Safety Assessment of Adjacent Roads Sections via Maximum Entropy Driver's Perception Field

Kulbashna, N.; Lynnyk, Iryna; Galkin, Andrii; Прасоленко, О.В.; Dulfan, Sergii

doi:10.26552/com.c.2020.4.182-190

Cited by 3 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Previous Studies On the Impact Of Traffic Flow Entropy On Ro...mentioning

confidence: 99%

“…Perhaps, only the works of Ukrainian authors [104,105] highlight the relationship between the entropy characteristics of the environment and road accident rates. The authors [104,105] presented the results of studying the impact of the driver's perception field entropy on road accident rates. N. Kulbashna et al have observed, drawing on findings from [88], that an increase in the differential of maximum entropy between neighboring areas correlates with a decline in the accident rate, albeit up to a specific threshold [104].…”

Section: Previous Studies On the Impact Of Traffic Flow Entropy On Ro...mentioning

confidence: 99%

“…The authors [104,105] presented the results of studying the impact of the driver's perception field entropy on road accident rates. N. Kulbashna et al have observed, drawing on findings from [88], that an increase in the differential of maximum entropy between neighboring areas correlates with a decline in the accident rate, albeit up to a specific threshold [104]. This correlation is attributed to the fact that accidents predominantly occur in zones where drivers are adjusting and the road conditions are perceived as comfortable.…”

Section: Previous Studies On the Impact Of Traffic Flow Entropy On Ro...mentioning

confidence: 99%

See 2 more Smart Citations

Ideology of Urban Road Transport Chaos and Accident Risk Management for Sustainable Transport Systems

Morozov,

Petrov,

Shepelev

et al. 2024

Sustainability

View full text Add to dashboard Cite

Transport systems are complex systems present in modern cities. The sustainability of all other urban systems depends on the sustainable functioning of urban transport. Various processes occur within transport systems. Road traffic is one of them. At the same time, road traffic is a rather complex process to manage, which is explained by the influence of many different internal and external environmental factors. The unpredictable and chaotic behavior of each vehicle in a traffic flow complicates predicting the transport situation and traffic management. This problem gave rise to several unsolved problems, including traffic congestion and road accident rates. The solution to these problems is connected with sustainably managing transport systems in terms of road traffic. However, numerous regularities between elements within the system should be understood in order to implement the management process. Unfortunately, the results of many previous studies often reflect only partial regularities and have limited functionality. Therefore, a new approach to urban traffic management is needed. As opposed to the existing solutions, the authors of this paper propose to implement management based on the regularities of changes in the chaos of the transport system. In this regard, the purpose of this research is to establish the relationship between road traffic chaos and road accident rates. The general methodological basis of this research is the system approach and its methods: analysis and synthesis. The theoretical studies were mostly based on the theories of chaos, dynamic systems, and traffic flows. The experimental studies were based on the theories of experimental design, probability, and mathematical statistics. To achieve this goal, a profound analysis covered studies on the sustainability of transport and dynamic systems, sociodynamics, and traffic. The authors proposed considering the relative entropy of lane occupancy at signal-controlled intersections as a measure for assessing traffic flow chaos and sustainability. Notably, as the main conclusions, the authors established regularities for the influence of entropy on the kinetic energy of traffic flows and injury risk. It also makes sense to emphasize that the initial data for the experiment were collected via real-time processing of video images using neural network technologies. These technologies will further allow for the implementation of traffic management and real-time forecasting of various events. Ultimately, the authors identified changes in injury risk depending on the level of road chaos. According to the authors, the obtained results can be used to improve the sustainability of urban transport systems. The research identified changes in injury risk depending on the level of road chaos, which could have significant implications for urban traffic management strategies.

show abstract

Section: Previous Studies On the Impact Of Traffic Flow Entropy On Ro...mentioning

confidence: 99%

Section: Previous Studies On the Impact Of Traffic Flow Entropy On Ro...mentioning

confidence: 99%

Section: Previous Studies On the Impact Of Traffic Flow Entropy On Ro...mentioning

confidence: 99%

See 1 more Smart Citation

Ideology of Urban Road Transport Chaos and Accident Risk Management for Sustainable Transport Systems

Morozov,

Petrov,

Shepelev

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

Naturalistic Driving Study: Methodological Aspects and Exemplary Analysis of a Long Roadwork Zone

Pashkevich¹,

Bartusiak

Burghardt

et al. 2021

Research Methods in Modern Urban Transportation Systems and Networks

View full text Add to dashboard Cite

Risk Management Methodology for Transport Infrastructure Security

Makarova¹,

Yakupova²,

Buyvol³

et al. 2022

Infrastructures

View full text Add to dashboard Cite

The development of transport infrastructure is associated with risks, expressed in the likelihood of harm to the road users’ health during road accidents and their consequences. The risk management process is aimed at reducing the influence of factors that contribute to the occurrence of an accident and increase the consequences’ severity after it. This article proposes a risk management methodology within five stages: identification, analysis and evaluation, processing, development of recommendations, and monitoring. For each step, we describe the methods and models that allow us to effectively solve the problem of risk management. We proposed a risk management algorithm based on feedback. We tested the adequacy of the methodology on a specific example: we conducted an analysis, an assessment, and proposed risk management measures in the field of ensuring road safety in a small town.

show abstract

Safety Assessment of Adjacent Roads Sections via Maximum Entropy Driver's Perception Field

Cited by 3 publications

References 16 publications

Ideology of Urban Road Transport Chaos and Accident Risk Management for Sustainable Transport Systems

Ideology of Urban Road Transport Chaos and Accident Risk Management for Sustainable Transport Systems

Naturalistic Driving Study: Methodological Aspects and Exemplary Analysis of a Long Roadwork Zone

Risk Management Methodology for Transport Infrastructure Security

Contact Info

Product

Resources

About