Regional Road Research Articles

Analysis of Urban Congestion Traceability: The Role of the Built Environment

Analyzing the factors influencing traffic congestion is essential for urban planning and coordinated development. Previous research frequently focuses on the internal aspects of traffic systems, often overlooking the impact of external factors on congestion sources. Therefore, this study utilizes a geospatial dataset and mobile signaling data, firstly applying the Fuzzy C-Means (FCM) algorithm to identify congested roads of different levels and trace the localization of travelers’ origins on regional congested roads. Furthermore, it employs the LightGBM method to study the influence of the built environment of various congestion sources on network-level congestion. The findings are as follows: (1) There is a positive correlation between traffic congestion and geographical location, with congestion predominantly caused by a few specific plots and demonstrating a concentrated trend in city centers. (2) Residential population density is the most critical factor, accounting for over 12% of the congestion contribution, followed by road density and working population density. (3) Both residential and working population densities show a non-linear positive correlation with congestion contribution, while the mixture of land use displays a non-linear V-shaped influence. Additionally, when residential population density is between 8000 and 11,000, it notably exacerbates congestion contribution. Significantly, by emphasizing land use considerations in traffic system analysis, these findings illuminate the intricate linkages between urban planning and traffic congestion, advocating for a more comprehensive approach to urban development strategies.

A Spatiotemporal Hierarchical Analysis Method for Urban Traffic Congestion Optimization Based on Calculation of Road Carrying Capacity in Spatial Grids

Traffic congestion is a globally widespread problem that causes significant economic losses, delays, and environmental impacts. Monitoring traffic conditions and analyzing congestion factors are the first, challenging steps in optimizing traffic congestion, one of the main causes of which is regional spatiotemporal imbalance. In this article, we propose an improved spatiotemporal hierarchical analysis method whose steps include calculating road carrying capacity based on geospatial data, extracting vehicle information from remote sensing images to reflect instantaneous traffic demand, and analyzing the spatiotemporal matching degree between roads and vehicles in theory and in practice. First, we defined and calculated the ratio of carrying capacity in a regional road network using a nine-cell-grid model composed of nested grids of different sizes. By the conservation law of flow, we determined unbalanced areas in the road network configuration using the ratio of the carrying capacity of the central cell to that of the nine grid cells. Then, we designed a spatiotemporal analysis method for traffic congestion using real-time traffic data as the dependent variables and five selected spatial indicators relative to the spatial grids as the independent variables. The proposed spatiotemporal analysis method was applied to Chengdu, a typical provincial capital city in China. The relationships among regional traffic, impact factors, and spatial heterogeneity were analyzed. The proposed method effectively integrates GIS, remote sensing, and deep learning technologies. It was further demonstrated that our method is reliable and effective and enhances the coordination of congested areas by virtue of a fast calculation speed and an efficient local balance adjustment.

A Hybrid Control Path Planning Architecture Based on Traffic Equilibrium Assignment for Emergency

Unconventional events exacerbate the imbalance between regional transportation demand and limited road network resources. Scientific and efficient path planning serves as the foundation for rapidly restoring equilibrium to the road network. In real large-scale road networks, especially during emergencies, it is usually difficult to obtain or predict accurate dynamic traffic network flows in real-time, which is used to support equilibrium path planning. Moreover, the traditional iterative methods cannot meet the real-time demand of emergency equilibrium path planning decision generation. To solve the above problems, this paper proposes a hybrid control architecture for path planning based on equilibrium traffic assignment theory. The architecture introduces the travelers’ real-time travel data and constructs a spatio-temporal neural network, which captures the evolution of traffic network loads. Adaptive multi-graph fusion technology is used to mix the background traffic flow data and the traveler’s real-time Origin–Destination (OD) data, to mine the dynamic correlation between the traffic state and the travelers’ travel. Based on the real-time prediction of dynamic network states, equilibrium mapping learning is carried out to pre-allocate potential travel demands and construct equilibrium traffic graphs based on system optimization traffic assignment. Finally, individual evacuation path strategies are generated online in a data-driven manner in real time to achieve improved resilience in the transportation system.

Comparative Analysis of Deterministic Fundamental Diagrams Representative of Continuous and Interrupted Traffic Flow on Selected Regional Road in Croatia

Since the inception of the traffic flow theory, numerous traffic flow models have been formulated by scholars in an effort to more accurately delineate the relationships between various traffic flow parameters. However, only a limited number of studies have explored the distinctions between fundamental traffic diagrams, which characterize continuous and interrupted traffic flow conditions. Addressing this research lacuna, we compared twelve “speed–density” and “flow–density” models fitted to empirical data collected under continuous and interrupted traffic flow conditions on a selected regional road in Croatia. The empirical data used to develop these models were extracted from video footage captured by an unmanned aerial vehicle on two representative road segments during characteristic peak and off-peak hours on workdays. Our analysis reveals that, depending on the selected traffic flow model and prevailing traffic flow conditions, the practical capacity of the observed regional road is estimated to be in the range from 799 to 2333 veh/h/lane. It was also discovered that the considered models reach practical capacity at a significantly different density under continuous and interrupted traffic stream conditions, i.e., between 37 and 129 veh/km/lane. The conducted t-tests underscore the need to employ distinct “speed–density” and “flow–density” regression functions for modeling continuous and interrupted traffic stream conditions.

Regional passenger motor transport systems: problem statement, first estimation results

Relevance. Passenger road transport in the 90s of the last century showed a high rate of transition to new management methods. The subsequent streamlining of activities progressed unevenly, mainly through regulation. However, important problems in the development of the industry, especially in the regions, have not been resolved. A crisis situation in intra-regional inter-municipal transportation and a high accident rate are the example. To a large extent, this situation is caused by the lag of the modern interpretation of the regional passenger road transport system from its real state, which does not allow achieving the greatest effect in the development of passenger road transport. The purpose of the work is to increase the importance of regular passenger transportation based on the substantiation of the importance of the structural parts of regional passenger motor transport systems, the developed methodology for assessing their condition, and creating development rules taking this into account.Materials and methods. General scientific methods of analysis and synthesis, system analysis, mathematical statistics, as well as the provisions of the theory of transport processes and systems are used in the work. Modern general scientific software products, open information resources about passenger vehicles in the regions were used.Results. The main scientific result of the article is the introduced concept of a regional passenger motor transport system. For a quantitative assessment of its condition, an indicator of the level of system self-organization has been developed, which is determined by the ratio of the number of cars to the number of buses, trolleybuses and trams in the region. The values of the indicators are in the range from 74 to 543 with an average value of 277. The dependencies of the influence of gross regional products and the number of population in the regions on the number of buses and cars in them are revealed. The practical significance lies in the development of tools for assessing the state of regional passenger transport systems. The directions for further research to determine the influence of structural parts on the level of self-organization of the system, building on this basis effective regional strategies for the development of passenger road transport are related.

Forecast of temporal variations in some road condition variables

The article considers issues of forecasting temporal variations in the condition of roads. The road condition is affected by external factors against the background of internal processes, occurring in construction layers. Most mathematical models, forecasting the service life of roads, are developed on the basis of strength characteristics, which, in conditions of limited financing of regional and local significance roads, leads to certain difficulties in their practical application. Therefore, it is necessary to develop a model of variations in the condition of road pavements based on data about their consumer properties, such as evenness, adhesion coefficient and pavement condition. The process of reducing the evenness values, pavement condition, and adhesion coefficient over time can be described using the Weibull distribution. The paper presents mathematical models of temporal variations in the condition of the road pavement, adhesion coefficient and longitudinal evenness. The data of the model and annual road diagnostics, compared for assessing the model effectiveness, demonstrated high convergence. The proposed approach to assessing the variations in the pavement condition, evenness and adhesion coefficient makes it possible to increase the efficiency of managing the road condition.

Proposal of a GIS and BIM based structured database for bridge management digitalization

Structured databases are an established and widely used tool in all areas of work to properly store and manage information in daily work. In the search for methods to digitize the existing heritage most effectively, it was found that a good organization of the information in a digital archive combined with a structured database facilitates the transition to more innovative tools such as Geographical Information System (GIS) and even more Building Information Modeling (BIM). The role of structured databases in digitizing information with innovative tools such as GIS or BIM is to accelerate the digitization of existing extensive heritage. Structured databases are widespread and, in the last years, they have been increasingly included by much of the management world. In the context of infrastructures and road operators, information is often rarely collected in structured databases, but this is an opportunity in the context of applying the proposed research and methodology, as it is versatile, widespread, and influential. Therefore, this research highlights how a structured database can be a good starting point for defining a more modern BIM model. Starting from a limited amount of information on specific elements, it is possible to digitize, georeference and create BIM models of a large number of objects. In this paper, the digitalization process of the data concerning bridges of the regional road network is highlighted and the relative advantages are shown. In particular, a database, developed within the MLAZIO project, has been designed to collect information on about 400 bridges in the Lazio region. The whole information contained in this database allows on one side to visualize all the data in a geo-referenced system (GIS), on the other side the automatic realization of BIM models of the bridges.

An Analysis of the Perspective Road Design Scheme Around Zhangzhou Olympic Sports Center

City events take place in the Zhangzhou Olympic Sports Center, resulting in traffic. Hence, this study analyzed the road planning and design around Zhangzhou Olympic Sports Center through traffic demand forecasting. The simulated data and road plan underwent macro prediction model technology and numerical simulation technology through Emme and TransCAD. The regional road network structure, traffic demand forecast, plane, longitudinal section, and cross-sectional program selection were investigated to determine a reasonable design program. While urban development programs were implemented, the study ensured an increase in the city's economic growth alongside the guaranteed value of citizens’ welfare.

China's One Belt One Road (OBOR) Initiative and Its Ambitions for Global Hegemony

This research paper analyses China's One Belt, One Road initiative and explores its ambitions for influencing the world economy through these economic corridors. However, each economic corridor has been separately explained in order to understand how these economic corridors would contribute to the rise and expansion of China in the world. In addition, to know whether the One Belt and One Road Initiative offers these six corridors' member states an opportunity to create a win-win relationship with China. It will ensure access and increase trade volume to the major world markets, or is it still a pipe dream for these countries to obtain such goals and objectives? Apart from this, to find out how it would improve and enhance regional connectivity, people-to-people contact, economic development, transit trade, road and maritime transport networks and tourism. This study used the qualitative method with an interpretive and descriptive approach. The purposive sampling technique was used to select the participants for the interview, and the snowball sampling technique was used to approach the participants. Five participants were interviewed through an interview schedule. The interview schedule was emailed to participants, and they typed their responses on MS Word and sent them back to the researcher. The researcher developed themes, and data were analyzed according to those themes. The findings of the study suggested that China has initiated these projects to promote its political power and economic interests in the region.

Потенциал применения зарубежного подхода при создании транспортно-логистической инфраструктуры

Changing the approach to the integrated development of the territories of the regions of Russia requires the development of conceptual approaches to the organization of logistics of road construction. It is noted that currently in Russia, key projects for the development of the country and society are implemented by achieving the goals and objectives of national strategies (national projects 2019-2024), in three areas - human capital, a comfortable living environment, economic growth. As a result of the low efficiency of the management mechanisms for the implementation of the tasks of the national strategy “Safe and High-quality Highways”, new projects for the development of small towns require complex solutions of contractors for the construction of logistics infrastructure. The projects of organization of construction and improvement of road transport infrastructure of foreign countries are considered. The analysis of road construction management models in China and India was carried out in order to determine the potential of applying a foreign approach to the creation of transport and logistics infrastructure in Russia within the framework of national strategies for the integrated development of the country's territory. The main obstacles to the realization of the Russian potential for economic growth and their causes are identified. Conclusions are drawn that in order to create a comfortable and efficient transport and logistics infrastructure in the region, it is advisable to expand the target regional road construction markets and apply a project approach with the choice of a road construction logistics operator.

Developing a probability-based technique to improve the measurement of landslide vulnerability on regional roads

Considering the uncertainty in vulnerability curves, this study employs a probabilistic technique to improve the current landslide vulnerability on roads. The uncertainty in current vulnerability was first elaborated, and slope failure and the damage caused to roads were investigated. To minimize uncertainty, subsequently, the probabilistic landslide intensity was proposed, and hired to calibrate the empirical landslide intensity. Finally, an improved vulnerability curve was developed and compared with the empirical vulnerability, in terms of the fluctuation band and residual value. Results show that the uncertainty of the improved vulnerability is significantly reduced compared with the empirical vulnerability model. In detail, the uncertainty reduction in landslide vulnerability is reflected not only in the decrease of the residual range, from 0.6 to 0.3, but in the narrowing of the fluctuation band. It provides a route for enhancing the accuracy of landslide vulnerability from a probabilistic view.

Partially observable Markov decision process for perimeter control based on a stochastic macroscopic fundamental diagram

The use of a macroscopic fundamental diagram (MFD) for perimeter control is an effective strategy for managing traffic flow on regional road networks. However, existing methods either assume a MFD with low scattering or assume complete availability of information, which is not realistic. In order to address these limitations, we propose a novel approach that incorporates a stochastic evolution dynamic into the MFD and introduces a partially observable Markov decision process for perimeter control. Our approach assumes that the MFD is randomly distributed between upper and lower boundaries, characterized by a physically interpretable parameter, and that real-time observations represent cumulative data in specific regions. We focus on three sub-objectives: minimizing travel time, minimizing capacity loss due to hysteresis, and preventing gridlock. By utilizing the Bellman equation, we solve the problem and demonstrate that our proposed control method enhances trip completion rates by 7.2% compared to the benchmark case without perimeter control. Furthermore, the inclusion of stochasticity leads to an additional 1.2% improvement in trip completion rates. Through extensive numerical tests, we establish the effectiveness of our approach in optimizing traffic flow regulation on regional road networks.

Kampanye Stop Melawan Arus Kendaraan Melalui Media Game Telepon Cerdas

Traffic violation against the flow on Jl. Cihaliwung to Jl. Raya Purwakarta is very difficult to stop, even though raids are often held by the police, violations still continue to this day. Long one-way traffic forces motorists to demand efficiency for shorter travel times, so they are willing to go against the flow of the road. The large number of regional roads that are not touched by the police is also the reason for many motorists not meeting the correct driving equipment. This traffic problem which has not been resolved for more than 10 years needs to be stopped, bearing in mind that the road is often passed by large trucks and often causes traffic accidents. The suggested design solution is a traffic police simulation game, in which there is a story that contains campaign messages, a police ticketing game that can provide a police experience to players that shows how stubborn motorists are violating, and the results of the police ticketing game are also campaign messages. It is hoped that this design can make people understand the importance of obeying traffic rules, especially for teenagers and early adults.

Accounting for the topology of road networks to better explain human‐mediated dispersal in terrestrial landscapes

Human trade and movements are central to biological invasions worldwide. Human activities not only transport species across biogeographical barriers, but also accelerate their post‐introduction spread in the landscape. Thus, by constraining human movements, the spatial structure of road networks might greatly affect the regional spread of invasive species. However, few invasion models have accounted for the topology of road networks so far, and its importance for explaining the regional distribution of invasive species remains mostly unexplored. To address this issue, we developed a spatially explicit and mechanistic human‐mediated dispersal model that accounts and tests for the influence of transport networks on the regional spread of invasive species. Using as a model the spread of the invasive ant Lasius neglectus in the middle Rhône valley (France), we show that accounting for the topology of road networks improves our ability to explain the current distribution of the invasive ant. In contrast, we found that using human population density as a proxy for the frequency of transport events decreases models' performance and might thus not be as appropriate as previously thought. Finally, by differentiating road networks into sub‐networks, we show that national and regional roads are more important than smaller roads for explaining spread patterns. Overall, our results demonstrate that the topology of transport networks can strongly bias regional invasion patterns and highlight the importance of better incorporating it into future invasion models. The mechanistic modelling approach developed in this study should help invasion scientists explore how human‐mediated dispersal and topography shape invasion dynamics in landscapes. Ultimately, our approach could be combined with demographic, natural dispersal and environmental suitability models to refine spread scenarios and improve invasive species monitoring and management at regional to national scales.Keywords: biological invasions, human‐mediated dispersal, road network, secondary spread, spatially explicit model, stochastic jump model

Prediction of transportation index for urban patterns in small and medium-sized Indian cities using hybrid RidgeGAN model

The rapid urbanization trend in most developing countries including India is creating a plethora of civic concerns such as loss of green space, degradation of environmental health, scarcity of clean water, rise in air pollution, and exacerbated traffic congestion resulting in significant delays in vehicular transportation. To address the intricate nature of transportation issues, many researchers and planners have analyzed the complexities of urban and regional road systems using transportation models by employing transportation indices such as road length, network density, accessibility, and connectivity metrics. This study addresses the complexities of predicting road network density for small and medium-sized Indian cities that come under the Integrated Development of Small and Medium Towns (IDSMT) project at a national level. A hybrid framework based on Kernel Ridge Regression (KRR) and the CityGAN model is introduced to predict network density using spatial indicators of human settlements. The major goal of this study is to generate hyper-realistic urban patterns of small and medium-sized Indian cities using an unsupervised CityGAN model and to study the causal relationship between human settlement indices (HSIs) and transportation index (network density) using supervised KRR for the real cities. The synthetic urban universes mimic Indian urban patterns and evaluating their landscape structures through the settlement indices can aid in comprehending urban landscape, thereby enhancing sustainable urban planning. We analyzed 503 real cities to find the actual relationship between the urban settlements and their road density. The nonlinear KRR model may help urban planners in deriving the network density for GAN-generated futuristic urban patterns through the settlement indicators. The proposed hybrid process, termed as RidgeGAN model, can gauge the sustainability of urban sprawl tied to infrastructure and transportation systems in sprawling cities. Analysis results clearly demonstrate the utility of RidgeGAN in predicting network density for different kinds of human settlements, particularly for small and medium Indian cities. By predicting future urban patterns, this study can help in the creation of more livable and sustainable areas, particularly by improving transportation infrastructure in developing cities.

Assessing regional road traffic safety in Sweden through dynamic panel data analysis: Influence of the planned innovative policies and the unplanned COVID-19 pandemic

Efficient transport infrastructures are crucial to improve traffic safety and reduce negative effects of human activities, where effective transport policies play a vital role. It is also important to evaluate the effects of the policies to document and update them with time. The purpose of this study is to examine road traffic crashes with fatalities and severe injuries at the county level in Sweden, considering both planned innovative policies and the unexpected influence of the COVID-19 pandemic. Data on road traffic crashes with fatalities and severe injuries from 2010 to 2021 in twenty-one counties in Sweden were collected, as well as road network data, vehicle registration data, land use data and socio-demographic data. Negative binomial autoregressive models with region fixed effect were proposed to estimate the effects of explanatory variables on crash frequency, along with Generalized Method of Moments (GMM) models. The findings demonstrate that the speed limit changes and the introduction of safety cameras in Sweden is effective in reducing fatalities and severe injuries. Importantly, different regions exhibit distinct responses to these interventions, with varying effects on different types of crashes. Additionally, findings show that other factors, such as land use characteristics, presence of trucks, and population density also influence the crash frequencies. Moreover, the effect of the COVID-19 pandemic was investigated, which shows a reduction in traffic crashes during the pandemic period. Important policy implications based on the findings are discussed to enhance transport safety and resilience. By considering regional variations, this study provides insights into the spatial dynamics of road safety patterns, and supports the Vision Zero policy in Sweden.

Evaluation of Regional Road Transport Safety Service Level With Edge Computing in Scalable Sensor and Actuator Networks

In contemporary society, road transport has assumed a pivotal role in the daily lives of individuals, with virtually everyone being a road user in one capacity or another. Unfortunately, a significant portion of road accidents stem from user negligence and a lack of awareness regarding road safety principles and regulations. The majority of these accidents are fundamentally a result of human errors, errors that could potentially be averted through the comprehensive utilization of technology. The integration of edge computing within actuator networks, combined with the scalability of sensors, holds the potential to proactively detect and prevent impending collisions. This cutting-edge approach not only accumulates and processes sensor-generated data but also employs it to mitigate the occurrence of road accidents. This discussion delves into the potential advantages offered by smart sensors and advanced technology, focusing on the enhancement of safety within transportation networks. The core attributes of these intelligent technologies facilitate the establishment of robust connectivity and the effective implementation of processes, ushering in an innovative era in the realm of road safety through smart technology.

Measurement of Efficiency for Regional Road Inconvenience Complaint Reporting System using DEA

Measurement of Efficiency for Regional Road Inconvenience Complaint Reporting System using DEA

Historical architectural and town-planning centers in the ethnic culture of Ukraine

The article considers the features of the location of small historical settlements - carriers of the architectural and urban culture in 12 ethnic regions of Ukraine. Among them: Bukovyna, Volyn, Halychyna, Donbas, Zakarpattia, Crimea, Podillia, Polissia, Naddnipryanshchyna, Sivershchyna, Slobozhanshchyna, Tavria. For the analysis, an original method was used to identify the areas of historical settlements and the formation of the corresponding 57 polygons. The areas that form the centers of regional culture are identified according to the principle of territorial proximity of settlements, taking into account the tracing of communication routes between them. Accordingly, the polygons are formed from small towns with historical monuments of architectural and town-planning art, which are connected to each other along the perimeter in the shortest possible way by regional and local roads. For example, on the territory of Bukovyna there are 10 villages, small towns, settlements, castles and monasteries, which form 2 polygons around Chernivtsi: the western (Kitsman, Vyzhnytsia, Storozhynets) and the eastern (Khotyn, Novoselytsia, Banchaky, Boyany, Molodiy). As a result, groups of small provincial cities and towns, towns and villages, temples and monasteries were formed with signs of a historical architectural environment. In each ethnic region, a different number of such groups have been formed, which form the corresponding number of polygons: Bukovyna – 2, Volhynia – 4, Galicia – 6, Donbas – 4, Transcarpathia – 2, Crimea – 3, Podillia – 5, Polissia – 8, Naddnipryanshchyna – 6, Severshchyna – 6, Slobozhanshchyna – 4, Tavria – 6. The identified groups of historical architectural and urban centers require further thorough study. The results of these studies can be used to develop a concept for the restoration and further sustainable development of the historical settlements of Ukraine.

From slope seismic resilience to regional road network resilience: an integrated framework for evaluating the seismic resilience of mountainous road networks

A systematic review was conducted, ranging from the seismic resilience of single slope engineering structures as disaster-bearing bodies to their transformation into disaster-inducing bodies owing to seismic dynamic instability. The resilience of slopes is considered with regard to regional transportation networks, which are most severely threatened by earthquake-induced landslide disasters. For the engineering structure of a single slope as a disaster-bearing body, the stage before the slope engineering loses stability can be considered as the first stage of slope seismic resilience evaluation. This review summarizes the latest progress in seismic resilience evaluation and reinforcement design from the perspective of engineering seismic resilience. In response to the lack of definition for the resilience of existing regional road networks to earthquake-induced landslide impacts during the review, the second stage involves the transformation of the seismic dynamic instability of regional slopes into landslide disasters; resilience is defined as the global system reliability of the regional road network in this study. From the perspective of network reliability, an assessment framework for the resilience of the regional transportation network against seismic landslide disasters is systematically proposed in this study. In accordance with high-dimensional nonlinear network dynamics theory, this paper highlights the future research direction of introducing high-dimensional network dynamics theory into the disaster resilience of regional road networks affected by landslide disasters.