Road Planning Research Articles

The rocks are hotter on the other side of the fence: roadside habitats should inform mitigation design

Maintaining viable populations of large reptiles is often challenging in road fragmented landscapes. While mitigation structures can reduce impacts, few studies have investigated how mitigation success can be affected by roadside habitats. In southeast Ohio, USA, we evaluated mitigation effectiveness for state-endangered timber rattlesnakes (Crotalus horridus) at a new highway in a forested landscape. Road construction at the study site created a wide corridor of open canopy habitats (the right-of-way; ROW) containing roadcuts and stone piles. However, exclusion fencing was constructed along the forest-ROW boundary, leaving the open canopy habitats on the road-side of the fence. Over three years, we monitored 6 rattlesnakes using radiotelemetry and found that rattlesnakes repeatedly crossed the fence to access forest-edge and ROW habitats. Rattlesnakes ostensibly crossed through damaged sections of the fence. The ROW was used most intensively by gravid females (n = 2), with their core home ranges overlapping the ROW by more than 50 percent. Despite the fence crossings, all home ranges were bounded by the highway and no rattlesnake road mortality was observed. Operative temperature models revealed that the ROW provided warmer thermal regimes that were rare or unavailable in the forest. On average, field preferred gestation temperatures (Tb = 29.7°C, SD = 1.8) could be attained or exceeded for more than 5 times as many hours per day in the ROW (7.8 hours) than in the forest (1.4 hours). Habitat selection models indicated gravid females selected warmer thermal habitats that were spatially concentrated in the ROW and edge habitats, while non-gravid snakes avoided the ROW beyond the forest edge. Habitat use within the ROW was mostly limited to rocky microhabitat structures, especially riprap stone piles and subsurface rock crevices on roadcuts, which provided buffered thermal regimes with refugia from extreme temperatures during the day and warmer Te through the night. In forested landscapes, we encourage road planners to consider whether new road corridors are likely to introduce basking sites, and if so, maintain those features on the habitat-side of exclusion fencing, and consider restoring basking sites in the surrounding forest to reduce the potential for ecological trap formation.

How Does the Living Street Environment in the Old Urban Districts Affect Walking Behavior? A General Multi-Factor Framework

To strike a trade-off between walking behavior and street resource constraint, extensive research tends to focus on how the urban environment affects walking behavior. However, most of the existing impact measurements focus on the cities in low-latitude temperate environments, which may not truly reflect the situation when assessing high-latitude cities. To address this drawback, in this paper, a general multi-factor framework is introduced to quantify the influence of street-level environmental factors on walking behavior. Specifically, a framework is constructed by comprehensively considering the subjective data and the objective data of Harbin, China, which is mainly composed of multivariate measurement indicators, a multi-source data analysis library, and four-dimensional evaluation paradigm. The results indicate that two main measures can promote the current situation of human-oriented living street environment planning, namely, increasing the distribution of green facilities and life service facilities in the old urban districts living street, and paying attention to the diversity of street greening and street landscape. The proposed framework is conducive to improve the planning status of human-centered street environments and guide the construction of pedestrian-friendly life and healthy streets.

A real-time discovery method for vehicle companion via service collaboration

PurposeVehicle companion is one of the most common companion patterns in daily life, which has great value to accident investigation, group tracking, carpooling recommendation and road planning. Due to the complexity and large scale of vehicle sensor streaming data, existing work were difficult to ensure the efficiency and effectiveness of real-time vehicle companion discovery (VCD). This paper aims to provide a high-quality and low-cost method to discover vehicle companions in real time.Design/methodology/approachThis paper provides a real-time VCD method based on pro-active data service collaboration. This study makes use of dynamic service collaboration to selectively process data produced by relative sensors, and relax the temporal and spatial constraints of vehicle companion pattern for discovering more potential companion vehicles.FindingsExperiments based on real and simulated data show that the method can discover 67% more companion vehicles, with 62% less response time comparing with centralized method.Originality/valueTo reduce the amount of processing streaming data, this study provides a Service Collaboration-based Vehicle Companion Discovery method based on proactive data service model. And this study provides a new definition of vehicle companion through relaxing the temporal and spatial constraints for discover companion vehicles as many as possible.

Post Evaluation of Rural Road Renovation and Upgrading Plans in Low Mountain and Hilly Areas Based on IF-VE Method

Currently, China is vigorously promoting the construction of "Four Good Rural Roads", and the planning and construction layout of urban and rural transportation, especially rural roads, can effectively promote the rapid integration of urban and rural areas and the coordinated development of small towns. However, there are still problems in the current planning and construction of rural roads, such as large inventory, low level, and chaotic layout. Post evaluation of rural road renovation and upgrading, analysis and evaluation of the effectiveness of the plan, can provide strong support for the subsequent adjustment of regional comprehensive transportation system construction. Based on various national, provincial, and municipal transportation development guidelines, this article analyzes the factors related to the planning and evaluation of rural roads in low mountain and hilly areas. Based on the IF-VE method formed by intuitionistic fuzzy theory and value engineering theory, a post evaluation study is conducted on a rural road renovation and upgrading project plan. The application results indicate that the indicator system and model constructed in the article have certain feasibility and applicability.

The Influence of Visual Landscapes on Road Traffic Safety: An Assessment Using Remote Sensing and Deep Learning

Rapid global economic development, population growth, and increased motorization have resulted in significant issues in urban traffic safety. This study explores the intrinsic connections between road environments and driving safety by integrating multiple visual landscape elements. High-resolution remote sensing and street-view images were used as primary data sources to obtain the visual landscape features of an urban expressway. Deep learning semantic segmentation was employed to calculate visual landscape features, and a trend surface fitting model of road landscape features and driver fatigue was established based on experimental data from 30 drivers who completed driving tasks in random order. There were significant spatial variations in the visual landscape of the expressway from the city center to the urban periphery. Heart rate values fluctuated within a range of 0.2% with every 10% change in driving speed and landscape complexity. Specifically, as landscape complexity changed between 5.28 and 8.30, the heart rate fluctuated between 91 and 96. This suggests that a higher degree of landscape richness effectively mitigates increases in driver fatigue and exerts a positive impact on traffic safety. This study provides a reference for quantitative assessment research that combines urban road landscape features and traffic safety using multiple data sources. It may guide the implementation of traffic safety measures during road planning and construction.

Ensuring the quality of atmospheric air on main streets and in residential buildings by means of planning and landscaping

Introduction. The level of concentration of toxic substances in the atmospheric air of main streets is largely determined by their aeration regime, established due to exposure to air flow of buildings and green spaces. Therefore, when developing master plans of cities and projects of detailed planning of residential formations to ensure hygienic standards for the expected content of emissions of motor transport in the air of transport communications and adjacent residential buildings, the influence of urban factors on wind speed and direction one should take into account.
 The aim of the study is the justification and selection of urban planning measures to reduce atmospheric air pollution from main roads and streets by exhaust gases of motor transport.
 Material and methods. Full-scale surveys of transport infrastructure facilities in large cities and modelling of the processes of dispersion of exhaust gases of cars in the air using models of residential buildings and green spaces.
 Results. The regularities of the formation of the aeration regime of city streets and the dispersion of car emissions behind the landscaping strips and in residential buildings have been established. Optimal variants of planning, development and landscaping of main streets have been determined, ensuring the reduction of gas contamination of pedestrian zones, public spaces and residential areas.
 Limitations. The choice of landscaping objects for urban roads and streets for field observations and modelling of car emissions dispersion processes is limited to strips of green spaces of a blown and dense construction, without taking into account the peculiarities of the transformation of the air flow and reducing gas pollution under the influence of landscaping strips of an openwork design.
 Conclusions. Reduction of gas pollution of main roads and streets is ensured by choosing the direction of the route and planning, and building techniques. At the same time, it is necessary to use environmental protection linear-strip landscaping facilities of optimal design. At the same time, it should be borne in mind that frontal multi-sectional buildings and strips of green spaces of windproof dense construction stimulate the appearance of stable vortices with a closed circulation of impurities in street canyons and on sections of highways. When choosing urban planning solutions to ensure the quality of atmospheric air of transport communications and adjacent residential buildings in various landscape and climatic conditions, it is necessary to take into account the specifics of the tasks arising in this case to regulate the aeration regime and reclamation of the microclimate as a whole.

High-Resolution Mapping of Material Stocks in Belgian Road Infrastructure: Material Efficiency Patterns, Material Recycling Potentials, and Greenhouse Gas Emissions Reduction Opportunities.

Road infrastructure is an integral part of built environment stocks, as it delivers essential social and economic services. While previous work has assessed material stocks, flows, and embodied emissions, spatially refined mapping of materials accumulated in road infrastructure can highlight hitherto underappreciated synergies between improved spatial planning, material stock efficiency, and urban mining. In this study, we mapped the materials stocked in road infrastructure across Belgium, explored the patterns of material stock efficiency and the recyclability of end-of-life road materials, and examined the greenhouse gas (GHG) emissions reductions of improving stock efficiency and recycling. We assembled data scattered across various governmental sources and crowdsourced platforms and developed a comprehensive database to warehouse locational information on road typology, layer geometry and thickness, material characteristics, traffic volume, climatic conditions, and soil conditions. Our results reveal a strong but nonlinear correlation between material stock efficiency and population density, indicating that spatial planning can reduce the required road stocks and associated GHG emissions. Urban mining potentials in road infrastructure hinge on multiple factors, such as the proximity to recycling facilities and the degradation of pavements during use. Our counterfactual analysis shows that urban road planning and reusing recycled asphalt can cut GHG emissions by up to 53 and 70%, respectively. Therefore, material-efficient road planning and improved material recycling can help realize circular economy potentials and mitigate GHG emissions moving forward.

Определение видимости в плане лесовозной автомобильной дороги методом наземной стереофотограмметрии

The article describes a method for determining the visibility on the roundings of logging roads based on the materials of ground-based photo and video recording. The essence of this method is to compare the spatial photogrammetric coordinates of the points of the visibility zone. The obstacle zone and the visibility zone are considered in the same photogrammetric coordinate system, and the design center of this system coincides with the left end of the photovideo recording basis. Studies are given to determine the magnitude of the visibility distance on the horizontal curves of logging roads in the presence of an obstacle in relation to the normal case of shooting. Measures to improve traffic conditions on the roundings of logging roads in the event of a complete or partial lack of visibility are also considered. In the course of the research, dependences were obtained to determine the value of the visibility distance by the method of ground-based stereophotogrammetry, in relation to horizontal curves in the road plan; the assessment of the accuracy of determining the distance of visibility based on the materials of ground-based stereophotogrammetry was carried out. In the case of lack of visibility on the horizontal curves of roads, dependencies are proposed to determine the area and volume of the cut, and dependencies are established to assess the accuracy of the measurements performed.

Child friendliness of rural school travel road: Improvement strategies based on rural children's perception

IntroductionIn the process of building child-friendly cities, scholars have conducted extensive research on the appropriateness of urban facilities for children in urban regions, while less attention has been paid to rural areas with large numbers of children. This study attempts to explore the friendly planning and design of rural school travel roads from the perspective of children's perception of the current environment. MethodsSixteen school route assessment indices were summarized into four categories: road characteristics (width, pavement type, maintenance, and cleanliness), basic services (sidewalks, non-motorized lanes, recreational facilities, street lights, shops), traffic safety features (traffic signals, crosswalks, speed bumps, slow/speed limit signs, traffic volume), and aesthetic elements (street trees, landscape pieces). Through a face-to-face questionnaire survey of students in 28 rural schools, 992 valid questionnaires were obtained. Then sixteen microscopic road environment indicators were classified by the IPA model, and on this basis, the TOPSIS model was used to prioritize the contents in the improvement area. ResultsThere were differences between the children's perception of the importance and satisfaction of the rural school travel environment, and the actual situation of each indicator did not reach the expected level. The priority of the five environmental factors needing improvement were sidewalks > crosswalks > slow/speed limit signs > traffic signals > speed bumps. ConclusionsInterventions should be considered from the perspective of children's perception, which can provide a reference for the optimization and upgrading of rural roads, and for the theory and practice of the further construction of child-friendly villages.

DPSDA-Net: Dual-Path Convolutional Neural Network with Strip Dilated Attention Module for Road Extraction from High-Resolution Remote Sensing Images

Roads extracted from high-resolution remote sensing images are widely used in many fields, such as autonomous driving, road planning, disaster relief, etc. However, road extraction from high-resolution remote sensing images has certain deficiencies in connectivity and completeness due to obstruction by surrounding ground objects, the influence of similar targets, and the slender structure of roads themselves. To address this issue, we propose a novel dual-path convolutional neural network with a strip dilated attention module, named DPSDA-Net, which adopts a U-shaped encoder–decoder structure, combining the powerful advantages of attention mechanism, dilated convolution, and strip convolution. The encoder utilizes ResNet50 as its basic architecture. A strip position attention mechanism is added between each residual block to strengthen the coherent semantic information of a road. A long-distance shortcut connection operation is introduced to preserve the spatial information characteristics of the original image during the downsampling process. At the same time, a pyramid dilated module with a strip convolution and attention mechanism is constructed between the encoder and decoder to enhance the network feature extraction ability and multi-scale extraction of road feature information, expand the model’s receptive field, and pay more attention to the global spatial semantic and connectivity information. To verify the reliability of the proposed model, road extraction was carried out on the Massachusetts dataset and the LRSNY dataset. The experimental results show that, compared with other typical road extraction methods, the proposed model achieved a higher F1 score and IOU. The DPSDA-Net model can comprehensively characterize the structural features of roads, extract roads more accurately, retain road details, and improve the connectivity and integrity of road extraction in remote sensing images.

PELATIHAN AUOTOCAD PERCEPAT RANCANGAN DALAM DUNIA INFRASTRUKTUR PADA FOSFAT (FORUM SILATURRAHMI FAKULTAS TEKNIK)

Construction is a design and planning of buildings, roads and bridges in a predetermined area both in urban and rural areas. Many construction constructions, be it buildings, roads and bridges are still carried out or planned manually, so it requires a long time to complete, especially in Sumenep Regency. Construction design requires accuracy and accuracy in the drawing process, and must be adjusted to the rules that apply to the construction world. The number of open land in Sumenep Regency which is an asset for the development of Sumenep Regency which every year the population is increasing. Therefore, it is necessary to improve the quality of human resources related to the design or depiction of construction with a program as a tool to accelerate a construction design. The program that will later be outlined in a framework is how to implement a construction design quickly and precisely designed with the Autocad program. Activities are carried out by means of research on how to design or draw a construction with the Autocad program, with the hope of naming the quality of human resources of the successors of construction implementers in Sumenep Regency.

Prediction of Urban Trees Planting Base on Guided Cellular Automata to Enhance the Connection of Green Infrastructure

Urbanization and climate change pose significant challenges to urban ecosystems, underscoring the necessity for innovative strategies to enhance urban green infrastructure. Tree planting, a crucial aspect of green infrastructure, has been analyzed for optimized positioning using data metrics, priority scoring, and GIS. However, due to the dynamic nature of environmental information, the accuracy of current approaches is compromised. This study aims to present a novel approach integrating deep learning and cellular automata to prioritize urban tree planting locations to anticipate the optimal urban tree network. Initially, GIS data were collated and visualized to identify a suitable study site within London. CycleGAN models were trained using cellular automata outputs and forest mycorrhizal network samples. The comparison validated cellular automata’s applicability, enabled observing spatial feature information in the outputs and guiding the parameter design of our 3D cellular automata system for predicting tree planting locations. The locations were optimized by simulating the network connectivity of urban trees after planting, following the spatial-behavioral pattern of the forest mycorrhizal network. The results highlight the role of robust tree networks in fostering ecological stability and cushioning climate change impacts in urban contexts. The proposed approach addresses existing methodological and practical limitations, providing innovative strategies for optimal tree planting and prioritization of urban green infrastructure, thereby informing sustainable urban planning and design. Our findings illustrate the symbiotic relationship between urban trees and future cities and offer insights into street tree density planning, optimizing the spatial distribution of trees within urban landscapes for sustainable urban development.

Simulation Analysis of the Efficiency of Evacuation Entrances of Strip-like Metro Commercial Streets: A Case Study of Wuhan Business District Metro Station

The high-performance evacuation of commercial streets is the primary requirement for subway planning and construction. This study introduces a simulation and analysis framework to analyze the evacuation efficiency of a strip subway commercial street with the same number of entrances and exits and different entrance positions. The study modifies the entrances/exits of strip-shaped metro business street plans in a simulation approach to analyze the variation in evacuation effectiveness under varying exit layouts, as well as the effects of different escape entries on the subway commercial street. The study aims to find the optimized spatial structure of evacuation entrances of strip-like metro commercial streets. In this simulation approach, the scenarios of different combinations of entrances and exits, the floating scenario of the number of people to be evacuated, and the scenario of adjusting the proportion of elevator personnel were simulated. Through comparing the evacuation times of these simulated layout scenarios, this study finds that equidistant interval insertion-type entrance and exit arrangements of strip-shaped metro business street plans are better suited to improving evacuation efficiency. This finding can be used as a manual to improve the evacuation capacity of subway commercial streets, which will be helpful for the planning and design of subway commercial streets.

The Effect of Rural Road Access on Rural Households Livelihood Improvement: Evidence from Selected Weredas in Amhara Regional State, Ethiopia

The development of appropriate road infrastructure is fundamental to economic growth and poverty reduction. Rural roads, especially, are especially important for economic development in rural areas. Against this background, this study aims at investigating the effect of rural road access on rural households’ livelihood improvement. Concerning the methodology, mixed research approach involving descriptive and explanatory designs was used. This study compares (using propensity score matching techniques) households located in Keble’s with road access to suitable controls. The descriptive analysis reveals that rural roads provide enhanced access to markets for inputs such as fertilizers and improved seeds, enable households to sell their produce to nearby markets, and allow to achieve additional non-farm employment opportunities, leading to a rise in income and reduce poverty. The results from econometrics analysis shows that road access positively and significantly improved the livelihood of households as measured by the livelihoods asset capital index. On the basis of their propensity score, the mean difference in the livelihood assets index between households located in Keble’s with road access and non-accessible household’s ranges up to 6% after matching. The results also indicated that women who are employed during road construction, on average, have 25% to 37% higher empowerment level than those who are not employed. This strengthens the argument for making efforts towards gender mainstreaming during rural road construction and greater engagement of women in road planning and implementation.

Perencanaan Geometrik Dan Perkerasan Lentur Jalan Wisata Lut Atas Waq Pondok Sayur Kabupaten Bener Meriah, Aceh

Jalan Wisata Lut Atas Bener Meriah Aceh is a road leading to the tourist attraction of the lake, located at 2,100 meters above sea level. The lake called Lut Atas located in Bener Meriah, Aceh, exactly in Waq Pondok Sayur Village, Bukit District. The current status of the Lut Atas Tourist Road is still in the form of a rock and gravel cover, making it difficult to access the tourist area. The purpose of this study is to calculate the throughput capacity and road age plan on the Lut Atas Tourism section, knowing the required soft pavement thickness on the Lut Atas Tourism section with the manual road design method. 2017, knows how to climb slopes and bends to ensure safety and comfort for road users. Based on the results of the 4-day LHR survey, the total number of vehicles is 125 vehicles. Calculation results of pavement thickness of Upper Lut tourist road Waq Pondok Sayur village from STA 0+000 - 3+000, with pavement thickness AC-WC 40 mm, AC-BC 60 mm, aggregate layer 400mm material (LFA) and optional 100mm backfill. The Lut Atas Tourist Trail has a geometric road plan to guide the route according to the plan of 3 bends, namely PI1 Spiral Curve (SCS), PI2 Turn Spiral Circle (SCS), Turn PI3 Spiral bend (SS). The section of Thuong Lut Tourist Road has an expected longitudinal profile of 4 vertical curves with the following details: PPV1 (vertical intersection centre) vertical convex type, PPV2 (vertical intersection centre) concave longitudinal type, PPV3 (vertical intersection centre) concave longitudinal type, PPV4 (vertical intersection centre) convex longitudinal type

Current research and progress of machine learning in traffic monitoring systems

In modern traffic environments and road construction, road monitoring is one of the most important safeguards for urban safety. Traditional image processing techniques are not suitable for comprehensive data collection and thus accurate and fast feature extraction and generalization of the massive amount of data generated. Real-time surveillance is both tedious and tiring, but vital to safety. This paper describes the traditional image and video processing techniques that have been used to monitor pavements, as well as todays means of image processing for pavement inspection, and summarize the current development based on existing literature research. The result shows that the application of these methods can lead to a better understanding of complex pavement conditions, improved road planning and design and overall safety, and even derive applications to other aspects of computer vision as well.

Sustainable Road Planning for Trucks in Urbanized Areas of Chinese Cities Using Deep Learning Approaches

Nowadays, urban areas are experiencing heavy traffic, and governments are implementing various policies to manage it. For example, in China, trucks are prohibited from entering urban areas during the daytime to reduce traffic congestion. However, we have found that this policy is not cost-efficient for logistics, which includes gas fees, air pollution fees, and wear and tear expenses, as it cannot adjust to real-time traffic conditions. To minimize logistics costs in real-time, we propose DeepPlan, a deep-learning-based model that optimizes urban planning. Our model calculates the optimal route for each truck based on real-time traffic data in urban areas. We learned the optimal route from the trace data of taxi drivers who are experienced in minimizing logistics costs. Our experimental results show that DeepPlan outperforms existing urban plans by 25% and works well in various circumstances, including different weather and unexpected events.

Evaluation of Morphometric Terrain Parameters and Their Influence on Determining Optimal Density of Primary Forest Road Network

Planning forest truck roads network involves a lot of factors that directly affect their density and length. Depending on the purpose of the forest truck road network, this number is higher or lower. Our opinion was that these factors should be divided into invariable and variable. Common parameters, regardless of the purpose of the roads, are morphometric parameters because they can limit the length and density of the network of forest truck roads due to their variety of forms. For this reason, this paper deals exclusively with the morphometric characteristics of the terrain and their influence on the density of the network of forest truck roads. The DEM of the terrain was processed with GIS software based on the seven most important influencing factors. By standardizing the criteria, the obtained maps were reclassified, and then each of the seven selected parameters was weighted with the coefficients obtained by the AHP method.In this way, a map of the suitability of the terrain for the construction and addition to the existing network of forest truck roads was obtained. The terrain is divided into 4 categories of suitability. Zero lines were drawn with GIS tools for road design. During the creation of the optimal road network, it was tested with absolute and relative openness.As a final result, each of 26 Forest Economic Areas (FEA) was assigned to one of 4 categories of terrain suitability for the construction and density of the forest truck road network. For each category of terrain convenience, the optimal absolute and relative openness is shown. Based on this work, we suggest that the use of morphometric parameters should be considered as the first step of forest road planning in other regions.

Local Perspectives on Spatial Accessibility to Market in the Afram Plains, Ghana

The capacity to reach surrounding areas from a location, commonly known as spatial accessibility, is crucial in the economic development of such a location. The Afram Plains in Ghana, despite been touted as the food basket of the country, has long struggled with poor spatial accessibility due to the lack of reliable transport infrastructure. This problem negatively impacts the movement of people and products, which ultimately hinders the economic development of the area. This research aimed at capturing the perspectives of Afram Plains' residents regarding their spatial access to nearby markets. A mixed-method approach comprising survey questionnaire, interviews, and geographic information system (GIS) was utilized. The results affirmed that movement within the area, particularly to market, is difficult. Again, due to limited transport facilities, many people resort to walking as their primary means of transportation. These findings are expected to provide some vital ideas for future road planning in the area.

Driver Decision Space Inversion Method Based on DC-GAN

In the driving process, drivers need to constantly perceive the surrounding environment to make decisions and perform operations. This cognitive space formed in the driver's mind is the driver's decision space. For the actual driving environment, factors such as complex road sign settings, unreasonable road planning, long-time fatigue driving, and reduced reaction ability of elderly drivers may interfere with the normal perception of the driver's decision space, resulting in reduced driving safety. In this paper, a driver decision space inversion method based on deep convolutional neural networks and generative adversarial networks is proposed to study driver perception in near-domain traffic scenarios. The steps of the method include: near-domain target element extraction, driving data collection, sample data generation, adversarial generative network model learning, data enhancement and decision space inversion. The experimental results show that the method in this paper can accurately identify the driver's decision space in both real and simulated driving scenarios by implementing real-time monitoring of driver perception. The method is important for studying the driver's decision space, which can promote the development of intelligent driving technology and the synergistic development of human-vehicle-road-loop. In the context of today's sustainable transportation and smart mobility, driver decision space research is not only an important basic research, but also an inevitable requirement to promote innovation and upgrading in the transportation field.