Interurban Road Research Articles

Risk-taking behavior in birds foraging along interurban roads

Risk-taking behavior in birds foraging along interurban roads

Contribution of Network Redundancy to Reducing Criticality of Road Links

Road networks are frequently disrupted by natural hazard events, producing severe consequences for isolated communities as well as increased travel times and significant reconstruction costs. Therefore, identifying which critical links need investment to reduce network impacts has become a priority for road agencies. Road network redundancy contributes to reducing these potential consequences by providing viable alternative routes. Although several metrics have been proposed in the literature to evaluate road criticality, including those based on topological variables and transportation cost increases, a comparison of the contribution of redundancy to reducing expected consequences has not been undertaken using a range of different metrics. This paper proposes a methodology to evaluate road criticality under different metrics and to quantify the contribution of redundancy in reducing expected impacts using the “full scan” method and Monte Carlo simulation. This methodology is then applied to a case study of New Zealand’s South Island to quantify the contribution of secondary and tertiary inter-urban roads to overall network redundancy, and to determine the most critical links under different approaches. The results obtained from the case study demonstrate that the redundancy level provided by secondary and tertiary inter-urban roads, over and above the state highway network, decreases expected transportation cost increases by 94.93% on average, and improves topological metrics, such as network betweenness values, by 73% on average when the road network is disrupted. The proposed methodology has the potential to help decision makers quantify and, therefore, prioritize investments to reduce the consequences of network disruptions.

Examining the impact of managers’ network size on SME performance: a case study of Interurban and local road freight transport in the Paris department

This study focuses on the interplay between managers’ personalities, relationships, and company performance. We investigate the influence of managers on a sample of small and medium-sized enterprises (SMEs), specifically examining the size of their networks. Our focus is on enterprises working in the sector of interurban road freight transport and local road freight transport within the Paris department. The model we propose aims to understand the advantages of a well-established and interconnected network for SME performance. We analyse how the different characteristics of a company as well as its manager’s personality and network ties can affect company performance. By drawing upon the dependency network approach, the Resource Dependency Theory, and network theory, we investigate the connection between resource and network dependencies, and how these influence firms’ behavior and long-term growth. Through our theoretical review and by analyzing a database of selected companies through the multiple linear regression and the Principal Component Analysis, we find that networking plays a vital role and significantly impacts a company’s revenues and costs, although not to the extent that we predicted. The results of our research provide evidence of the correlation between networking and performance ratios, but only partially confirm our hypotheses.

Study in a Virtual Night Environment of the Influence of the Travel Mode on the Observation Angle of Illuminated Road Surfaces

ABSTRACT We present a study of the influence of the travel modality (pedestrian, cyclist, motorist) on the observation angle of road surfaces in a nighttime situation under public lighting. This study is based on the simulation of an urban environment where the user travels at different speeds (6, 12 and 25 km/h) depending on the travel mode studied. An interurban main road, where the user travels at 75 km/h, is also simulated to approximate the observation geometry associated with public lighting standards. The results obtained show that the angle of observation of a user varies according to his mode of locomotion. As the speed of travel increases, the observer looks further away. Moreover, the distribution of observation angles is not the same according to the mode of travel. The slower one moves, the greater the spatial extent covered by the visual fixations. These results are likely to encourage current investigations in the field of public lighting. They aim to redefine the geometries of users’ observations according to their mode of travel and the expected functionalities of urban nighttime developments. Beyond that, these results also contribute to the understanding of visual perception in a virtual environment.

Capacity Estimation for Four-Lane Inter-Urban Roads in Telangana through Speed Data Analysis

Capacity Estimation for Four-Lane Inter-Urban Roads in Telangana through Speed Data Analysis

Road Safety Efficiency on Interurban Roads in Spain.

The slowdown in economic development caused by traffic accidents in Spain, together with the disparity in the risk of death or injury due to traffic accidents in its provinces, makes it necessary to evaluate their road safety performance. Therefore, the objectives of the present research are, on the one hand, to find out the level of road safety efficiency of Spanish provinces in the period 2014-2018. On the other hand, it is also aimed to determine to what extent the annual efficiency change is originated by pure changes in efficiency or by technological changes. To achieve both objectives, the nonparametric technique of Data Envelopment Analysis and the Malmquist Index have been used based on the consideration of the Safety Performance Indicators (SPI) as the inputs of the process. The research findings show changes in the level of road safety efficiency in each of the years of the study period. Thus, it is possible to identify a geographical delimitation of the causes that generate changes in efficiency in recent years. A contraction in efficiency and technological progress is identified in part of the Spanish provinces in the north, northeast, and south of Spain.

Planning traffic surveillance in Spain: How to optimize the management of police resources to reduce road fatalities

Although traffic police enforcement is widely recognized as a key action in the road safety field, it can be a costly policy to implement. In addition, governments often impose budget constraints that can limit the resources available for activities such as law enforcement and surveillance. To evaluate the impact of human traffic control resources planning on traffic fatalities on Spanish NUTS-3 regions interurban roads, this paper uses an econometric model to investigate the performance of police enforcement intensity by focusing on two crucial traffic law infractions (i.e., speeding and drunk driving). After controlling for a range of economic, demographic, climate, and risk exposure variables, results highlight the relevance of visible, human, and in-person traffic law enforcement through regular vehicle patrols for reducing traffic crashes, with a non-significant effect of automatic enforcement. Our findings have important implications for traffic police resource management regarding the effective maintenance of patrol cars and plans to digitalize and automatize police administrative tasks and procedures.

Integration of measured data for the seismic fragility assessment of deteriorated bridges

AbstractThe reliable assessment of bridge capacity is necessary in order to ensure the functionality of the roadway network under normal, or emergency operating conditions. Damage due to the interaction with the environment (e.g., corrosion of coastal reinforcement) has been observed in many cases, even in newly built interurban road networks. Therefore, the need for obtaining and including measured data in fragility assessment analysis has emerged. In line with the above, the proposed research introduces a framework for the assessment of bridges considering integrating data obtained with NDTs. The scope of NDTs is to track down the evolution damage on bridges and determine its risk of failure. The work presents a structural damage identification approach that successfully updates a digital twin of the structure. Subsequently the digital twin is used in order to determine the bridge fragility. Fiber modeling is used for creating the digital twin of the structure. Modified uniaxial material laws are applied for the fragility assessment of a deteriorated case study bridge also providing comparative assessment results for the pristine bridge, i.e. without damage.

PRESERVASI JALAN NASIONAL SIMPANG LAGO-SIMPANG BUATAN KABUPATEN SIAK BERDASARKAN UMUR SISA PERKERASAN

<p>Tanjung Buton Mengkapan Port is one of significant transportation node for Riau <br />citizen, especially for Pekanbaru citizen. This port has some destinations within and <br />outside the province of Riau. Access to reach this port through the Simpang lago <br />and, Simpang Buatan. In order to keep good accessibility from and to this port, the <br />road owner should develop a road management program on a regular basis. <br />Programming can be set based on the Remaining Service Life, (RSL). The method <br />which used to determin RSL in this study is the Interurban Road Management <br />System (IRMS) method. The data required are deflection data generated from the <br />Falling Weight Deflectometer (FWD) tools, average daily traffic data (ADT) and <br />road geometric data. The results of the analysis showed that the smallest RSL was <br />0.012 years old at STA 14+220 and the Biggest RSL was 12.35 years old at STA <br />02+636. In addition, based on calculations, it is known that 50.3% of the road <br />length requires overlay as preservation, 38.8% of the length of the road requires <br />routine maintenance and 10.93% of the road needs reconstruction</p>

Low-Cost System for Automatic Recognition of Driving Pattern in Assessing Interurban Mobility using Geo-Information

Mobility in urban and interurban areas, mainly by cars, is a day-to-day activity of many people. However, some of its main drawbacks are traffic jams and accidents. Newly made vehicles have pre-installed driving evaluation systems, which can prevent accidents. However, most cars on our roads do not have driver assessment systems. In this paper, we propose an approach for recognising driving styles and enabling drivers to reach safer and more efficient driving. The system consists of two physical sensors connected to a device node with a display and a speaker. An artificial neural network (ANN) is included in the node, which analyses the data from the sensors, and then recognises the driving style. When an abnormal driving pattern is detected, the speaker will play a warning message. The prototype was assembled and tested using an interurban road, in particular on a conventional road with three driving styles. The gathered data were used to train and validate the ANN. Results, in terms of accuracy, indicate that better accuracy is obtained when the velocity, position (latitude and longitude), time, and turning speed for the 3-axis are used, offering an average accuracy of 83%. If the classification is performed considering just two driving styles, normal and aggressive, then the accuracy reaches 92%. When the geo-information and time data are included, the main novelty of this paper, the classification accuracy is improved by 13%.

SCADA System: Control and Automation of Lighting System of Urban and Inter-Urban Roads

Denetim kontrolü ve veri toplama (SCADA) sistemleri, petrol ve su dağıtım otomasyonu, enerji otomasyonu ve su arıtma sistemi otomasyonu gibi çeşitli alanlarında kullanılmaktadır. Bu çalışmada, şehir içi ve şehirlerarası yolların aydınlatma sisteminin izlenmesi ve kontrolü için Visual Studio C#.NET ortamında geliştirilen bir SCADA sistemi yazılımı tasarlanmıştır. Tasarlanan SCADA yazılımında, şehir içi ve şehirlerarası yolların aydınlatma sistemindeki tüm olayların izlenmesi ve kontrolü, animasyonlar ve renkli grafikler ile ifade edilerek gerçekleştirilmiştir. Bu olaylar, sahada bulunan ışık şiddetini ölçen, arızaları tespit eden algılayıcılar ile aydınlatma direkleri ekipmanlarının nasıl çalıştığını ve bağlantı yapılarını içermektedir. Ayrıca tasarlanan SCADA yazılımı şehir içi ve şehirlerarası yolların aydınlatma sisteminin günlük verilerini, alarm yönetimini, güvenlik yönetimini, veri arşivini ve raporlama işlemlerini de kapsamaktadır. Sonuç olarak, Irak-Kerkük şehrinde yapılan uygulama ile tasarlanan SCADA sistemi yazılımının şehir içi ve şehirlerarası yolların aydınlatma sistemi kontrolünde eş zamanlı, hatasız ve verimli bir şekilde çalıştığı kanıtlanmıştır.

Investment in roads and traffic safety: linked to economic development? A European comparison

This study analyzes how economic resources invested in roads may affect mortality, depending on the level of economic development of a country. To this end, 23 European countries were classified into two groups—high-income countries and low-income countries—according to their average Gross Domestic Product (GDP) per capita over the period 1998–2016. The economic resources are considered through the investment in construction and the maintenance expenditure. Further variables are included to control for several factors related to the infrastructure, socioeconomics, legislation, and meteorology. Fixed-effects panel data models were built separately for the interurban road network of each group of countries. These models also capture the international inequalities within each group and the country-specific national trend for the study period. The main results indicate a reduction effect on the fatality rate of road maintenance expenditure (in both groups), and of the investment in construction (in the low-income countries). Other variables—such as proportion of motorways, motorization rate, unemployment rate, GDP per capita, alcohol consumption, Demerit Point System, and mean annual precipitation—showed statistically significant results as well. Finally, the country-specific fixed effects and the country-specific trend were mapped geographically, to better reflect national conditions for achieving lower fatality rates in the high-income countries, and greater progress in reducing fatalities in the low-income countries. In the end, this study provides evidence to policy-makers that can help to achieve a safer and more sustainable transport system, namely, how to tackle an ongoing major problem—traffic-related deaths—when attending and allocating the economic resources that road infrastructure needs.

Long-term evidence on induced traffic: A case study on the relationship between road traffic and capacity of Budapest bridges

Reducing urban road congestion by infrastructure development promises lower travel times, reduced pollution and wider economic benefits. However, besides advanced transport infrastructure affecting existing traffic, it also induces new demand, which tends to be underestimated. This phenomenon is well-known for interurban roads, especially for motorways, but the literature is scarce on real-life data for urban areas. Most analyses on induced traffic were carried out on relatively short time periods. Therefore, this paper studies 55 years in an urban environment and shows how capacity provision induced extra traffic. Furthermore, it could also be demonstrated that scaling back capacity diminishes travel demand. Most of the analyses on induced traffic concentrated on just a handful of countries; therefore, evidence from a country that emerged from middle income to high income provides new insights for other developing nations and cities.

Predicting the Segment-Based Effects of Heterogeneous Traffic and Road Geometric Features on Fatal Accidents

Inter-urban roads in Indonesia are characterized mainly by distinct road geometry and heterogeneous traffic features. The accident database from the Republic of Indonesia National Traffic Police recorded a substantial number of fatal accidents and

Neural Network-based Model for Traffic Prediction in the City of Valencia

There are many models that attempt to predict vehicular speed in urban and interurban roads, the noise pollution caused by traffic in cities, or even the traffic flow based on historical data from cameras or from people's mobile phones. Such information can be useful for administration authorities, and for researchers attempting to improve the living conditions of citizens. In this context, the aim of the present study is to design a model capable of predicting the traffic flow in the city of Valencia, Spain, based on data collected by electromagnetic loops distributed throughout the city. With a good traffic prediction, it will be possible to foresee possible traffic jams, and also to trigger countermeasures to mitigate them. Therefore, two models based on two recurrent neural networks of Long Short-Term Memory (LSTM) type have been designed to predict the traffic flow in the different streets of Valencia at the different hours of the day. We also study the influence of the specific characteristics used on the accuracy of the model. The results of our experiments show that, despite the high heterogeneity in terms of per-street traffic behaviour, it is possible to reach useful prediction models with low errors.

Constructing a simplified interurban road network based on crowdsourced geodata

The road network that connects cities with the existing road infrastructure of a country is a valuable tool for analyzing its transport routes, connectivity, and urban patterns. Yet, it is challenging to construct, given the data available.•We present a method to construct a simplified and connected urban network. Some network nodes are cities, and others are “transport nodes” representing road crossings or other types of infrastructure.•The result is a simplified connected network of all cities and the existing road infrastructure that maintains road distances and available routes.•The procedure reduces millions of spatial points that sometimes are disconnected polygonal lines or patches into a connected network with only a few edges and nodes.

A “Brilliant Talk” and a “Stirring Appeal”: How Women of Grand Rapids, Michigan, Built an Audience for the Ballets Russes in 1917

A “Brilliant Talk” and a “Stirring Appeal”: How Women of Grand Rapids, Michigan, Built an Audience for the Ballets Russes in 1917

Impact of the COVID-19 Lockdown in a European Regional Monitoring Network (Spain): Are We Free from Pollution Episodes?

The impact of the lockdown, during the period from March to June in 2020, upon the air quality of the Basque Country in northern Spain is analyzed. The evaluation accounts for the meteorology of the period. Daily and sub-daily analysis of aerosol and ozone records show that the territory was repeatedly affected by episodes of pollutants from outer regions. Three episodes of PM10 and ten of PM2.5 were caused by transported anthropogenic European sulfates, African dust, and wildland fires. The region, with a varied orographic climatology, shows high and diverse industrial activity. Urban and interurban road traffic of the region decreased by 49% and 53%, respectively, whereas industrial activity showed a lower reduction of 20%. Consequently, the average concentrations of NO2 in the cities during the period fell to 12.4 µg·m−3 (−45%). Ozone showed up to five exceedances of the WHOAQG for the daily maximum 8-h average in both rural and urban sites, associated with transport through France and the Bay of Biscay, under periods of European blocking anticyclones. However, averages showed a moderate decrease (−11%) in rural environments, in line with the precursor reductions, and disparate changes in the cities, which reproduced the weekend effect of their historical records. The PM10 decreased less than expected (−10% and −21%, in the urban and rural environments, respectively), probably caused by the modest decrease of industrial activity around urban sites and favorable meteorology for secondary aerosol formation, which could also influence the lower changes observed in the PM2.5 (−1% and +3% at the urban and rural sites, respectively). Consequently, in a future low NOx traffic emission scenario, the inter-regional PM and ozone control will require actions across various sectors, including the industry and common pollution control strategies.

Development of models to study traffic accidents on the final sections of access roads to the cities: a case study of three major Iranian cities

The final sections of main access roads to the cities require especial attention as the frequency of accidents in these road sections are considerably higher than other parts of interurban roads. These road sections operate as an interface between the rural roads and urban streets. The previous researches available on this subject are limited and they have also mainly focused on a narrow range of factors contributing to the accidents in these areas. The main contribution of this research is to consider a relatively comprehensive range of potential factors , and to examine their impacts through the development and comparison of both conventional probabilistic models and Artificial Neural Network (ANN) models. For this purpose, information related to the main access roads of three major Iranian cities were collected. This information consisted of accident frequency data together with the field observations of traffic characteristics, road-way conditions and roadside features of these roads. Various ANN and probabilistic models were developed. The frequency of accidents, i.e. fatal, injured, or damaged accidents, was considered as the output of the developed models. The results indicated that a hybrid of ANN models, each comprised of 10 input variables representing traffic, roadway and roadside conditions, outperformed several probabilistic models, i.e. Poisson, Negative binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial models, also developed under similar conditions in this study. Moreo-ver, effective roadway width, roadway lighting condition, the standard deviation of vehicles speed, percentage of drivers violating the speed limit, average annual daily traffic, percentage of heavy goods vehicles, the density of road-side commercial and industrial landuses, the density of median U-turns, the density of local access roads, and the effective width of the left-side shoulder were identified as the most effective factors contributing to the accidents in these areas. The developed ANN model can be used as a tool to predict accident rates in these road sections, and to estimate a potential reduction in the accident rates, following any improvements in the major factors contributing to the traffic accidents in these areas.

Sensitivity analysis and uncertainty quantification of a seismic risk model for road networks

AbstractNatural hazards may cause significant disruptions to road infrastructure, subsequently affecting road agencies, users, and productive activities. Despite the existence of infrastructure fragilities to seismic hazard and some operational consequences on network mobility, previous research has not modeled risk in terms of traffic disruptions and consequent travel time delays in subduction environments, analyzing the sensitivity to model parameters and quantified model uncertainty. This study proposes a risk framework to evaluate operational consequences in interurban road networks exposed to seismic hazard using travel time delays and propagate uncertainty in the model. Risk values are evaluated using Monte Carlo simulations, and uncertainty is propagated using a polynomial chaos expansion meta‐model. The framework was applied to a very critical interurban network in central Chile. Results demonstrate that the parameters that most significantly influence risk are fragility, loss of road capacity, and traffic volume.