Usage of Microscopic Simulation to Estimate the Environmental Impact of Road Transport

Makarova, Irina; Buyvol, Polina; Magdin, Kirill; Pashkevich, Anton; Boyko, Alekxey; Shubenkova, Ksenia

doi:10.1016/j.trpro.2020.02.013

Cited by 19 publications

(5 citation statements)

References 17 publications

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“…Since emissions from stationary sources are conditionally constant, it is possible to construct scatter maps of pollutants, on which emissions from stationary sources will be presented as "background", based on the maximum permissible emissions and production control in compliance with environmental requirements. The calculation of emissions from traffic flows is performed by adding two components: emissions from a moving stream (1) and emissions from vehicles in the area of controlled intersections (2).…”

Section: Methodsmentioning

confidence: 99%

“…One of the modern city problems, which is aggravated by the increase in the motorization level, is the lack of parking spaces, which refers both to places where shortterm demand is formed (near business, cultural, shopping, entertainment centers) and to population residence places (long-term vehicle storage). This problem has a number of consequences associated with the formation of spontaneous parking lots that impede the transport traffic, leading to traffic jams and congestion, as well as worsening the environmental situation in cities [1][2][3]. The issue of parking management is solved by creating parking management systems.…”

Section: Introductionmentioning

confidence: 99%

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Rational Organization of Urban Parking Using Microsimulation

et al. 2022

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Urbanization, which causes the need for population mobility, leads to an increase in motorization and related problems: the organization of parking spaces in cities, both near work places and recreational spaces, and not far from residential locations. This has a number of consequences. Therefore, the occupation of parking spaces near shopping centers and sports and recreation facilities, intended only for customers of these organizations, makes it difficult for direct customers to access services. This forces potential customers to look for a parking space in adjacent areas, often far from the target location. At the same time, the search for a parking space is stretched over time, negatively affecting the environment in the form of emissions and noise. On the other hand, there is a risk of losing a client. In the course of the study, we have analyzed the state of the problem and the directions of research on parking management in cities, and then we have studied the possibilities of using simulation models to find rational options for the organization of access to parking spaces and further using such models in decision support systems (DSS) as an intellectual core. The literature review showed that this is the most adequate option for an intelligent city parking space management system. At the same time, the environmental factor must also be taken into account. Research methods are based on field studies of traffic flows and emissions near parking places, and mathematical and simulation modeling. The proposed system will allow the evaluation of the effectiveness of the proposed changes in the organization of access to parking spaces, and, in the future, when implementing the obtained optimal solution, in practice, provide customers with a guaranteed parking space and reduce traffic and emissions. The introduction of such a system guarantees its quick payback, which is associated with the efficiency of use, as well as with the additional effects obtained from its implementation (improving the road situation, reducing vehicle emissions, solving social problems of the population, etc.), which is especially important for medium and small cities with limited budgets.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rational Organization of Urban Parking Using Microsimulation

et al. 2022

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“…), a multidimensional intelligent data model (online analytical processing cube (OLAP)) is used, which makes it possible to predict possible changes situation on the city roads in subsequent periods. Decisions are made on the basis of multivariate data analysis and computer experiments on simulated micro-models of the road network problem areas [ 26 ], which make it possible to assess, among other things, the ecological load on the territory (Fig. 1 ).…”

Section: Concept Of the Proposed Managerial Information Systemmentioning

confidence: 99%

Mobility and Road Safety Improvement by Optimizing Smart City Infrastructure Parameters: A Case Study

Buyvol

Yakupova

Shepelev

et al. 2021

Lecture Notes in Networks and Systems

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Accelerating urbanization leads to an increase in transport fleets. The road infrastructure does not have time to develop at the same pace, it gives rise to problematic situations in the field of organization and road safety. In order to solve these problems, an information managerial system has been developed. It aggregates information from several databases (information on traffic intensity, statistics of road traffic accidents, location and characteristics of infrastructure objects). Decisions are made on the basis of multivariate data analysis and computer experiments on simulated micro-models of the road network problem areas. The practical significance of the system lies in the ability to calculate the effects of the implementation of the proposed solutions at the stage of development of projects for the modernization and reconstruction of the road network parameters. The system can also be used for operational management decisions in the event of extreme situations in the city transport system (lockdown, public events).

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“…To obtain a highly accurate forecast of changes in the concentration of harmful pollutants, researchers have developed a hybrid model based on Empirical Wavelet Transform and a deep learning neural network (Kim et al, 2021;Zeng et al, 2022). Several researchers focused on the development of highly accurate emission models at the level of individual vehicles due to their diversity, driving conditions, and other factors (Motallebiaraghi et al, 2021;Makarova et al (2020)).…”

Section: Introductionmentioning

confidence: 99%