Existing Road Network Research Articles

Expanding the Accessible Forest Areas by Improving Forest Road Standards and Utilizing Mobile Fire-fighting Teams

In Turkey, most of the roads (66%) in forests consist of Type-B secondary forest roads with limited technical standards. The lack of technical standards used on these roads and the lack of road structures and surface material limit the fire truck’s speed and increase the travel time of the firefighting team. Improving forest road standards will contribute to driving safety and increasing the design speed, thereby expanding the forest areas that can be reached within the critical response period, reducing possible wood raw material losses. There is no study in the national and international literature investigating the contribution of forest road standards improvement to firefighting activities and the effects on possible wood raw material losses due to forest fires. In this study, it was aimed to investigate the effects of improving forest road standards on expanding accessible forest areas within the critical response time, especially in forests with high fire risk, and thus reducing potential wood raw material losses. Antalya Forestry Regional Directorate, where forest fires are seen most frequently and the amount of burned area is the highest in Turkey, was selected as the study area as one of the forest regional directorates where forest fires are seen most frequently and the amount of burned area is the highest in Turkey. In the solution process, primarily the forest areas that can be reached by the firefighting team (including mobile teams used in emergencies) within the critical response time were determined by considering the existing road network in the study area. Then, the possible increase in the accessible forest areas was investigated when the road standards are improved. Within the scope of the study, the impact of mobile teams used in emergency situations on forest areas reached during the critical response period was also evaluated. According to the results, in the scenario where current road standards and stationary teams were evaluated, it was determined that only 59.54% of the forest areas could be reached by initial response teams during the critical response time, and if road standards were improved, this rate increased to 71.69%. On the other hand, in the scenario where current road standards and stationary and mobile teams were evaluated together, it was determined that 70.40% of the forest areas could be reached by initial response teams during the critical response time, and if road standards were improved, this rate increased to 78.17%. The results obtained have shown that improvements in road standards and the presence of mobile teams have a very effective role in combating forest fires.

Escape routes and safe points in natural hazards. A case study for soil

The scope of this work was to develop soil liquefaction and landslide hazard maps, by computing Peak Ground Acceleration (PGA) for a return period of 475 years, to outline safe points and escape routes designed for schools situated in the drainage basin of Xerias River at northeastern Peloponnese, Greece. The school locations were spatially correlated with each geohazard map to assess the potential hazards to schools within the study area. Web maps illustrating safe and unsafe areas for both geohazards were developed though the GIS online platform for the town of Corinth and four settlements of the study area, where schools exist. Safe points were identified, and routes for evacuation from schools to these locations were mapped using the shortest paths on the existing road network for each geohazard. All the data was integrated into the GIS application available to the public. The findings indicated that 75% of the schools in the study area are situated in areas susceptible to soil liquefaction and landslide hazards. The northern part of the town of Corinth, which includes 62% of the town's schools, is situated in unsafe areas to soil liquefaction. Unsafe areas for landslides are located in the central and northern section of the town, encompassing 35% of the schools. The school buildings in one settlement within the study area are situated in safe areas for both geohazards. The schools in the remaining settlements are sited in areas considered unsafe due to either liquefaction or landslides hazard. A total of 12 safe points were proposed for soil liquefaction hazard and 17 for landslide hazard across all the studied urban areas. The suggested escape routes for both geohazards range from 200 to 1094 m, distances that teachers and students can easily walk. The proposed method can rapidly and effectively identify safe locations and evacuation routes, facilitating authorities in planning for evacuations.

Climate change impact and adaptation assessment for road drainage systems

Climate change exhibits a clear trend of escalating frequency and intensity of extreme weather events, posing heightened risks to drainage systems along the existing road networks. However, very few studies to date have investigated the consequences of projected future changes in rainfall on main road drainage and the resulting risk of road flooding. The work presented in this paper builds on the limited research by introducing a probabilistic model for assessing the impact of climate change on road drainage systems, incorporating climate uncertainty and drainage system variation. The probabilistic scenario-based model and associated framework offer a practical and innovative method for estimating the impact of short-duration storms under future climates for 2071–2100, in the absence of fine-resolution spatio-temporal data. The model also facilitates the assessment of the effectiveness of a climate adaptation strategy. An illustrative case-study of a road drainage system located in the south of Ireland is presented. It was found that the probability of road flooding during intense rainfall is projected to surpass the current acceptable limits set by Irish standards. Assessment of a proactive climate adaptation strategy implemented in 2015 indicated it may need to be adjusted to further reduce climate change impacts and optimise adaptation costs.

Traffic emissions before and after development based on traffic impact assessment

Abstract Traffic impact assessment evaluates the traffic conditions in the vicinity before and after the completion of a new development as new development will generate additional vehicle trips on the road and contribute to a rise in traffic emission. Thus, this study aims to evaluate the impact of the proposed development in Nibong Tebal, Penang, on the existing road network and identify the necessary improvements to ensure all intersections perform satisfactorily. Additionally, the impact of the proposed intersection’s design on fuel consumption and traffic emissions will also be investigated. During morning and evening rush hours, six hours manual vehicle counts were conducted at ten intersections. The collected data is then analyzed to determine the performance of the intersection. The level of service, based on the delay and ratio of volume over capacity of a turning movement, is used as the performance indicator for intersections. This study revealed that the reduction of delay time of more than 100 seconds at signalized intersections can significantly reduce fuel consumption and traffic emissions. In conclusion, a well-designed intersection will facilitate traffic movement and reduce traffic emissions which will eventually reduce the quantity of greenhouse gases released into the atmosphere that contribute to global climate change.

A Research on Determining the Importance Levels of Criteria Effective in Forest Road Network Planning through GIS-Based Methods

This study investigated the importance levels of criteria effective in forest road network planning using Geopraphic Information System (GIS)- based Multi- Criteria Evaluation (MCE) method. It is crucial to determine the criteria to be considered in forest road construction and planning for a standardized application nationwide. The research was conducted within the boundaries of the Yaylacık Forest Management Directorate (YFMD) under the Tokat Forest Management. Firstly, the existing road network was identified in the research. After the identification of the existing road network, a GIS database was created. In this study, criteria to be used, in Forest Road Network Planning (terrain slope, aspect, road density, distance to road, land use, distance to main stream) were determined. Each criterion was classified and scored internally. Information from road and road network planning studies and previous works were utilized in determining the criteria to be used in Forest Road Network Planning. Five different degrees and suitability values are defined for the determined criteria. In this context, it was created to reach 5 fundamental road network planning functions to determine their positional statuses as Absence (Ab), Very Suitable Areas for road planning (VS), Suitable Areas for road planning (S), Less Suitable Areas for road planning (LS), and Very Less Suitable Areas for road planning (VLS). As a result, Terrain Slope and Road Density were determined as the most effective criteria in Road Network Planning, while Distance to Main Stream was identified as the least effective criterion. As a result of the study, a flow chart was created to determine the criteria and impact values that are effective in forest road network planning in order to ensure integrity and convenience in application throughout the country.

A comprehensive study incorporating structural equation modeling and factor analysis study on the evaluation of performance criteria for infrastructure development projects

Infrastructure development projects are vital for economic growth and societal well-being for every phase of any futuristic growth in the region, city, or country as its backbone in structure development, but their success hinges on effective performance evaluation. The present research employs a thorough methodology that integrates Structural Equation Modeling (SEM) and Factor Analysis decision-making tools to examine the interdependencies and comparative significance of diverse performance standards for infrastructure development initiatives. Research has been carried out through numerous parameters on sustainable dimensions in terms of usage as service providers and users. The user’s effect in understanding the endogenous and exogenous factors like traffic flow restrictions, road conditions in the existing road network, AQI (Air Quality Index), urbanization, Los (Level of Service) for roads, travelers characteristics, and interconnected parameters. To identify important dimensions and latent elements that have a substantial impact on the overall success of the project, factor analysis will be used concurrently. The research attempts to identify hidden variables and complex interactions that influence project outcomes through this dual-method approach. Key findings will illustrate the significance for stakeholders to be involved in the project planning process, to take the environment into account, and to ensure the project’s financial viability. Additionally, the study finds both competitive and complimentary correlations between various performance metrics, reinforcing the significance of an extensive assessment strategy.

Analisis Dampak Lalu Lintas Pasar Ngablak Kabupaten Magelang

Changes in the structure of urban space will affect movement patterns, ultimately burdening the existing road network in an area. Traffic Impact Analysis (TIA) is an analysis of the influence of land-use development on the system of traffic flow movement around the development; this is caused by the emergence of new traffic, shifting traffic, and vehicles coming in and out of or to the development land. The construction of Pasar Ngablak can have a new traffic impact and increase the traffic load around the market, disrupting traffic links that can reduce the level of road services. This study aims to analyze the impact of market development activities that are useful to minimize traffic impact and provide appropriate recommendations. The research method used was the approach of the 1997 Indonesian Road Capacity Manual (MKJI, 1997), with the results of the delay value and degree of saturation. The results of the delay value and degree of saturation are used to see the existing conditions and during operation. However, predictions for the next 5 (five) years after development need to be watched out for and given appropriate recommendations because there is an increase in traffic movement around the market

Electrifying an urban delivery fleet: a case study

When carriers consider electrifying their delivery fleets, it is not only a societal and moral obligation, given road traffic's impact on emissions. It has also become an economic consideration as sustainability metrics can result in investment, and the life-cycle cost of electric vehicles is becoming more attractive. In this paper, we report on an actual case of a South African pharmaceutical company considering replacing and electrifying its current delivery fleet. The paper uses an agent-based simulation approach that models each delivery vehicle on an existing road network. Each vehicle's emissions characteristics are known, and its spatiotemporal movement results from solving a variant of the well-known routing problem. Vehicle movements are coupled with a detailed database of emissions factors to estimate the total emissions per vehicle per link, which can then be aggregated to any required level. The results show that electrifying an entire fleet may not be viable initially, suggesting a hybrid fleet as a more practical intervention in the foreseeable future.

Map Matching Based on Seq2Seq with Topology Information

Most existing road network matching algorithms are designed based on previous rules and do not fully utilize the potential of big data and historical tracks. To solve this problem, we introduce a new road network matching algorithm based on deep learning and using the topology information of the road network. Taking inspiration from the sequence-to-sequence (seq2seq) model popular in natural language processing, our algorithm builds multiple grid-dependent dictionaries based on the topology of road networks. Then the Byte Pair Encoding (BPE) algorithm is used to compress the grid dictionary, which effectively restricts the output range. A Bidirectional gated loop unit (Bi-GRU) with attention mechanisms is used as a recurrent neural network to capture information from a sequence of trajectory points. The model output feedback obtained by training the road network on Yibin City and the empirical evidence of the comparison in this experiment prove the effectiveness of the algorithm. When juxtaposed with similar algorithms, it shows superior accuracy and faster training speeds in road networks matching different scenarios.

Optimizing Wildfire Prevention through the Integration of Prescribed Burning into ‘Fire-Smart’ Land-Use Policies

Integrating fire into land management is crucial in fire-prone regions. To evaluate the effectiveness and efficiency of prescribed fire (PF), we employed the REMAINS model in NW Iberia’s Transboundary Biosphere Reserve Gerês-Xurés. We tested three levels of prescribed fire treatment effort for shrubland and grassland, employing three spatial allocation strategies: random distribution, prioritization in high-wildfire-risk zones, and creating fuel breaks by utilizing the existing road network. These approaches were assessed in isolation and in combination with three land-use scenarios: Business-as-usual (representing rural abandonment trends), High Nature Value farmland (reversing farmland abandonment), and Fire-Smart forest management (promoting fire-resistant landscapes). Our results confirm that PF is effective in reducing future wildfires (reductions up to 36%), with leverage values ranging from 0.07 to 0.45. Strategic spatial allocation, targeting wildfire-risk areas and existing road networks, is essential for maximizing prescribed fire’s efficiency (leverage effort of 0.32 and 0.45; i.e., approximately 3 ha of PF decrease subsequent wildfire by 1 ha). However, the PF treatments yield the best efficiency when integrated into land-use policies promoting ‘fire-smart’ landscapes (reaching leverage values of up to 1.78 under policies promoting ‘HNVf and ‘fire-smart’ forest conversion). These recommendations strengthen wildfire prevention and enhance landscape resilience in fire-prone regions.

A Regional Road Network Capacity Estimation Model for Mountainous Cities Based on Auxiliary Map

The focus of sustainable urban transportation development lies in realizing the untapped capacity potential of the existing road network and enhancing its operational efficiency without expanding its physical footprint. To quantify the supply capacity of road networks in mountainous cities, this paper converts the problem of solving the capacity of road networks into the problem of solving the minimum cut set in road networks from the perspective of road network capacity, using the idea of the auxiliary diagram method in graph theory. By improving the limitation that the auxiliary map method is only applicable to the single starting point and terminal point network, a regional road network capacity estimation model of a mountain city based on the auxiliary map is constructed. Combined with the actual regional road network, the model results presented in this paper show that the road network capacity calculated by the auxiliary graph method is 30,137 pcu/h. Using the improved traffic distribution simulation method, the network capacity is 38,776 pcu/h. Compared with the traffic distribution simulation method, the regional road network capacity model based on an auxiliary map proposed in this paper is more realistic.

Efficiently computing alternative paths in game maps

Alternative pathfinding requires finding a set of k alternative paths (including the shortest path) between a given source s and a target t. Intuitively, these paths should be significantly different from each other and meaningful/natural (e.g., must not contain loops or unnecessary detours). While finding alternative paths in road networks has been extensively studied, to the best of our knowledge, we are the first to formally study alternative pathfinding in game maps which are typically represented as Euclidean planes containing polygonal obstacles. First, we adapt the existing techniques designed for road networks to find alternative paths in the game maps. Then, based on our web-based system that visualises alternative paths generated by different approaches, we conduct a user study that shows that the existing road network approaches generate high-quality alternative paths when adapted for the game maps. However, these existing approaches are computationally inefficient especially when compared to the state-of-the-art shortest path algorithms. Motivated by this, we propose novel data structures and exploit these to develop an efficient algorithm to compute high-quality alternative paths. that shows that the existing road network approaches generate high-quality alternative paths in game maps. Our extensive experimental study demonstrates that our proposed algorithm is more than an order of magnitude faster than the existing approaches and returns alternative paths of comparable quality. Furthermore, our algorithm is comparable to a state-of-the-art shortest path algorithm in terms of running time.

Evaluating Roads Network Connectivity for Two Municipalities in Baghdad-Iraq

The road network serves as a hub for opportunities in production and consumption, resource extraction, and social cohabitation. In turn, this promotes a higher standard of living and the expansion of cities. This research explores the road network's spatial connectedness and its effects on travel and urban form in the Al-Kadhimiya and Al-Adhamiya municipalities. Satellite images and paper maps have been employed to extract information on the existing road network, including their kinds, conditions, density, and lengths. The spatial structure of the road network was then generated using the ArcGIS software environment. The road pattern connectivity was evaluated using graph theory indices. The study demands the abstraction and examination of the topological structure by choosing a few factors associated with the connection of the roads. These involved the cyclomatic number, Eta coefficient, Aggregate Transform Score (ATS), Beta, gamma, and Alpha indices. According to the findings, the Al-Adhamiya roads network is more developed, better linked, and has a higher overall connectivity value than the Al-Kadhimiya network. The two study areas, however, have minimal circuitry and high complexity. Due to the modifications and expansion of land use that the municipalities have seen, the research suggests that the transportation network should be developed to reach greater interconnectedness, particularly in locations outside the city center.

Modeling Automated Driving in Microscopic Traffic Simulations for Traffic Performance Evaluations: Aspects to Consider and State of the Practice

The gradual deployment of automated vehicles on the existing road network will lead to a long transition period in which vehicles at different driving automation levels and capabilities will share the road with human driven vehicles, resulting into what is known as mixed traffic. Whether our road infrastructure is ready to safely and efficiently accommodate this mixed traffic remains a knowledge gap. Microscopic traffic simulation provides a proactive approach for assessing these implications. However, differences in assumptions regarding modeling automated driving in current simulation studies, and the use of different terminology make it difficult to compare the results of these studies. Therefore, the aim of this study is to specify the aspects to consider for modeling automated driving in microscopic traffic simulations using harmonized concepts, to investigate how both empirical studies and microscopic traffic simulation studies on automated driving have considered the proposed aspects, and to identify the state of the practice and the research needs to further improve the modeling of automated driving. Six important aspects were identified: the role of authorities, the role of users, the vehicle system, the perception of surroundings based on the vehicle’s sensors, the vehicle connectivity features, and the role of the infrastructure both physical and digital. The research gaps and research directions in relation to these aspects are identified and proposed, these might bring great benefits for the development of more accurate and realistic modeling of automated driving in microscopic traffic simulations.

Capacity of a constrained urban airspace: Influencing factors, analytical modelling and simulations

The traffic density of small aerial vehicles operating within urban environments is expected to increase significantly in the near future. This urban environment is highly constrained due to being limited to the low-altitude airspace directly above the existing road network. Multiple studies have addressed factors influencing the capacity of urban airspace. These have used simulations of aircraft, yet the empirical nature of these simulations limits their use beyond the specific conditions that have been tested. Analytical models would not have this limitation, but they are only developed for general airspace, while the emergent patterns in constrained urban airspace are different than in general, unconstrained conditions. For instance, queuing and local congestion are patterns that are unique to the heavily-constrained environment. Therefore, in this paper, we derive an analytical model for air traffic in a confined airspace to find the influencing factors for its capacity. By means of a simulation of aerial vehicles, we verify the analytical model and show a relationship between the mean flow rate and mean density in a two-dimensional orthogonal grid network airspace. Results show that the entire airspace can become unstable when the maximum capacity of just one intersection is reached. Furthermore, the maximum airspace density is found to be unaffected by cruise speed. The results demonstrate how the derived analytical model provides an effective tool to predict the effect of several design parameters on the capacity of constrained urban airspace. Moreover, this model can form the basis for further extensions, including the altitude dimension and non-orthogonal or non-four-way intersections.

Urban Road Network Serviceability Analysis Using Traffic Flow Profiles

Urban road networks are lifelines for cities in fulfilling the transportation needs of their inhabitants. The Patna Urban Agglomeration Area (PUAA) lacks properly planned roads; many of them have varying widths, with encroachments that reduce effective road width. A serviceability analysis is required through a traffic survey in order to create a traffic flow profile. This profile aids in performing time-based path, elevation, and serviceability analyses. In this study, traffic data were collected using cameras at vital road junctions and signals. A manual traffic survey was conducted at locations where active traffic was observed during peak hours. The road network of the study area was created using Google Maps, digitizing roads as lines and utilities as points. The traffic survey data, the road network, and the utilities were analyzed in the Network Analyst tool of the ArcGIS software. The analyses revealed suitable routing at underpass and overpass, as well as feasible paths during peak hours and locations with poor utility access. The analysis focused on the low-income group of people who depend on public transport and utilities and are the driving force of a developing economy. Suitable solutions are suggested to improve the existing road network.

Updating forest road networks using single photon LiDAR in northern Forest environments

Abstract Knowledge about the condition and location of forest roads is important for forest management. Coupling accurate forest road information with planning and conservation strategies supports forest resource management. In Canada, spatial data of forestry road networks are available provincially; however, they lack spatial accuracy, and up-to-date information on key attributes such as road width is missing. In this study, we apply a novel approach to update forest road networks and characterize road conditions in Ontario’s Boreal and Great Lakes—St. Lawrence (GLSL) Forest regions. We use airborne laser scanning (ALS), to facilitate the identification of forest roads across densely forested landscapes. We categorized roads into four classes based on driveable width, edge vegetation, as well as surface and edge degradation as derived from high-density Single Photon LiDAR (SPL) data. Using a novel road extraction method, we produced a road probability raster and map road centerlines. We validated road location and attribute information using Global Navigation Satellite System (GNSS) ground truth data in two Ontario forest management units, in the boreal forest and the GLSL. Road segments in some regions have been altered to account for land cover changes, such as flooding or fallen trees. In other situations, the road path may deviate from the planned layout of the road, which is not always followed in the field. Our results highlight inaccuracies in the existing road networks, with 30 per cent of ‘Full access’ roads and 29 per cent of ‘Partial access’ roads being undriveable by standard vehicles and 45 per cent of ‘Status unknown’ roads, which make up 48 per cent of the pre-existing network, being driveable by standard vehicles. Results show that the average positional accuracy of updated road centerlines is 0.4 m, and the average road width error is 2 m. The production of spatially accurate forest road networks and road attribute information is important for characterizing large road networks for which often minimal information is available.

A hybrid bacterial foraging – simulated annealing framework for improving road networks

Effective techniques for reducing traffic congestion include adding new edges to the road network or increasing the capacity of existing edges. To determine the optimal set of improvements that can be made to an existing road network, it is standard practise to solve a Discrete Network Design Problem. Due to the bi-level nature of its formulation, it is one of the most difficult problems to solve to optimality. The Bacterial Foraging Optimization technique has been investigated in a previous work to gauge its effectiveness in determining the n-optimal solution to the Discrete Network Design Problem. This concept is further developed in this paper by hybridizing the Bacterial Foraging Optimization algorithm with Simulated Annealing. In the elimination step, the metropolis criterion from Simulated Annealing ensures a more diverse search of the solution space. We also employ a modified candidate set of improvements that incorporates both edge and capacity additions. The effectiveness of the hybrid bacterial foraging optimization algorithm in determining n-optimal solutions to the Discrete Network Design Problem has been demonstrated by testing it on the 24-node, 76-arc Sioux Falls network.

Infrastructure requirements for the safe operation of automated vehicles: Opinions from experts and stakeholders

The need to future-proof road transport networks is becoming increasingly urgent in order to take full advantage of automated vehicles (AVs). It is now vital to understand the basic road infrastructure requirements of AVs in order to assess the readiness of the existing road network and prepare the roads for the safe operation of these vehicles. However, current literature on this subject is limited. As such this research seeks to understand the desired infrastructure-related requirements of highly automated vehicles (SAE Level 4) for safe operation based on a survey with experts and stakeholders. On the basis of 168 expert responses from 29 countries, this study presents stakeholders’ views on: (1) deployment paths of Level 4 automated driving, (2) the concept of road certification for automated driving, (3) basic road infrastructure elements for the safe operation of automated driving, and (4) factors affecting safe operations of Level 4 automated driving. The findings show that different types of stakeholders (e.g. academics, infrastructure owners and operators, and vehicle and information technology developers) have broadly similar views on most criteria requiring consideration in the early stages of automated driving implementation. However, there is no clear consensus on issues regarding operating constraints on road networks and some are in favour of waiting for the technology to mature or until it proves beneficial to overall community goals and then acting on the infrastructure needs.

Assessment of radius of curvature along the existing road networks

Assessment of radius of curvature along the existing road networks