Road Network Design Research Articles

Detection of Pothole in Real-Time Using Android Based Application

Road networks are the means of transporting, sharing and movement of goods and services from place to place in society. Road networks are also channels of communication in some parts of the world. Consequently, access to good road networks enhances the quality of life and work of people living in society. But the poor nature of design and development of road networks coupled with natural disasters such as heavy rainfall has brought about many unwanted potholes and scratches on the roads which are very dangerous to commuters and other road users as well as vehicles that utilize the roads. In addition, the lack of a proper road maintenance system has resulted in an ever-increasing number of potholes which endanger efficient transportation and road safety. Meanwhile road maintenance works has largely depended on manual detection and reporting The project conducts a study into the use of the internet of things to detect and report potholes on roads. The paper assembles an open hardware equipment and sensor to experiment the detection and reporting of potholes using GPS Tracker devices. The project presented the architectural design and system to detect, report and manage potholes and other road obstacles using GPS Tracker. The project also presented some prospects and challenges in the implementation of the internet of things GPS. The main components of the project are the Accelerometer, GPS and the Android smartphone. This project would be given to government road contractors to rectify the potholes and avoid accidents and help in traffic analysis. Also, our aim is to make safety systems affordable to every vehicle in the country.

A novel framework of graph Bayesian optimization and its applications to real-world network analysis

Network structure optimization is a fundamental task of many expert and intelligent systems, such as the intelligent tools for chemical molecular discovery and expert systems for road network design. However, traditional model-free methods suffer from the expensive computational cost of evaluating networks; almost all the research on Bayesian optimization is aimed at optimizing the objective functions with vectorial inputs, e.g., the hyper-parameters in any expert systems. This work focuses on applying Bayesian optimization to optimize network structure with graph-structured inputs, and presents a flexible framework, denoted as graph Bayesian optimization (GBO), to handle arbitrary graphs. By combining the proposed framework with graph kernels, it can take full advantage of implicit graph structural features to supplement explicit features guessed according to the experience, such as tags of nodes and any attributes of graphs. Simultaneously, the proposed framework can identify which features are more important during the optimization process. By collaboratively working with a down-stream decision tree, the GBO can not only find the optimum but also discover its knowledge represented by rules, which can further enhance its interpretability and assist expert decision-making. A novel problem of opening the gated residential areas is presented in this work, which can serve as one benchmark task of road network design. Intensive experiments conducted on three real-world applications, including robust network design, the most active node identification, and urban transportation network design, demonstrate its efficacy and potential applications.

Impact of Forest Roads on Hydrological Processes

The current review summarizes the knowledge generated by the recently published studies of the last twenty years, in the field of forest road networks, concerning the impact of forest road construction on hydrological processes. The currently applied methodology techniques/practices are discussed, the findings are highlighted and effective mitigation measures to mitigate the impact of forest roads are proposed. Critical for the minimization of the impact of forest roads on overland flow is the significant decrease in road surface runoff and overland flow velocity. The decrease in runoff energy reduces the detachment of soil particles and transportation in streams. The disturbances of forest roads in logging areas should be limited to decrease soil erosion. Additionally, aiming to minimize sediment transportation into the streams, it is very important to reduce the connectivity between the forest roads (or skid trails) and streams. The positive role of vegetation and organic matter on the road prism, naturally/technically established riparian buffers along the streams, and the use of appropriate bioengineering designs for each area significantly decrease the runoff generation and sedimentation. From a construction point of view, the decrease in short and long-term forest road-related impact could be achieved by reducing the depth of excavations and the use of soil compaction limiting technology during forest works. The road network design should be more efficient, avoiding hydrologically active zero-order basins. Techniques that minimize the length and connectivity among skid trails, unpaved roads and streams are highly crucial. Broad-based dips, immediate revegetation and outsloping of the road base are considered good road construction practices. Research should be focused on the hydrologic behavior of forest road networks and on the impact at the watershed scale, the degree of connectivity, utilizing plenty of qualitative field data, especially during intense rainfall events, which has been proven to exacerbate the runoff and sediment generation and transportation into the stream networks.

Off the Grid…and Back Again?

Problem, research strategy, and findings In this morphological study I identify and measure recent nationwide trends in American street network design. Historically, orthogonal street grids provided the interconnectivity and density that researchers identify as important factors for reducing vehicular travel and emissions and increasing road safety and physical activity. During the 20th century, griddedness declined in planning practice along with declines in urban form compactness, density, and connectivity as urbanization sprawled around automobile dependence. But less is known about comprehensive empirical trends across U.S. neighborhoods, especially in recent years. Here I use public and open data to examine tract-level street networks across the entire United States. I develop theoretical and measurement frameworks for a quality of street networks defined here as griddedness. I measure how griddedness, orientation order, straightness, 4-way intersections, and intersection density declined from 1940 through the 1990s, while dead-ends and block lengths increased. However, since 2000, these trends have rebounded, shifting back toward historical design patterns. Despite this rebound, when controlling for topography and built environment factors, all decades after 1939 are associated with lower griddedness than pre-1940 decades. Higher griddedness is associated with less car ownership—which itself has a well-established relationship with vehicle kilometers traveled and greenhouse gas emissions—while controlling for density, home and household size, income, jobs proximity, street network grain, and local topography. Takeaway for practice Interconnected grid-like street networks offer practitioners an important tool for curbing car dependence and emissions. Once established, street patterns determine urban spatial structure for centuries, so proactive planning is essential.

Scalable and Parallel Deep Bayesian Optimization on Attributed Graphs.

We propose a general and scalable global optimization framework directly operating on annotated graph data by introducing a Bayesian graph neural network to approximate the expensive-to-evaluate objectives. It prevents the cubical complexity of Gaussian processes and can scale linearly with the number of observations. Its parallelized variant makes it scalable. We provide strict theoretical support on its convergence. Intensive experiments conducted on both artificial and real-world problems, including molecular discovery and urban road network design, demonstrate the effectiveness of the proposed methods compared with the current state of the art.

Complex networks to understand the past: the case of roads in Bourbon Spain.

The work aims to study, using GIS techniques and network analysis, the development of the road network in Spain during the period between the War of Succession and the introduction of the railway (1700–1850). Our research is based on a detailed cartographic review of maps made during the War of Succession, largely improving preexisting studies based on books of itineraries from the sixteenth century onwards. We build a new, complete map of the main roads at the beginning of the eighteenth century along with the matrix of transport costs for all the important towns describing the communications network. Our study of this complex network, supplemented by a counterfactual analysis carried out using a simulation model based on agents using different centralized decision-making processes, allows us to establish three main results. First, existing trade flows at the beginning of the eighteenth century had a radial structure, so the Bourbon infrastructure plan only consolidated a preexisting situation. Second, the development of the network did not suppose important alterations in the comparative centrality of the regions. Finally, the design of the paved road network was adequate for the economic needs of the country. These findings are in stark contrast with claims that the radial structure of the Bourbon roads was designed ex-novo with political or ideological objectives rather than economic ones. Our methodology paves the way to further studies of path-dependent, long-term processes of network design as the key to understanding the true origin of many currently existing situations.

Off the Grid… and Back Again? The Recent Evolution of American Street Network Planning and Design

This morphological study identifies and measures recent nationwide trends in American street network design. Historically, orthogonal street grids provided the interconnectivity and density that researchers identify as important factors for reducing vehicular travel and emissions and increasing road safety and physical activity. During the 20th century, griddedness declined in planning practice alongside declines in urban form compactness, density, and connectivity as urbanization sprawled around automobile dependence. But less is known about comprehensive empirical trends across US neighborhoods, especially in recent years. This study uses public and open data to examine tract-level street networks across the entire US. It develops theoretical and measurement frameworks for a quality of street networks defined here as griddedness. It measures how griddedness, orientation order, straightness, 4-way intersections, and intersection density declined from 1940 through the 1990s while dead-ends and block lengths increased. However, since 2000, these trends have rebounded, shifting back toward historical design patterns. Yet, despite this rebound, when controlling for topography and built environment factors all decades post-1939 are associated with lower griddedness than pre-1940. Higher griddedness is associated with less car ownership—which itself has a well-established relationship with vehicle kilometers traveled and greenhouse gas emissions—while controlling for density, home and household size, income, jobs proximity, street network grain, and local topography. Interconnected grid-like street networks offer practitioners an important tool for curbing car dependence and emissions. Once established, street patterns determine urban spatial structure for centuries, so proactive planning is essential.

Forecast and control of traffic noise based on improved UE model during road network design

Considering the factor of traffic noise during design period could mitigate the noise emission of urban road networks. In this paper, noise prediction and control of typical points among design networks are presented, with the establishment of a univariate noise prediction model and the improvement of UE (user equilibrium) traffic assignment model. First, a univariate traffic noise prediction model is built with flow as variate merely, which is based on the line source model and introduce of the Van Aeder model. Furthermore, the accuracy of the prediction model is verified in comparison with measured traffic noise data. Secondly, the univariate traffic noise prediction model and travel time model are combined to form the impedance function with different traffic noise weight coefficients after normalization, and upon which the UE model is rebuilt with the road level of service as a constraint. Finally, the improved UE model is used to study the noise control law of the control points, which are divided in two types according to the location. The results show that the improved UE model can effectively reduce the traffic noise of control points by adjusting the traffic noise weight, and among them, the traffic noise of the control point beside the single road and the control point at the road crossing are reduced by at most 0.54 dB, 1.1 dB respectively. Meanwhile, the noise control of points in road network will cause uncertainty to the overall traffic noise emission of the road network, which confirms the noise paradox. Besides, while the traffic noise of the road where the control point is located is reduced, the noise emission and the travel delay of roads in parallel with objective road increases by 0.19 dB, 0.932 s at most. The correlation coefficient between the traffic noise difference of the control point and the VC ratio difference of the road beside the control point is as high as 0.9811 under the improved UE model with different traffic noise, and there is a linear relationship between them. The study can provide a reference for traffic noise control during urban road network design.

Multi-objective optimization model and algorithm design of road network in tourist town

To alleviate traffic congestion in tourist towns, we propose a method to optimize the road network design by combining the macro-traffic simulation software with the heuristic algorithm. Based on the characteristics of traffic flow in tourist towns, the problem of optimal design of tourism urban road network is transformed into a multi-objective optimization model. To seek the optimal balance point between traffic congestion management and road resource investment, a multi-objective optimization model is established to optimize the saturation system of each road section and minimize the investment cost. We use TransCAD simulation software and the user equilibrium model to distribute the traffic flow of the initial road network, then, design the model algorithm based on genetic algorithm, and at last, design Matlab algorithm program to solve the model. The optimal weight of the objective function is determined by multiple algorithm experiments and comparative analysis of the experimental results. The results of the numerical example show that the total saturation value of all sections in the road network decreases from 16.70 to 11.12, and the average saturation value of all sections in the road network decreases from 0.93 to 0.62. The saturation of optimized sections is stable in a reasonable range from 0.5 to 0.8. The overall road network saturation is significantly reduced and becomes more balanced, moreover, the cost of investment is more reasonable. Therefore, results of the study have certain guiding significance for the road network planning of new tourist towns.

Optimal Placement of wireless charging lanes in road networks

The emergence of electric vehicle wireless charging technology, where a whole lane can be turned into a charging infrastructure, leads to new challenges in the design and analysis of road networks. From a network perspective, a major challenge is determining the most important nodes with respect to the placement of the wireless charging lanes. In other words, given a limited budget, cities could face the decision problem of where to place these wireless charging lanes. With a heavy price tag, a placement without a careful study can lead to inefficient use of limited resources. In this work, the placement of wireless charging lanes is modeled as an integer programming problem. The basic formulation is used as a building block for different realistic scenarios. We carry out experiments using real geospatial data and compare our results to different network-based heuristics. Reproducibility: all datasets, algorithm implementations and mathematical programming formulation presented in this work are available at https://github.com/hmwesigwa/smartcities.git

A greedy evolutionary hybridization algorithm for the optimal network and quadratic assignment problem

Our paper deals with a combinatorial optimization problem called the optimal network and quadratic assignment problem. The problem has been introduced by Los (Region Sci Urban Econ 8:21–42, 1978) as a model of an urban planning problem that consists in optimizing simultaneously the best location of the activities of an urban area (land-use), as well as the road network design (transportation network) in such a way to minimize as much as possible the routing and network costs. We propose a mixed-integer programming formulation of the problem, and a hybrid algorithm based on greedy and evolutionary heuristic methods. Some numerical experiments on randomly generated instances, and on real-life big data from Dakar city, show the efficiency of the method.

Home and school environmental correlates of childhood BMI

BackgrouandActive commuting to school can be a substantial opportunity to provide the necessary daily physical activity for children and to counteract childhood obesity. This paper examines the associations of urban form, in general, and street network design, in particular, with body mass index (BMI) in children aged between 12 and 16, controlling for socio-economic features (gender, educational attainment, income, and auto ownership) and daily physical activity (access mode to/from school and walking behaviour). MethodsData were drawn from questionnaires conducted in 20 elementary schools located in the Anatolian part of İstanbul, Turkey. Randomly selected 6th, 7th, and 8th grade students (N = 1784) completed questionnaires regarding their commuting modes to/from school while their parents (N = 1118) completed questionnaires about their socio-economic characteristics and their children's daily physical activity. Each student's BMI was calculated by measured height and weight data. Home- and school-environments (800-and 1600-m buffers around the respondent and school) were evaluated through GIS-based land-use data and segment-based street connectivity measures. Selected street segments within school-environments were also audited with regard to pedestrian environment characteristics. ResultsFindings indicate that children who actively commuted to/from school had lower BMIs than non-active commuters. More importantly, it is shown that increased street network connectivity measured at the segment-level is significantly associated with reduced BMI in school children. In fact, connectivity measures appear to be the strongest correlates of BMI. ConclusionsThis study provides important evidence for planners, urban designers, and policy makers on the significance of built environment, in general, and street network configuration, in particular, within home- and school-environments. One rule of thumb would be to design a well-connected street network with relatively denser connections and reduced direction changes within the neighbourhood – not only within a couple of blocks of homes and schools but also within their larger fabric (800–1600 mt buffers).

Road Network Design in a Developing Country Using Mobile Phone Data: An Application to Senegal

This study uses mobile phone data to understand mobility patterns in a country, with limited mobility data, in order to give advice about decisions on how to design the national and regional road network. Our method consists of three parts: (1) filtering mobile phone traces to derive mobility patterns, (2) building an adapted formulation of the gravity-based trip distribution model, which considers telecommunication intensity (i.e., aggregate number of calls and text messages) and travel time as input to forecast the influence of road improvements on country-wide mobility, and (3) optimizing the road network investment based on the adapted trip distribution model by using a local search algorithm. The method was applied to the case study country of Senegal. The mobile phone data was transformed to support informed decisions on road network development in that country given different objectives, namely accessibility and equity. We believe that the methodology is valuable and reproducible to other countries where traditional mobility data is scarce but mobile phone data is available to transport planners.

Connected and Autonomous Vehicles, Electric Scooter and Their Implications for Road Network Design

New generation mobile telecommunication networks and battery technology are profoundly transforming the capability of vehicles and the transport system. The road network will need to be adapted to this new technical reality. A historical assessment of the transformation of the British and French road network in the 20th century was undertaken, and this article summarises its key findings into a conceptual framework. This framework has been applied to better understand the potential impact of CAVs and E-scooters.

Forest Road Network Design based on Multipurpose Forestry Management in Hyrcanian Forest

Traditionally, the main focus of forestry management has been based on wood production but more recently it is directed at multifunctional forest management. Multifunctional forestry management includes many considerations such as ecotourism, ecology, economic and social issues of forest dwellers as well as wood production. This study aims to design forest roads using GIS and satellite data of SPOT-HRG in the Darabkla forest based on Multipurpose Forestry. The study used the multi-criteria evaluation method based on fuzzy logic to assess the potential of land area for a road network. Opinions of experts and scholars were used to select four criteria and 18 sub-criteria for road design. Analytical Hierarchy Process (AHP) was used for weighting factors. Layers were combined using a weighted linear combination (WLC) operator and the map of crossing the road potential was identified and zoned. The road was designed using the PEGGER program. Geographic Information System (GIS) and satellite data of SPOT-HRG were effective tools for improving outcomes. Weighted Linear Combination (WLC) Model for combination layers was used in this study and recommended the multi object operation (MOLA) in future studies.

Design And Enactment Of Dynamically Reconfigurable Bus Enhanced Noc Architecture For Emerging Digital System

The large amount imperative issue in present VLSI circuit proposes in the area and power reduction. This work proposes a new architecture which reduces an area efficiently.The reimbursement of adding a little latency, modified mutual bus as an essential element of the NoC structural design is explored. This architecture design reduces the charge of partisan a broad choice of design occurrence through specified throughput needs by minimizing the requirement of design entities in the architecture design of NoC road and rail network for the area minimization.

A Decentralized Solution for Transmission Expansion Planning: Getting Inspiration from Nature

Transmission expansion planning is a problem of considerable complexity where classical optimization techniques are unable to handle large case studies. Decomposition and divide-and-conquer strategies have been applied to this problem. We propose an alternative approach based on agent-based modeling (ABM) and inspired by the behavior of the Plasmodium mold, which builds efficient transportation networks as result of its search for food sources. Algorithms inspired by this mold have already been applied to road-network design. We modify an existing ABM for road-network design to include the idiosyncratic features of power systems and their related physics, and test it over an array of case studies. Our results show that the ABM can provide near-optimal designs in all the instances studied, possibly with some further interesting properties with respect to the robustness of the developed design. In addition, the model works in a decentralized manner, using mostly local information. This means that computational time will scale with size in a more benign way than global optimization approaches. Our work shows promise in applying ABMs to solve similarly complex global optimization problems in the energy landscape.

Las calles latinoamericanas. Teoría e intervención

El sistema espacial de movilidad tiene un papel esencial en las ciudades al estructurar el crecimiento urbano, permitir la accesibilidad e incidir en los aspectos ambientales, económicos y sociales del espacio público. A pesar de esta concepción teórica, la necesidad de resolver los problemas derivados de la movilidad en Latinoamérica ha impulsado intervenciones que, en la mayoría de los casos, han contemplados para su diseño criterios funcionales que responden al sistema de transporte motor. El presente trabajo caracteriza dos líneas de pensamiento sobre movilidad y planificación urbana a nivel mundial, para luego analizar bajo dicho lente tres casos de espacios viarios diseñados y ejecutados en distinto momento en ciudades de América Latina: Río de Janeiro, Bogotá y Medellín. Esto conlleva a reflexionar sobre la relación entre las propuestas teóricas, y la práctica de diseño y construcción de las redes viarias.

Street-level neighborhood greenery linked to active transportation: A case study in Milwaukee and Green Bay, WI, USA

Sedentary lifestyles contribute to many adverse health outcomes and pose concerns for public health worldwide. Studies show that road network design and greenery are critical, independent factors in supporting active lifestyles. Yet greenery along the road network has been insufficiently assessed. This study modelled individual weekly participation in active transportation (AT) using spatially refined measures of street versus overall neighborhood greenery in greater Milwaukee and Green Bay, Wisconsin, USA. Measures of AT (walking or biking for commutes or errands) were collected by the Survey of the Health of Wisconsin. Meter-scale landcover was used to estimate percent tree cover and aggregate greenery (tree and herbaceus cover combined) at increasing distances from each residence (n = 423) along neighborhood streets and in circular buffers. Street greenery metrics were designed to indicate the provision of ecosystem services, including shade and aesthetics, which promote physical activity by enhancing the safety and beauty of the publicly-accessible outdoor environment. Positive associations were consistently observed for street tree cover (e.g., adjusted odds ratio for a 10% increase in sidewalk tree cover within 500 m = 1.19; 95% CI: 1.02–1.40; and in street tree cover within 1250 m = 1.39; 95% CI: 1.09–1.79). Aggregate greenery was significant only in circular buffers, where it was negatively associated with AT. Sensitivity analysis revealed that herbaceous cover alone was consistently negatively associated with AT. Findings inform urban design to promote healthy lifestyles by distinguishing street tree cover as a positive factor in AT. Studies in additional geographic areas and causal designs are recommended.

Forest Road Design Combining Common Design Techniques and GIS (Case Study: 2nd Series of Liresar Forest)

Nowadays, it is necessary to apply modern techniques for the design of road networks, especially roads passing through ecosystems such as forests, in order to reduce operating costs, prevent further degradation of the environment, increase road efficiency and achieve sustainable development goals. In this paper, a new way of designing the road is presented. New design method has the ability to analyze a large amount of information in a variety of digital layers using GIS while being able to store, recover, and analyze information through multi-criteria decision-making process (AHP) and routing algorithms at high speed and precision. The output of the proposed design method (combining information with AHP via Dijkstra algorithm in GIS software) is compared with the existing forest road in the 2nd series of Liresar in Mazandaran province of Iran, designed using common methods. According to experts, hydrological criteria (0.408) and environmental criteria (0.375) have the highest importance and weight in comparison with other criteria in forest road design. The results show the map of area's capability for road construction is prepared for road design with better functionality and less adverse effects on the environment using the divider method compared to conventional topographic maps. Finally, the design of the new road in comparison with the existing reduce the slope (5%), increase access (15%) and reduce the cost of construction (30%).