Miroslava Mikusova

Bio: Miroslava Mikusova is an academic researcher. The author has contributed to research in topics: Sustainable transport & Traffic generation model. The author has an hindex of 1, co-authored 2 publications receiving 2 citations.

Privileging Electric Vehicles as an Element of Promoting Sustainable Urban Mobility—Effects on the Local Transport System in a Large Metropolis in Poland

Abstract: The main purpose of this article was to determine the impact on the equilibrium of the local transport system from privileging EVs by permitting them to use bus lanes. The study used two sets of data: information on infrastructure and traffic management; and information on the recorded road network loads and traffic volumes generated by a given shopping centre—the E. Leclerc shopping centre (an important traffic generator within the city of Łodź, Poland). These sets were then used to develop a microsimulation traffic model for the shopping centre and the associated effects on the localised transport system. The model was constructed by means of the PTV Vissim software tool. An initial simulation was conducted that formed a basis for subsequent scenarios (in total, 17 simulations were performed). On the basis of the conducted analyses, it was established that—for the researched part of the transport system—privileging the still rather uncommon battery electric vehicles (BEVs) engendered a marginal deterioration of traffic conditions. At the same time, allowing BEVs to use bus lanes within the chosen research area had no negative impact on bus journey times.

Changes in Urban Mobility Related to the Public Bike System with Regard to Weather Conditions and Statutory Retail Restrictions

Abstract: The main purpose of the paper is to determine changes in transport behaviour of users of the public bike-share (PBS) scheme in a large Polish city, Łodź. By tracking GPS signals for individual trips taken by PBS users, it was possible to analyse their changeability (time and spatial) for periods before the implementation of statutory Sunday retail restrictions (2017) and after their partial introduction (2018). The study also took into account weather conditions, namely maximum and minimum daily temperatures and daily totals of precipitation recorded by a weather station in Łodź. In order to determine the correlations between certain weather conditions and PBS trips, the authors applied regression analysis. The results of the study showed that weekend cycling is less susceptible to the impact of weather than cycling on weekdays. At the same time, a comparative analysis of trading and non-trading Sundays proved that, during Sundays with retail restrictions, public bikes were used for longer, farther, and slower trips. These observations were confirmed by analyses of maps of traffic structure.

How Long Will Combustion Vehicles Be Used? Polish Transport Sector on the Pathway to Climate Neutrality

Abstract: Transformation of road transport sector through replacing of internal combustion vehicles with zero-emission technologies is among key challenges to achievement of climate neutrality by 2050. In a constantly developing economy, the demand for transport services increases to ensure continuity in the supply chain and passenger mobility. Deployment of electric technologies in the road transport sector involves both businesses and households, its pace depends on the technological development of zero-emission vehicles, presence of necessary infrastructure and regulations on emission standards for new vehicles entering the market. Thus, this study attempts to estimate how long combustion vehicles will be in use and what the state of the fleet will be in 2050. For obtainment of results the TR3E partial equilibrium model was used. The study simulates the future fleet structure in passenger and freight transport. The results obtained for Poland for the climate neutrality (NEU) scenario show that in 2050 the share of vehicles using fossil fuels will be ca. 30% in both road passenger and freight transport. The consequence of shifts in the structure of the fleet is the reduction of CO2 emissions ca. 80% by 2050 and increase of the transport demand for electricity and hydrogen.

Effects of Incorporating Rail Transport into a Zero-Emission Urban Deliveries System: Application of Light Freight Railway (LFR) Electric Trains

Abstract: This paper addresses the issue of incorporating rail transport into an urban delivery system. Its main purpose was to identify the possibilities of utilising rail transport in a Zero-emission Urban Delivery System (ZUDS) by applying Light Freight Railway (LFR) electric trains. The study applied the following research methods: literature review, observation, case study, and mathematical computations. In order to estimate the volume of transport external costs reduction resulting from shifting urban deliveries from road to rail transport in the city of Szczecin, the EU methodology was applied to specify the amounts of external costs generated by individual modes and means of transport. The research study showed that application of LFR electric trains makes it possible to significantly reduce external costs generated by transport. Moreover, this solution may have an impact on developing Clean Transport Zones (CTZs) and may also contribute to expansion of the ZUDS. The research study results also provide grounds to conclude that application of the LFR system makes it possible to reduce negative effects generated by Urban Freight Transport (UFT) and to achieve a coherent zero-emission system for handling cargo and passenger flows in cities, which consequently contributes to achieving electromobility goals in transport.

Determining factors affecting public bike ridership and its spatial change before and after COVID-19

Abstract: COVID-19, which has spread since late 2019, has caused drastic changes in transportation use. A few studies have already addressed the relationships between COVID-19 and transportation mode choice. However, in most cases, the analysis has been based on transit ridership during the early phases of the COVID-19 pandemic. In addition, few studies have focused on public bike use before and after COVID-19. This study examines the effect of COVID-19 on the ridership of public bikes and various determining factors of public bike use. An origin-destination (OD) analysis and spatial regression models were used with public bike ridership data from Seoul, Korea. The findings of the analysis can be summarized as follows. First, this study confirms that public parks have significantly influenced the increase in public bike ridership since the COVID-19 outbreak. This finding indicates that outdoor spaces such as riverside parks have played important roles in public bike ridership during the pandemic period. Second, this study finds that accessibility to subway stations strongly impacts the increase in public bike ridership. This means that the demand for public bikes as a connected transportation mode has increased since COVID-19. Third, access to bike lanes has had a significant impact on the increase in public bike ridership. This finding indicates the importance of expanding the public bike infrastructure network. Finally, this study makes policy proposals to promote public bike ridership during the COVID-19 pandemic.

A Microscopic Traffic Flow Model Characterization for Weather Conditions

Abstract: Road surfaces are affected by rain, snow, and ice, which influence traffic flow. In this paper, a microscopic traffic flow model based on weather conditions is proposed. This model characterizes traffic based on the weather severity index. The Intelligent Driver (ID) model characterizes traffic behavior based on a constant acceleration exponent resulting in similar traffic behavior regardless of the conditions, which is unrealistic. The ID and proposed models are evaluated over a circular road of length 800 m. The results obtained indicate that the proposed model characterizes the velocity and density better than the ID model. Further, variations in the traffic flow with the proposed model are smaller during adverse weather, as expected. It is also shown that traffic is stable with the proposed model, even during adverse weather.