State Of Road Network Research Articles

Indirect Measurements of Bridge Vibrations as an Experimental Tool Supporting Periodic Inspections

Recent collapses and malfunctions of European bridges threatened the service conditions of road networks and pointed out the need for robust procedures to mitigate the impact of material degradation and overloading of existing bridges. Condition assessment of bridges remains a challenging task, which could take advantage of cost-effective and reliable inspection strategies. The advances in sensors as well as Information and Communication Technologies (ICT) ensure a significant enhancement of the capabilities in recording and processing physical and mechanical data. The present paper focuses on the paradigm of indirect vibration measurements for modal parameter identification in operational conditions. It is very attractive because of the related opportunities of application of dynamic tests as a tool for periodic inspections while significantly mitigating their impact on the traffic flow. In this framework the instrumented vehicle acts as a dynamic measurement device for periodic inspections and provides valuable information on the structural response of the bridge at a low-cost. Vehicle-bridge interaction models are here applied to realistically simulate the traffic-induced vibration response of bridges and assess the accuracy of modal parameter estimates obtained from indirect vibration measurements characterized by different noise levels.

An Integrated Reinforcement Learning and Centralized Programming Approach for Online Taxi Dispatching.

Balancing the supply and demand for ride-sourcing companies is a challenging issue, especially with real-time requests and stochastic traffic conditions of large-scale congested road networks. To tackle this challenge, this article proposes a robust and scalable approach that integrates reinforcement learning (RL) and a centralized programming (CP) structure to promote real-time taxi operations. Both real-time order matching decisions and vehicle relocation decisions at the microscopic network scale are integrated within a Markov decision process framework. The RL component learns the decomposed state-value function, which represents the taxi drivers' experience, the off-line historical demand pattern, and the traffic network congestion. The CP component plans nonmyopic decisions for drivers collectively under the prescribed system constraints to explicitly realize cooperation. Furthermore, to circumvent sparse reward and sample imbalance problems over the microscopic road network, this article proposed a temporal-difference learning algorithm with prioritized gradient descent and adaptive exploration techniques. A simulator is built and trained with the Manhattan road network and New York City yellow taxi data to simulate the real-time vehicle dispatching environment. Both centralized and decentralized taxi dispatching policies are examined with the simulator. This case study shows that the proposed approach can further improve taxi drivers' profits while reducing customers' waiting times compared to several existing vehicle dispatching algorithms.

The Architecture and Development of Intelligent Traffic Signal Control Platform

The project used intelligent video analysis, traffic big data information processing and analysis technology to accurately grasp the traffic demand of urban traffic. The platform developed by this project could be combined with the vehicle level to adjust and optimize the traffic signal timing scheme in real time, which could improve road utilization of cities. This platform could use the big data analysis technology to predict future traffic situation based on historical traffic conditions and develop a best timing plan in advance. Under the existing road network conditions, the basis of this project was to rationally organize and plan traffic flow, improve road traffic management facilities, and strengthen and enhance the modern traffic awareness of traffic participants. The goal of the platform was to provide order, smooth, safe and traffic management services, it also aims at rapid response, and decision-making in the field of intelligent transportation.

Research on Layout Network Optimization of Public Charging Infrastructure

With the gradual popularity of new energy vehicles in the world, people’s demands for the construction of supporting services such as charging infrastructure are becoming increasingly urgent. The popularity of charging infrastructure also determines the upper limit of the future development of new energy vehicles. This paper starts from the research on user satisfaction of charging infrastructure, finds the key indicator that affects user satisfaction-the layout network of charging stations, establishes a multi-path trajectory node model to quantitatively solve the problem of charging station layout under complex road network conditions, and calculates Example simulations verify the feasibility of the model method.

Important risk factors for road accidents

This article analyzes the relationship and influence of factors such as the population, the level of motorization, economic development, and the state of the state road network on the state of the risk of road accidents, including the level of mortality and road injuries, as well as the relevance of improving methods for assessing, managing and predicting the risk of accidents in road traffic. National indicators of the level of road deaths and injuries in different countries were studied. The relationship between road accidents and the level of motorization, income of the population, the state of the road network, and other indicators were revealed. The urgency of the problem of road accidents and the organization of measures to reduce the level of road accidents is emphasized. It also takes into account the special importance of forming conceptually new approaches to the task of improving the efficiency of public administration in the field of organization and maintenance of road traffic through the implementation of the Concept of Road Safety in the Republic of Uzbekistan for the period 2018-2022, which includes the following main directions: further improvement of the regulatory framework in the field of road safety, including significant strengthening of responsibility for gross violations of traffic rules; comprehensive improvement of road infrastructure, improving the quality of roads, creating reliable conditions for the safe movement of vehicles; improving the legal culture, the necessary knowledge, and skills of road users, strengthening their discipline.

Performance assessment of the state of road infrastructure in selected urban centers in Kogi State in Nigeria

Road infrastructure has been identified as a major factor in the development of a nation and where is lacking or inadequate usually creates a memorable hardship for road users. To this end, this study assessed the state of road infrastructure in selected urban centres in Kogi State, Nigeria. Structured questionnaire cum field observation were deployed to collect the required data for the study. The structure questionnaire were administered to one thousand, two hundred and fifteen (1,215) household heads in the selected urban centres to elicit information on the perception of the urban dwellers with the state of road infrastructure. More importantly, Z-Score technique was utilized to show variation in the distribution of road infrastructure in the selected urban centres in Kogi State. Findings revealed that disparity exists in the provision of road infrastructure across the selected urban centres in the study area with the highest Z-Score value of 3.85 in Lokoja and a least Z-Score value of -0.28 in Mopa-Amuro. Findings also indicated that that the respondents (urban dwellers) were dissatisfied with the condition of road network and fairly satisfied with the state of bridge and drainage system, lay-by and walk way, street light, traffic/road sign and parking spaces available in the study area. Having revealed the level of satisfaction of respondents with the physical state of existing road infrastructures and their serviceability, the study recommends that Kogi State government should made concerted efforts to develop and implement standard road infrastructure capacity framework for road construction, rehabilitation and maintenance across the urban centres in Kogi State.

Research on Road Traffic Network Design Model and Algorithm Considering Traffic Fairness

Urban transportation is an important part of urban economic structure, which plays an important role in promoting the orderly development of society, residents' work and life. This paper analyzes the fairness in traffic network design problem, constructs the average network improvement index to measure fairness, and establishes a bi-level programming model for road traffic network design considering traffic fairness. The upper model includes the optimal total travel time and traffic fairness, and the lower model is the traffic flow allocation model. Then, according to the characteristics of the model, a genetic algorithm is designed to solve the model. Finally, a simple example is given to illustrate the effectiveness of the mathematical model and algorithm. The model proposed in this paper can get the final road design scheme satisfying the total travel time and traffic fairness of the road network under certain road network conditions, and can provide decision support for traffic planners.

Состояние сети автомобильных дорог регионального и местного значения Байкальского региона

The purpose of the paper is to study the condition of the Baikal region road network. Statistical data on the development level of road networks, as well as the regulatory and technical legal documents governing the road industry in Russia and in the Baikal Region, we reanalysed. Firstly, the Baikal Region, as well as the Russian Federation as a whole, lags far behind most developed countries in terms of the development of road networks. Secondly, the road network in the Baikal Region has a very low density in the northern parts and a relatively high density in the southern parts, which are more developed and populated. Thirdly, the actual condition of the roads significantly differs from the regulatory and engineering requirements. Fourthly, the final cost of the product is twice as high as in developed countries. This is due to the low level of quality and development of the road network, as well as the high transport expenses. Moreover, the low quality of the roads has a direct impact on the number of accidents. It can be concluded that an effective mechanism for the modernization of the road industry in the Baikal region has not been developed. The existing regulatory framework and the deadlines set by various development programs do not accomplish the development indicators of regional and local road networks. It is essential that approaches to road capital repair and maintenance of regional and local roads should be modified. A repair of a whole stretch of a road should replace the traditional approach of repairing individual small sections of a road and its structures. To this end, theoretical and methodological provisions and practical guidelines for developing road networks in the Baikal region should be established.

Geohazard vulnerability and condition assessment of the Asian highway AH-48 in Bhutan

Transport networks are frequently exposed to geohazards, and losses can be observed frequently by notable disaster incidents such as landslides, earthquakes, and floods. Although losses due to natural disasters are frequently reported, limited attention is paid to assess the condition of strategic road networks in the Himalayas. Thus, to fulfill this gap, this study performs condition assessment of Asian Highway AH-48 in Bhutan and develops a system to rate the performance level of road assets. The assessment is conducted along a 157.6 km stretch of AH-48. The sum of findings highlights that about 55% of the road assets along the AH-48 are highly vulnerable to geohazards. Drains are observed to be the most vulnerable, with 52% drains lying below the standard rating among the considered assets followed by retaining walls and pavement. Landslide vulnerability function for highways that are situated in mountain regions is developed using the newly proposed landslide intensity scale. The sum of findings highlights that the Himalayan roads will be affected mostly by landslides and the drainage system is the most affected road asset showing the least serviceability among the common road assets.

Modeling risks of functional degradation in the road network of Russian northern cities due to predictable climatic changes

Predictable climate warming naturally leads to excessive thawing of permafrost soils and damage to the road network built on them. Using methods of mathematical modeling, we quantitatively estimated the additional risk associated with an increase in the mean annual air temperature by up to 2°C for the largest Russian northern cities (Murmansk, Norilsk, and Yakutsk). The current climate condition that serves as the basis for the design of roads was determined with account for long-term data of instrumental observations. The depth of additional soil thawing in the road base and its settlement in changing climatic conditions were calculated in accordance with existing design standards. The basic risk level corresponding to the maximum permissible settlements was conventionally adopted as 100%. The settlement of the road pavement was calculated for two cases: for undamaged fragments of the road network and with account for the initial settlement in them. The second case reflects the road network condition in the cities under consideration more realistically. With regard to it, we got significantly higher estimates of the predicted risk — up to 307% at an increase in temperature by 2°C (while in the first case, they were up to 78%). The paper shows that saturated soils in the road base are associated with aggravated risk of settlements in the road pavement. As for clayey soils, the potential excess of the basic risk level was recorded at an increase in air temperature by 1°C, and for sandy soils — by 1.5°C. We show a clear relationship between the predicted risk level and climatic and soil features of the territory.

Measuring rural access for SDG 9.1.1

AbstractThe Rural Access Index is a measure of access developed by the World Bank and has been incorporated into the Sustainable Development Goals (SDGs) as indicator 9.1.1. This measures the proportion of the rural population living within 2 km of an all‐season road, using GIS layers and relying on three data sources: population, road network location and condition. Open GIS data are used for population and road location, but there are challenges to define the all‐season status of roads. Every country measures road condition differently and against different parameters, which makes consistency of the all‐season status between countries difficult. This article reports on research to refine the GIS methodology for assessing SDG 9.1.1 to make it more sustainable, repeatable and consistent by using geospatial data and tools, based on trials in four countries—Ghana, Malawi, Myanmar and Nepal—which were selected for their diversity of environment and data.

Internet of people enabled framework for evaluating performance loss and resilience of urban critical infrastructures

Critical infrastructures (CIs) such as road networks play a critical role in transporting affected people to hospitals and shelters during disasters. Timely evaluation of road networks’ performance loss and resilience enables emergency management agencies (EMAs) to make quick and optimized decisions on resource allocation to critical road segments and bridges. However, real-time monitoring of road network conditions has been recognized as a challenge during major natural disasters because the affected regions are often inaccessible. This research introduces the Internet of People (IoP) enabled framework to assess road network’s performance loss during disasters and proposes a performance loss rate to evaluate the road network resilience. The framework is illustrated by a case study of Hurricane Florence in Wilmington, North Caroline, USA. Through semantic analysis of road-related social media data, this study identifies the affected roads during the hurricane. To further evaluate the road network resilience, this research utilizes road network analysis to generate a service zone for each main hospital before and after the hurricane. The population-weighted travel time in each service zone are compared before and after the hurricane to indicate the degree of performance loss. The findings show that our IoP enabled framework can effectively support CI protection for building smart and resilient city environments.

The Traffic Congestion Analysis Using Traffic Congestion Index and Artificial Neural Network in Main Streets of Electronic City (Case Study: Hamedan City)

Traffic is a major challenge for electronic cities and coping with it requires analyzing traffic congestion in the city road network. In this paper, the performance index of vehicle speed was estimated to evaluate the conditions of road networks. This study analyzes the traffic density for the main network of Hamedan communication routes based on the collected data of Speed performance of Hamedan traffic control system. According to this analysis, the congestion index and traffic peak hours were determined. Also the relationship between vehicle speed and traffic congestion was predictably predictable by neural network and the genetic algorithm. In this study areas of traffic were identified using Hamedan traffic control center due to the speed of vehicles.

Safety Audit of Construction Drawing Design of the NR3 Highway Reconstruction & Expansion Project and Traffic Safety Developing Suggestion in Cambodia

The highway safety audit is a means to improve the safety level and service ability of highway. Based on the safety audit of Cambodian highway in the construction drawing design and the investigation on the local road network conditions, the countermeasures for improving the road traffic safety and the suggestions for the future development of road traffic safety are put forward.

Prediction of the road pavement condition index using stochastic models

Mathematical models for prediction of road network condition based on the so-called Markov chains are presented in this article. The data for calculation of elements of the transition matrix from one condition to another are taken from visual evaluation as well as from instrumental reading. It is recommended to prepare data sets in the form of pavement management system data tables based on a representative sample of measuring sections. Discrete time intervals – of one year – are used when constructing the model of transition matrices. The procedure of forming Markov transition matrix with partially complete data sets is proposed also in paper. The basis of this procedure is information on the previous condition of the structure and the results of the instrumental evaluation, which enables correction of the predicted values. The final matrix takes into account not only the probability, but also the speed of transition from one condition to another. It is also possible to work with the initial data using appropriate databases or other software.

Spatially differentiated profiles for road traffic noise pollution across a state road network

Diverse traffic noise profiles across road networks remain largely undifferentiated using standardised noise indicators. To address this issue, this work derives two supplementary noise indicators for road traffic noise. The first supplementary indicator differentiates the impacts of daytime and night-time noise exposure. The second supplementary indicator differentiates heavy vehicle noise from commuter traffic noise. Both indicators are expressed in terms of hourly contributions of light and heavy vehicle noise associated with standard traffic noise indicators. The Spearman’s rank correlation coefficient is used to evaluate the strength of the relationship between the standard and supplementary noise indicators. Using the supplementary noise indicators, spatial variability of light and heavy vehicle traffic composition across urban and rural parts of a state road network in Australia is presented. The findings add a useful spatial dimension to large scale road traffic noise impact studies to better inform epidemiology and noise management action plans.

A Spatial Heterogeneity-Based Segmentation Model for Analyzing Road Deterioration Network Data in Multi-Scale Infrastructure Systems

Road network conditions and road quality are directly linked with the performance of an entire infrastructure system. As sensor monitoring of road deteriorations has rapidly increased, road infrastructure performance can now be assessed using multiple measures. However, more effective and accurate quantitative analysis methods are increasingly required. This research explores road infrastructure performance using road deterioration network data in the Mid West Gascoyne region, Australia. A spatial heterogeneity-based segmentation (SHS) model is developed for redefining road segments across the network in terms of sensor monitoring data, and for both project-level and network-level infrastructure systems management. To evaluate the model effectiveness and accuracy, an evaluation system is proposed from four aspects: segment number, homogeneity within segments, heterogeneity among segments, and segment morphology. The SHS model is compared with two widely used road network segmentation methods. The results show that the SHS model can use fewer segments to ensure higher homogeneity within segments and heterogeneity among segments across the network. Meanwhile, the segment lengths are more uniformly distributed as compared with results from other methods. The developed model and findings from this research can significantly improve the utilization of sensor monitoring network data and support multi-scale infrastructure systems management.

METHODOLOGY OF OPTIMIZATION OF CONSTRUCTION INDUSTRY UNDER DENSE DEVELOPMENT CONDITIONS

Purpose . The research of theoretical and methodological foundations of development and functioning of the construction industry in the context of using the tool of logistics and systems engineering as a modern basis for solving organizational and technological problems within the dense urban development conditions and significant factors of the functional and planning infrastructure of Ukrainian cities. Methodology. An important role in the organization of construction industry plays the ability to apply modern methods and mechanisms of construction logistics and systems engineering. In the modern conditions of development and functioning of the construction industry there is a need to apply innovative methods of management and organization of building processes in the conditions of dense urban development. In these conditions, the application of the concept of logistics in construction becomes especially relevant within the functional and planning infrastructure of Ukrainian cities. Findings. The analysis of the current state of the organization of construction in a dense urban development conditions within the functional and planning infrastructure of Ukrainian cities, which is clearly make the need for the use of tools based on the basis of knowledge of «logistics» and «systems engineering», that significantly improves the organizational processes of construction industry. Applying the principles and corresponding concepts of logistics, it will allow to form a system of views on the improvement of the processes of organization of construction industry within the dense urban development conditions, significant factors of functional and planning infrastructure of Ukrainian cities and the state of road network, through optimal flow-resource management. All of this will effectively raise the development of the construction industry at EU level. Originality. Theoretical and methodological directions on the basis of the tool of logistics and systems engineering, as a modern innovation basis for solving organizational and technological problems of construction industry within the dense urban development conditions and significant factors of functional and planning infrastructure of Ukrainian cities are formed. Practical value. The use of modern scientific and methodological tools based on the knowledge in the field of «logistics», that gives the opportunity to form a mechanism for choosing rational management decisions aimed at solving of organizational and technological problems of construction industry within the dense urban development conditions and significant factors of functional and infrastructure.

Network analysis of regional livestock trade in West Africa.

In West Africa, long and complex livestock value chains connect producers mostly in the Sahel with consumption basins in urban areas and the coast. Regional livestock trade is highly informal and, despite recent efforts to understand animal movement patterns in the region, remains largely unrecorded. Using CILSS' database on intraregional livestock trade, we built yearly and overall weighted networks of animal movements between markets. We mapped and characterized the trade networks, identified market communities, key markets and their roles. Additionally, we compared the observed network properties with null-model generated ensembles. Most movements corresponded to cattle, were made by vehicle, and originated in Burkina Faso. We found that live animals in the central and eastern trade basins flow through well-defined, long distance trade corridors where markets tend to trade in a disassortive way with others in their proximity. Modularity-based communities indicated that both national and cross-border trade groups exist. The network's degree and link distributions followed a log-normal or a power-law distribution, and key markets located primarily in urban centers and near borders serve as hubs that give peripheral markets access to the regional network. The null model ensembles could not reproduce the observed higher-level properties, particularly the propinquity and highly negative assortativity, suggesting that other possibly spatial factors shape the structure of regional live animal trade. Our findings support eliminating cross-border impediments and improving the condition of the regional road network, which limit intraregional trade of and contribute to the high prices of food products in West Africa. Although with limitations, our study sheds light on the abstruse structure of regional livestock trade, and the role of trade communities and markets in West Africa.

Impact assessment of short-term management measures on travel demand

Travel Demand Management (TDM) can be considered as the most viable option to manage the increasing traffic demand by controlling excessive usage of personalized vehicles. TDM provides expanded options to manage existing travel demand by redistributing the demand rather than increasing the supply. To analyze the impact of TDM measures, the existing travel demand of the area should be identified. In order to get quantitative information on the travel demand and the performance of different alternatives or choices of the available transportation system, travel demand model has to be developed. This concept is more useful in developing countries like India, which have limited resources and increasing demands. Transport related issues such as congestion, low service levels and lack of efficient public transportation compels commuters to shift their travel modes to private transport, resulting in unbalanced modal splits. The present study explores the potential to implement travel demand management measures at Kazhakoottam, an IT business hub cum residential area of Thiruvananthapuram city, a medium sized city in India. Travel demand growth at Kazhakoottam is a matter of concern because the traffic is highly concentrated in this area and facility expansion costs are pretty high. A sequential four-stage travel demand model was developed based on a total of 1416 individual household questionnaire responses using the macro simulation software CUBE. Trip generation models were developed using linear regression and mode split was modelled as multinomial logit model in SPSS. The base year traffic flows were estimated and validated with field data. The developed model was then used for improving the road network conditions by suggesting short-term TDM measures. Three TDM scenarios viz; integrating public transit system with feeder mode, carpooling and reducing the distance of bus stops from zone centroids were analysed. The results indicated an increase in public transit ridership and considerable modal shift from private to public/shared transit.