Road Alignment Research Articles

Design of Cost-Effective and Sustainable Treatments of Old Landslides Adapted to the Moroccan Road Network: A Case Study of Regional Road R410 Crossing the Rifan Structural Domain

The Moroccan road network is susceptible to multiple landslides annually, particularly in the northern regions due to high rainfall and specific geology. These events result in significant economic and social negative consequences, highlighting the need for sustainable and cost-effective solutions for network maintenance. This study outlines the methodology employed in addressing the issues within the RR410 regional road (Rifain region of Morocco), which entailed a thorough examination of the malfunctions, specific surveys, laboratory testing, and problem modeling. By incorporating long-term test-derived shear strength parameters, the model indicated that the road platform was stable, and back analysis using TALREN 4 software allows for model calibration. At kilometric point 23, using earthwork-based solutions (e.g., purging and replacing the base layer, employing granular water-insensitive substitution material) was found to provide a sustainable alternative to the expensive reinforced concrete-based solutions commonly used. Furthermore, these solutions contributed to the use of environmentally friendly and locally sourced materials. Road alignment rectification to anchor the platform in suitable soil was also an effective solution, as demonstrated at kilometric point 48. Additionally, enhancing the drainage and sanitation infrastructure, such as installing draining trenches, spurs, and reinforcing existing water structures, is a crucial aspect of addressing most landslides in the region.

Electrical Resistivity Imaging for Identifying Critical Sulfate Concentration Zones Along Highways

Assessing sulfate concentration levels and their distributions within road alignments is crucial for the design of highway projects. Sulfate minerals in soils react with calcium-based additives, leading to sulfate-induced heaving and pavement failures. However, a reasonable assessment of the extent and levels of sulfate concentration using current practices, such as conventional laboratory-based methods, is still challenging because of the spatial heterogeneity of sulfate minerals and their seasonal fluctuations. This study aims to assess the application of electrical resistivity imaging (ERI) to determine levels and distributions of sulfate concentration. Finite element and least-squares optimization were used to process the data and generate subsurface inverted resistivity profiles. Fourteen ERI surveys were carried out for two sites with a potentially high risk of sulfate-induced heaving to help determine the extent of critical sulfate concentration zones. Laboratory tests (sulfate and moisture content tests) were conducted on ten samples collected from the field sites to validate ERI findings. The results showed that electrical resistivities of critical sulfate concentration zones are significantly lower than typical ranges of electrical resistivity of earth materials because of the abundance of salt ions in pore water, which facilitates the flow of electric current. The findings of this study were consistent with laboratory test results in determining the sulfate concentration levels. This study showed that ERI successfully provides a rapid and continuous assessment of critical sulfate concentration zones within highway alignments. The findings of this study will help materials and pavement engineers determine where alternative materials and pavement designs are needed.

Hybrid Policy Model in the Land Acquisition Decision-Making Process for Toll Road Project in West Sumatra, Indonesia

This research is related to the social phenomenon of land acquisition for toll road construction. It is necessary to enrich knowledge about policy politics, especially in the decision-making process of land acquisition policies, by involving the participation of widely affected communities (hybrid policy). The implementation of land acquisition for the Sicincin-Padang toll road construction in West Sumatra relatively encounters challenges such as issues of compensation, disputes over customary land, coordination between stakeholders, and such. The purpose of this research is to formulate a hybrid policy model for the decision-making process of land acquisition for the construction of toll roads in West Sumatra. The research approach is a mixed method, a kind of concurrent triangulation, namely two-sided research conducted simultaneously so that both sides have the same emphasis (data collection and analysis techniques). Data were collected from relevant informants and respondents from affected communities (325 respondents). Data were analyzed using a soft system methodology consisting of root definition, customers, actors, transformation, worldview, owners, and environmental constraints (CATWOE) analysis. The study results explain that the implementation of land acquisition for toll roads in Indonesia and the Sicincin-Padang section of toll roads in West Sumatra has not been optimal; there are still problems such as refusal of compensation value, road alignment issues, land acquisition administration, and coordination between the central government, local government, and the community. Furthermore, based on the above findings, a hybrid policy model for land acquisition policy (especially at the planning stage) is formulated as a novel concept that can be an alternative solution to the problem of toll road land acquisition.
 
 Received: 15 January 2023 / Accepted: 20 April 2023 / Published: 5 May 2023

End-to-end BIM-based optimization for dual-objective road alignment design with driving safety and construction cost efficiency

Road alignment design is crucial to ensure driving safety. The application of BIM technology increases efficiency and reliability in the road design process. However, it is challenging to consider multiple factors in BIM-based road alignment design. This study proposed an optimization design framework considering driving safety and road construction costs using BIM. A fast and reliable parameterization method was developed for road alignment. The BIM technique was used for modeling and earthworks statistics. The automated driving simulation was performed using MATLAB to quantify driving safety, and NSGA-II was used to solve the optimal alignment. The entire data interaction procedure is end-to-end. The framework was applied to the design project of the Phnom Penh-Sihanoukville highway. The proposed optimization method results show a combined improvement of 6.6% compared to the expert design results.

Utilizing Different Machine Learning Techniques to Examine Speeding Violations

This study investigated the potential impacts on speeding violations in the United States, including the top ten states in terms of crashes: California, Florida, Georgia, Illinois, Michigan, North Carolina, Ohio, Pennsylvania, Tennessee, and Texas. Several variables connected to the driver, surroundings, vehicle, road, and weather were investigated. Three different machine learning algorithms—Random Forest (RF), Classification and Regression Tree (CART), and Multi-Layer Perceptron (MLP)—were applied to predict speeding violations. Accuracy, F-measure, Kappa statistic, Root Mean Squared Error (RMSE), Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) were used to evaluate the algorithms’ performance. Findings showed that age, accident year, road alignment, weather, accident time, and speed limits are the most significant variables. The algorithms used showed excellent ability in analyzing and predicting speeding violations. The RF was the best method for analyzing and predicting speeding violations. Understanding how these factors affect speeding violations helps decision-makers devise ways to cut down on these violations and make the roads safer.

Severity Analysis of Multi-Truck Crashes on Mountain Freeways Using a Mixed Logit Model

Many studies have analyzed the road characteristics that affect the severity of truck crashes. However, most of these studies have only examined road alignment or grade separately, without considering their combined effects. The purpose of this article is to address this gap in the literature. Our study uses truck crash data from 2015 to 2019 on freeways in the Yunnan Province of China, where the severity levels of the crashes were determined by taking into account economic loss and the number of injuries and fatalities. Our study develops three models to examine the severity of truck crashes: a multinomial logit model, a mixed logit model, and a generalized ordered logit model. The findings suggest that the mixed logit model, which can suffer from unobserved heterogeneity, is more suitable because of the higher pseudo-R-squared (ρ2) value and lower Akaike Information Criterion and Bayesian Information Criterion. The estimation results show that the combination of curve and slope significantly increases the severity of truck crashes compared to curves and slopes alone. In addition, risk factors such as crash type, vehicle type, surface condition, time of day, pavement structure, and guardrails have a significant impact on the severity of truck crashes on mountainous freeways. Based on these findings, we developed policy recommendations for reducing the severity of multi-truck collisions on mountainous highways and improving transport sustainability. For example, if possible, the combination of curve and slope should be avoided. Additionally, it is recommended that trucks use tires with good heat resistance.

Causal analysis of coach and bus accidents in China based on road alignments

Given the complexity and the difficulty of controlling contributors effectively, road passenger transport often results in serious injuries and fatalities. The purpose of this study is to identify the main contributors to coach and bus accidents and to provide policy recommendations for making improvements in accident prevention. The Driving Reliability and Error Analysis Method 3.0 (DREAM 3.0) was modified and used to analyze the contributing factors (i.e. phenotypes and genotypes in DREAM) and their casual mechanisms. By having statistical analysis and social network analysis (SNA) adopted, the main genotypes and phenotypes of the DREAM charts were identified. The results of the study showed that A2.1 (too high speed) was the key phenotype and the main genotypic process chain leading to the phenotype was “inadequate safety management → inadequate training → inadequate skills/knowledge → misjudgment of the situation → too high speed” on all types of road. For A2.1 (too high speed), C2 (misjudgment of the situation) was the dominant genotype, while N5 (inadequate safety management) was the root cause of most genotypes. This suggests that road passenger transport companies, as the responsible parties, often fail to implement or violate safety prevention and control systems. Government regulators should promote the policy system and incentivize them to fulfil their safety management responsibilities. The government should also educate the public and improve the road environment to reduce passenger-related risks and the impact of environmental factors on drivers.

A sequential exploration algorithm for the design optimization of horizontal road alignment

AbstractMost computer‐aided optimization procedures for horizontal alignment optimization of roads require the use of information such as horizontal points of intersection (PIs) to determine an alignment. In these methods, to obtain parameters such as the radius of the curve corresponding to a specific PI, the previous and next PIs must be known. In this paper, a sequential exploration algorithm (SEA) is proposed, and the algorithm continuously explores the entire optimization space through certain steps. Only the parameters of the previous node are required to determine the current node's parameters during the exploration process, avoiding the tight coupling between PIs in traditional optimization algorithms. Furthermore, the proposed SEA does not require assumptions about the positions and numbers of the PIs, and it can design near‐optimal road alignments that match geometric restrictions and automatically take transition curves into account. Another feature of the proposed algorithm is that it directly optimizes the geometric element parameters based on the actual milepost, and it is a fully collaborative optimization approach that does not require secondary optimization nesting during the optimization process. Analyses comparing the optimization effects of different algorithms are performed on a numerical case, that is, a problem of avoiding obstacles, and two actual cases from the literature, that is, a new road design problem and an existing road reconstruction problem. It is discovered that the proposed SEA results in an approximately 3% to 10% improvement in optimization effects when compared to two current cutting‐edge optimization algorithms. This work offers a new perspective on road alignment optimization by merging discrete and continuous optimizations, with a discrete component handling optimization accuracy and a continuous component handling real optimization.

Impact of road alignment on fuel consumption and gas emissions – experimental and analytical research

This research analysed the impact of road alignment on the fuel consumption and gas emissions of a vehicle driven at a free-flow speed by an 85th percentile driver. The field experiment included constant and free-flow speed rides by a personal car equipped with a high-performance (10 Hz) Bluetooth global position device and on-board diagnostics connector, with which the travel path, speed, acceleration, and consumption data were recorded. Regression analyses of the dependence of free-flow speed and fuel consumption on the geometric characteristics of the road (curvature, length, longitudinal slope, etc.) resulted in the formation of a reliable model that could compare alternative road designs for a given corridor in terms of route economy and safety. The main parameters contributing to the consumption on tangents were the slope and radii of adjacent curves. For constant speed, the slope was the only geometric parameter that had an impact on fuel consumption.

Evaluation on Lateral Stability of Vehicle: Impacts of Pavement Rutting, Road Alignment, and Adverse Weather

The combination of pavement rutting, poor road alignment, and extreme adverse weather will seriously threaten the driving safety of vehicles, whereas only a few of these factors are commonly concerned. This study aims to efficiently evaluate the impacts of various driving conditions on the lateral stability of the vehicle and produce a practical recommendation for pavement maintenance in what concerns rutting. A systematic framework was, thus, developed to conduct a comprehensive evaluation of the lateral stability of the vehicle, which incorporates a single-factor test and multi-factor test based on the stability indicators obtained from Carsim simulations. The vehicle road weather model was established in the Carsim software by considering seven factors, including driving speed, width–height ratio (WHR) of rutting sidewall, radius of circular curve, superelevation, crosswind angle, crosswind speed, and friction coefficient, respectively. The results show that the established framework behaves with satisfactory performance, regarding evaluating the effect of various impact factors on the lateral stability of the vehicle while driving across rutting. Stability indicators suddenly fluctuate in a short time, due to the instantaneous wandering behavior of crossing rutting. Additionally, the sudden fluctuation phenomenon is greatly enlarged, and the vehicle is inclined to occur with lateral instability when WHR equals 5, particularly in roll-over instability. It is recommended to concurrently confine the WHR greater than 10 and friction coefficient greater than 0.4, in order to ensuring driving stability. The multi-factor test revealed that the vehicle speed and WHR of the rutting are leading factors that affect driving stability, followed by the radius of circular curve, superelevation, crosswind angle, crosswind speed and friction coefficient, respectively, which are both essential factors for driving stability. The outcomes of this study may contribute to supplying guidelines for controlling key adverse conditions and making decisions on pavement maintenance.

Analysis Of Geometric Parameters For Increased Design Speed Of Highway-A Case Study On NH-27

Abstract: Roadway geometry design involves such as creating the road alignment and plotting the alignment profile using coordinates, stations, and elevations of points along the selected route, and designing the horizontal alignment, vertical alignment and superelevation. This study deals with the minimum standards for geometry that needs to be followed to achieve the minimum design speed of 140 Kmph. The various important factors related to Geometry of road are: - Horizontal Radius on Curves, Sight Distance on Horizontal and Vertical alignment, Superelevation, Vertical Curve length or radius, Maximum Gradient. The available Indian manuals and standards related to the Geometric design for highways is limited to the design speed of 120 Kmph. The author thinks about the setting of the base standards for the Geometric design of Highways for high-speed corridors.

Analisis Daerah Rawan Kecelakaan Lalu Lintas di Jalan S. Supriadi, Kota Malang

A traffic accident is an unexpected and unintentional road event involving vehicles with or without road users. Observations were made on Jalan S. Supriadi, Malang City with the aim of finding out the points of traffic accident-prone areas and the causes of accidents. The methods used are Equivalent Accident Number (EAN), Upper Control Limit (BKA) and Upper Control Limit (UCL). The results of the analysis show that Km 0 - 0.7 and Km 1.4 - 2.1 are black spot points where the EAN Km value is 0 - 0.7 = 115, the EAN Km value is 1.4 - 2.1 = 109 , exceeding the control limit of BKA. UCL value at Km 0 - 0.7 BKA = 75, UCL = 87 and at Km 1.4 - 2.1 BKA = 75, UCL = 86. Factors causing the accident at the black spot on Jalan S. Suoriadi Malang, the main factor is due to human error. Not careful in driving, not orderly, careless, and sleepy. In addition to this, it is also caused by road alignment factors that do not meet the requirements, there are no adequate markings and signs for non-motorized traffic, road pavement markings are not clearly visible and there is no special parking space available for vehicle stops.

Analysis of liquefaction potential in Opak Fault nearby area (case study: Solo-Yogyakarta-NYIA Kulon Progo Toll Road construction section I.2)

Construction of the Solo – Yogyakarta – NYIA Kulon Progo Toll Road Section I.2 is a part of Java's toll road network system that connects Solo and Yogyakarta. The presence of this opak fault allegedly cut the toll road alignment. Based on Indonesia's Liquefaction Vulnerability Zone Map, the alignment location is in a medium liquefaction vulnerability zone. This study aims to determine the potential of liquefaction in the construction of Solo – Yogyakarta – NYIA Kulon Progo Toll Road Section I.2 (stationing 29+000 - 36+000). The maximum peak ground acceleration on the surface was calculated using the Deterministic Seismic Hazard Analysis calculation. Calculating liquefaction potential analysis uses the simplified procedure method developed by Idriss and Boulanger. The research shows that ten borehole points with sandy soil types 2 m – 18 m below the surface have liquefaction potential. The depth of the groundwater table is between 0.2 m – 10 m below the ground surface. Based on the Liquefaction Potential Index analysis, the research location is in a low - high level of liquefaction vulnerability.

Study on Highway Alignment Optimization Considering Rollover Stability Based on Two-Dimensional Point Collision Dynamics

In order to reduce the influence of unreasonable road alignment design on vehicle driving safety, a study on road alignment optimization and vehicle driving safety based on two-dimensional point collision dynamics was carried out. First, through the two-dimensional point collision dynamics model, the relationship of the kinematic parameters before and after vehicle collision was deduced. Second, according to the vehicle–road coupling dynamic model analysis after collision, the safety threshold between the radius of the circular curve and the road superelevation was derived by taking vehicle rollover as the critical condition. Next, the road alignment optimization scheme based on vehicle rollover stability after collision was proposed. Finally, the rationality of the optimization scheme was verified by PC-Crash simulation. The simulation results showed that the proposed optimization scheme of the minimum radius and superelevation of the circular curve meets the safety requirements of vehicle rollover. This study optimized the relevant indicators of the road alignment under the premise of ensuring vehicle rollover stability and provides a reference for the improvement and optimization of road alignment design. It also has important guiding significance for the formulation of vehicle driving safety management measures.

Study on the influence of sun glare on driving safety

Sun glare affects the drivers' vision of the road traffic environment ahead, thereby introducing risks to driving safety. The angle between the sun's position and the driver's line of sight is one of the essential factors that affects the driver's perception of sun glare. Based on an analysis of the formation mechanism of sun glare, this paper proposes a subjective visual recognition scale and test method for sun glare. According to subjective experience, sun glare can be divided into disability, disturbing, and acceptable glare. Through the outdoor visual recognition test, the vertical and horizontal visual recognition angle of 24 drivers were recorded from June 1, 2019 to December 31, 2019 when the driver's glare perception was in the critical state between disturbing glare and acceptable glare on sunny days. The results revealed that as the winter solstice approached, the maximum vertical visual recognition angle decreased in the critical state between disturbing glare and acceptable glare. However, the minimum vertical visual recognition angle tended to increase. In the same month, with the increase in the vertical visual recognition angle, the horizontal visual recognition angle in the critical state between disturbing glare and acceptable glare gradually decreased. Based on the most unfavourable principle of driving vision, the angular range of sun glare that affects driving safety was identified, and it constituted a vertical visual recognition angle of γ∈[5.6°,29.0°] and horizontal visual recognition angle of φ∈[−57.7°,57.7°]. The results can provide a reference for road alignment selection and the development of anti-glare measures.

Speed Behavior of Heterogeneous Traffic on Two-Lane Rural Roads in Malaysia

Highway geometry is a significant factor that affects the efficiency and safety of highway systems. The present study aims to investigate the speed behavior of various vehicle classes on the horizontal alignment of two-lane rural roads. An automatic data collection system based on a pressure sensor was employed to collect the speed of each individual vehicle, vehicle type, and headway at seven sites in each travel direction. The 85th percentile speed under free-flow conditions was used to observe the relationship between the operating speeds of various vehicle classes at consecutive curve points and the effect of the travel direction, time of day, and curve radius on the operating speed of the vehicle. A one-way ANOVA was employed to evaluate whether there is a significant difference in speed on horizontal curves. Then, a Tukey post hoc test was used to assess the significance of the difference in speed across four classes of vehicles. The results revealed that the horizontal curve affects the operating speed for all vehicle classes. A curve radius of less than 500 m, the travel direction, and the time of day are significant variables that affect the speed of all vehicle classes. The findings from this study can provide insight to transportation engineers for safer road design of horizontal curves and to assess traffic safety based on actual speed behavior.

Study of Roadside Accident Prediction of a Multibridge and Multitunnel Section on an Expressway in a Mountainous Area

In order to ensure the roadside traffic safety of a multibridge and multitunnel section on an expressway in mountainous areas, optimize the roadside traffic facilities, and reduce the road traffic accidents caused by the overly frequent changes of the driving environment among the bridge group and tunnel group and their intervals, combined with the driving rules, the prediction model of the numbers of roadside accidents, passenger and freight vehicle accidents in a multibridge and multitunnel section on an expressway in mountainous areas is established using statistics, machine learning, and other related theories. To analyze the influence of the driving environment of the expressway on drivers’ visual, psychological, and operational characteristics, ten prediction indicators are selected from the aspects of road alignment, traffic structure, traffic environment, and weather conditions. The action mechanism between roadside accidents and the ten predictive indicators is explained by employing Spearman correlation analysis. The roadside accident prediction model based on BPNN, GA-BPNN, and PSO-BPNN are established. MAE, RMSE, and MAPE are used as the model evaluation indicators to select the optimal model. The roadside accident data including rollover, side collision, and collision with fixed objects are verified with examples using the accident patterns of Chongqing–Hunan Expressway in the past five years. The results show that (1) the roadside accidents of a multibridge and multitunnel section on an expressway in a mountainous area are comprehensively affected by ten prediction indicators, which are positively correlated with the length of road section, the proportion of curved roads, and the proportion of bridges, and the influence of the length of the road section is the greatest indicator; (2) compared with BPNN and GA-BPNN prediction models, the errors of MAE, RMSE, and MAPE of PSO-BPNN are reduced by 18.5%, 17.65%, and 24.16% on average, and the model prediction error is smaller and the accuracy is higher; and (3) the accurate prediction of the number of roadside accidents and the number of passenger and freight vehicle accidents can provide effective decision-making support for the optimization design of roadside facilities.

Evaluation of Optimal Ghat Road Alignment integrating Engineering, Environmental and Landslide Parameters using Geospatial Analysis

Roads in a hilly region contribute to significant development of the area and may cause negative impacts on the fragile environment. Optimal road alignment in the hilly region is challenging and mandates geospatial analysis that involves topographic and environmental parameters like slope, soil stability, forest cutting and obstruction to drainage. In this study, a multi-objective approach is proposed to delineate optimal road alignment in the hilly region of Sathuragiri hills, India using Geographic Information System (GIS) based integration techniques. Analytical Hierarchy Process (AHP) was used to generate suitability surfaces based on Engineering, Environmental, Landslide and Hybrid approaches. Thematic information like geology, land use, drainage network, slope, aspect, soil texture, distance from the road etc. have been generated from Remote Sensing and Collateral datasets. The suitability surfaces were generated through standardization and integration of criteria using a weighted overlay approach in the GIS environment. Alternate alignments were generated with these suitability surfaces using Dijkstra Algorithm for finding the shortest cost path. These alignments were evaluated for critical parameters like length of road, no. of bridges/culverts, area of forest cutting, area of agriculture land affected, length of road in critical slopes. The results indicate the efficiency of the hybrid approach combining the engineering, environmental and landslide risk-based parameters in the alignment planning.

Impact of pavement rutting on vehicle safety: a closed-loop assessment method

Rutting can incline to severe traffic accidents under some adverse driving conditions (i.e. curve and rain). In this paper a closed-loop assessment method is proposed to study the impact of rutting on vehicle safety. Different from most existing studies concentrating on the interaction of vehicle and rutting, driver factors were considered in the controller-vehicle-rutting pavement system (CVRS) model. Simultaneously, road alignment, rutting geometry and road wet conditions were integrated to establish the rutting pavement model. Load transfer ratio (LTR) and sideslip index (SI) were used to analyse the risk of rollover and sideslip under representative rutting scenarios. The results reveal that closed-loop vehicle is more prone to rollover than open-loop vehicle when traversing rutting on the curved road. The open-loop assessment method underestimates the impact of rutting on the stability of lane-changing vehicles. This study has potential applications for not only pavement maintenance but also accident prevention.

Form-Finding Method of Site Road from the Perspective of Meta-Design

Site road alignment is one of the main elements of architectural environmental design [B. Holdsworth, Refocus 6(1) (2005) 58–60]. It is difficult for traditional methods to achieve both qualitative exploration and quantitative optimization objectives, and optimization algorithms can only optimize quantitative objectives. On the other hand, the shape of the site road is subject to various other human interventions besides the designer, which is a multi-objective problem. Based on the idea of meta-design, this paper proposes a new method for “form-finding” of site roads. This method develops the architecture and components of an expert system, which can handle both qualitative and quantitative objectives in conceptual design, and can realize various human interventions. Component development combines site specification, recursive algorithm, and genetic algorithm, which treats human intervention as a factor of variation, allows for qualitative exploration of different preferences, and finally demonstrates the capabilities of this new approach through case studies.