disadvantages of using this method for more complex tasks with multiple variant solutions based on the results of the practical example are evaluated and the so-called Saaty's method based on the quantitative pairwise comparison to partially eliminate differences in the mutual evaluation of weights and criteria is mentioned.

The presented article deals with research on the dependence between road vehicle fuel consumption and the longitudinal height profile of the road. The main research goal is to investigate the difference in fuel consumption during acceleration on different longitudinal profiles of the road (i.e., flat surface, downhill) based on the actual investigation. In the first part of the article, important factors influencing fuel consumption during vehicle acceleration are summarized and a review of literature dealing with this issue is carried out. The next part focuses on the very real-world measurement. In addition to fuel consumption, other parameters were recorded that could be detected by a professional measuring laboratory. In the final part of the article, all the recorded data are evaluated, compared with research question and an actual example is given. Based on the evaluation, it could be concluded that approx. 100 L of fuel can be saved in one week thanks to the implemented measures. Thereafter, recommended possibilities for further use of these findings in technical practice are outlined in the conclusion.

This paper analyses road traffic volumes in the urban environment for the purpose of traffic planning and creation of traffic models. For modelling traffic in a certain area, the initial information about transport demand and distribution in given area is required. The demand for transport is further re-distributed to the transport network and measured against the current road traffic volumes / intensity of traffic. Traffic volumes over time are characterized by various periodic and non-periodic influences (variations). By studying these variations, the tools can be specified for making the final estimate of traffic volumes for a specific time period, a specific type of road or specific vehicle category, and for improving the traffic models for a specific area. In this paper, the authors study time variations in traffic volumes using the data obtained from vehicle detectors for monitoring traffic located on roads in the city of Ceske Budejovice, the Czech Republic.

By designing road infrastructure, it is necessary to adapt the real situation to current development trends and respond accordingly to the intensity of traffic on the transport network. The development of the traffic situation is generally very dynamic, difficult to predict and influenced by a number of other factors. Modern technologies enable adaptive traffic flow management based on the sharing and evaluation of traffic information obtained in real time from traffic monitoring systems or even from vehicles as such (e.g. thanks to “Connected Vehicles” technology). The article first carries out a literature review of professional literature and scientific articles dealing with the issue of autonomous mobility and autonomous management of transport processes. That is followed by a description and creation of own algorithm for autonomous control of vehicles at the level crossing, including description of used data, methods and proposed solutions. Finally, the developed method (algorithm) is tested by the Anylogic simulation program in a real environment, as a case study of autonomous vehicle decision-making at the level crossing.