Summary
Especially in urban contexts, the detection of damages in road infrastructures is crucial for their management and efficiency. This entails complex measurement chains. Several solutions were ...already developed and applied (e.g., high speed monitoring systems or sensor‐based systems), but the emerging smart city and smart road paradigms call for innovations in these fields. A possible solution could be the development of smart, non‐intrusive, and sustainable sensing systems able to perform continuous monitoring, allowing automatic and timely generation of alarms and proper maintenance strategies from Road Management Systems (RMSs). Consequently, this study aims to demonstrate the feasibility of integrating miniaturized sensing systems with high‐speed monitoring systems, to obtain innovative RMSs. In this regard, a specific web‐based platform, the core of a Smart RMS, properly defined to acquire, correlate, and exploit data from several sources was developed. To this end, high‐performance monitoring systems, an innovative sensing system (i.e., based on miniaturized devices and on feature‐ and signature‐based methods), and Micro‐electromechanical systems (i.e., smartphones accelerometers) were used. A new set of indicators has been set up and partly validated in the pursuit of setting out a new paradigm where Pavement Management Systems are supposed to become urban‐oriented and less expensive. Results show that combining traditional and innovative solutions allows providing a comprehensive overview of both the structural condition and the performance of road infrastructures. This information could be used to exponentially improve the efficiency of current RMSs in forecasting the occurrence of damages and in scheduling more effective and sustainable management interventions.
Non-cyclical and high-leverage infrastructure projects, such as road transportation networks, have been considered as critical policy instruments to promote growth and social development. Yet, their ...growth-generating effect on the economic welfare of countries and regions has come under scrutiny in recent years: several studies have nuanced the implicit positive associations between investments in transportation and economic benefits. Building upon a set of traffic flow characteristics as potential correlates to the regional development indicator, this research focuses on the economic impacts of Egnatia Odos Motorway (EOM) on Greece's Northern region. To specify, by employing a large-scale longitudinal dataset which includes over 230 million entry records of various vehicle types along EOM, generated from toll collection systems between 2010 and 2019, we investigate the associations between traffic data and potential variations in regional GDP per capita annual growth rate. Our results suggest positive associations between regional economic development and the EOM operation and, more specifically, with passengers' transportation and inland freight. We conclude that transportation big data provide essential input for the appraisal of a road transport investment project, reveal the status of regional welfare, and may contain valuable information for spatial management and planning.
Road transport imposes negative externalities on society. These externalities include environmental and road damage, accidents, congestion, and oil dependence. The cost of these externalities to ...society is in general not reflected in the current market prices in the road transport sector.
An efficient mobility model for the future must take into account the true costs of transport and its regulatory framework will need to create incentives for people to make sustainable transport choices. This paper discusses the use of economic instruments to correct road transport externalities, but gives relatively more weight to the problem of carbon emissions from road transport, as this is particularly challenging, given its global and long-term nature.
Economics offers two types of instruments for addressing the problem of transport externalities: command-and-control and incentive-based policies.
Command-and-control policies are government regulations which force consumers and producers to change their behaviour. They are the most widely used policy instruments. Examples include vehicle emission and fuel standards in the US as well as driving or parking restrictions in Singapore. The implementation cost of these instruments to the government is small. Although from an economic perspective these policies often fail to achieve an efficient market outcome, the presence of political constraints often make them the preferred option, in terms of feasibility and effectiveness.
Economic theory shows how policies, which affect consumption and production incentives, can be used to achieve the optimal outcome in the presence of externalities. Incentive-based policies function within a new or an altered market. We first examine incentive-based policies, which cap the aggregate amount of the externality, such as carbon emissions, by allocating permits or rights to the emitters. The emitters are then free to trade their permits amongst them. The permit allocation mechanism is important–although market efficiency would be satisfied by an auction, political influences usually favour a proportional allocation based on historic emissions. We discuss EU ETS as an example of a cap-and-trade system, however, no such policy for CO
2 emissions in road transport has been implemented anywhere in the world to date.
Fiscal instruments are, like command-and-control, widely used in road transport, because they are relatively cheap and simple to implement. They include the use of taxes and charges in order to bridge the gap between private and the social costs and, in principle, can lead to an efficient market solution. Registration, ownership, fuel, emissions, usage taxes, and parking and congestion charges have been implemented in many countries around the world. On the other side of the spectrum, subsidies can be given to those scrapping old cars and buying fuel-efficient vehicles. Some cities, such as London, have implemented congestion charges and many states in the United States have introduced high occupancy lanes. Other interesting possibilities include pay-as-you-drive insurance and other usage charges. However, the size and scope of taxes and subsidies are determined by governments, and because of their imperfect knowledge of the market the outcome is still likely to be inefficient.
Governments have many effective economic instruments to create a sustainable road transport model. These instruments can be used separately or together, but their implementation will be necessary in the nearest future.
PurposeA large number of roads have been constructed in the rural areas of India to connect habitations with the nearest major roads. With time, the pavements of these roads have deteriorated and ...they need some kind of maintenance, although they all do not need maintenance at the same time, as they have all not deteriorated to the same level. Hence, they have to be prioritized for maintenance.Design/methodology/approachIn order to present a scientific methodology for prioritizing pavement maintenance, the factors affecting prioritization and the relative importance of each were identified through an expert survey. Analytic Hierarchy Process (AHP) was used to scientifically establish weight (importance) of each factor based on its relative importance over other factors. The proposed methodology was validated through a case study of 203 low volume rural roads in the state of Himachal Pradesh in India. Ranking of these roads in order of their priority for maintenance was presented as the final result.FindingsThe results show that pavement distresses, traffic volume, type of connectivity and the socioeconomic facilities located along a road are the four major factors to be considered in determining the priority of a road for maintenance.Research limitations/implicationsThe methodology provides a comprehensive, scientific and socially responsible pavement maintenance prioritization method which will automatically select roads for maintenance without any bias.Practical implicationsTimely maintenance of roads will also save budgetary expenditure of restoration/reconstruction, leading to enhancement of road service life. The government will not only save money but also provide timely benefit to the needy population.Social implicationsRoad transportation is the primary mode of inland transportation in rural areas. Timely maintenance of the pavements will be of great help to the socioeconomic development of rural areas.Originality/valueThe proposed methodology lays special emphasis on rural roads which are small in length, but large in number. Instead of random, a scientific method for selection of roads for maintenance will be of great help to the public works department for better management of rural road network.
For the use of the national highway network of Lithuania, freight vehicles pay a fee of a fixed amount using the system of purchasing electronic vignettes (hereinafter referred to as e. vignettes). ...The tax is paid for a certain period (day, week, month, or year) regardless of the distance traveled by vehicles. Such a taxation model does not value the “polluter pays” principle enshrined in EU legislation and does not allow covering the damage caused by freight vehicles to the road infrastructure. Road maintenance and development program financing law no. VIII-2032 by the law on the amendment of articles 2, 6, 9 and appendices 2, 5, VĮ Lithuanian Road Directorate until 2023 must develop and implement an electronic road toll system that should replace the currently used e. vignettes. The article presents the currently tolled road network of Lithuania, the financial impact on the companies providing transportation services after the introduction of the electronic road toll system. The road toll systems operating in European countries and Lithuania and their operating technologies, marginal tariffs are analyzed, and a methodology is proposed, based on which it would be possible to fill in the list of currently tolled roads. A company providing cargo transportation services has been selected, and it has been determined how the amount of paid taxes will change after the implementation of the electronic road toll system on Lithuanian roads. It has been determined that after the introduction of EKRS for companies providing transportation services that carry out long-distance transport in Lithuania, the amount of taxes paid for using state roads will increase significantly.
A global strategy for road building Laurance, William F; Clements, Gopalasamy Reuben; Sloan, Sean ...
Nature (London),
09/2014, Letnik:
513, Številka:
7517
Journal Article
Recenzirano
Odprti dostop
The number and extent of roads will expand dramatically this century. Globally, at least 25 million kilometres of new roads are anticipated by 2050; a 60% increase in the total length of roads over ...that in 2010. Nine-tenths of all road construction is expected to occur in developing nations, including many regions that sustain exceptional biodiversity and vital ecosystem services. Roads penetrating into wilderness or frontier areas are a major proximate driver of habitat loss and fragmentation, wildfires, overhunting and other environmental degradation, often with irreversible impacts on ecosystems. Unfortunately, much road proliferation is chaotic or poorly planned, and the rate of expansion is so great that it often overwhelms the capacity of environmental planners and managers. Here we present a global scheme for prioritizing road building. This large-scale zoning plan seeks to limit the environmental costs of road expansion while maximizing its benefits for human development, by helping to increase agricultural production, which is an urgent priority given that global food demand could double by mid-century. Our analysis identifies areas with high environmental values where future road building should be avoided if possible, areas where strategic road improvements could promote agricultural development with relatively modest environmental costs, and 'conflict areas' where road building could have sizeable benefits for agriculture but with serious environmental damage. Our plan provides a template for proactively zoning and prioritizing roads during the most explosive era of road expansion in human history.
Automatic detection of pavement cracks is an important task in transportation maintenance for driving safety assurance. However, it remains a challenging task due to the intensity inhomogeneity of ...cracks and complexity of the background, e.g., the low contrast with surrounding pavement and possible shadows with similar intensity. Inspired by recent success on applying deep learning to computer vision and medical problems, a deep-learning based method for crack detection is proposed in this paper. A supervised deep convolutional neural network is trained to classify each image patch in the collected images. Quantitative evaluation conducted on a data set of 500 images of size 3264 χ 2448, collected by a low-cost smart phone, demonstrates that the learned deep features with the proposed deep learning framework provide superior crack detection performance when compared with features extracted with existing hand-craft methods.
Aim: Collisions between wildlife and vehicles are recognized as one of the major causes of mortality for many species. Empirical estimates of road mortality show that some species are more likely to ...be killed than others, but to what extent this variation can be explained and predicted using intrinsic species characteristics remains poorly understood. This study aims to identify general macroecological patterns associated with road mortality and generate spatial and species-level predictions of risks. Location: Brazil. Time period: 2001–2014. Major taxa: Birds and mammals. Methods: We fitted trait-based random forest regression models (controlling for survey characteristics) to explain 783 empirical road mortality rates from Brazil, representing 170 bird and 73 mammalian species. Fitted models were then used to make spatial and species-level predictions of road mortality risk in Brazil, considering 1,775 birds and 623 mammals that occur within the continental boundaries of the country. Results: Survey frequency and geographical location were key predictors of observed rates, but mortality was also explained by the body size, reproductive speed and ecological specialization of the species. Spatial predictions revealed a high potential standardized (per kilometre of road) mortality risk in Amazonia for birds and mammals and, additionally, a high risk in Southern Brazil for mammals. Given the existing road network, these predictions mean that >8 million birds and >2 million mammals could be killed per year on Brazilian roads. Furthermore, predicted rates for all Brazilian endotherms uncovered potential vulnerability to road mortality of several understudied species that are currently listed as threatened by the International Union for Conservation of Nature. Conclusion: With a rapidly expanding global road network, there is an urgent need to develop improved approaches to assess and predict road-related impacts. This study illustrates the potential of trait-based models as assessment tools to gain a better understanding of the correlates of vulnerability to road mortality across species, and as predictive tools for difficult-to-sample or understudied species and areas.
Aim
The road network is increasing globally but the consequences of roadkill on the viability of wildlife populations are largely unknown. We provide a framework that allows us to estimate how risk ...of extinction of local populations increases due to roadkill and to generate a global assessment that identifies which mammalian species are most vulnerable to roadkill and the areas where they occur.
Location
Global.
Time period
1995–2015.
Major taxa studied
Terrestrial mammals.
Methods
We introduce a framework to quantify the effect of roadkill on terrestrial mammals worldwide that includes three steps: (a) compilation of roadkill rates to estimate the fraction of a local population killed on the roads, (b) prediction of population risk of extinction based on observed roadkill rates (for a target group of species of conservation concern and non‐threatened species with high roadkill rates), and (c) global assessment of vulnerability to roadkill for 4,677 terrestrial mammalian species estimated using phylogenetic regression models that link extinction risk to demographic parameters.
Results
We identified four populations among the 70 species in the target group that could become extinct in 50 years if observed roadkill levels persist in the study areas: maned wolf Chrysocyon brachyurus (Brazil), little spotted cat Leopardus tigrinus (Brazil), brown hyena Hyaena brunnea (Southern Africa) and leopard Panthera pardus (North India). The global assessment revealed roadkill as an added risk for 2.7% (n = 124) terrestrial mammals, including 83 species Threatened or Near Threatened. We identified regions of concern that have species vulnerable to roadkill with high road densities in areas of South Africa, central and Southeast Asia, and the Andes.
Main conclusions
Our framework revealed populations of threatened species that require special attention and can be incorporated into management and planning strategies informing road managers and conservation agencies.
Accurate road detection and centerline extraction from very high resolution (VHR) remote sensing imagery are of central importance in a wide range of applications. Due to the complex backgrounds and ...occlusions of trees and cars, most road detection methods bring in the heterogeneous segments; besides for the centerline extraction task, most current approaches fail to extract a wonderful centerline network that appears smooth, complete, as well as single-pixel width. To address the above-mentioned complex issues, we propose a novel deep model, i.e., a cascaded end-to-end convolutional neural network (CasNet), to simultaneously cope with the road detection and centerline extraction tasks. Specifically, CasNet consists of two networks. One aims at the road detection task, whose strong representation ability is well able to tackle the complex backgrounds and occlusions of trees and cars. The other is cascaded to the former one, making full use of the feature maps produced formerly, to obtain the good centerline extraction. Finally, a thinning algorithm is proposed to obtain smooth, complete, and single-pixel width road centerline network. Extensive experiments demonstrate that CasNet outperforms the state-of-the-art methods greatly in learning quality and learning speed. That is, CasNet exceeds the comparing methods by a large margin in quantitative performance, and it is nearly 25 times faster than the comparing methods. Moreover, as another contribution, a large and challenging road centerline data set for the VHR remote sensing image will be publicly available for further studies.
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