Two-lane Highways Research Articles

An Artificial Neural Network Model for Short-Term Traffic Flow Prediction in Two Lane Highway in Khulna Metropolitan City, Bangladesh

Short-term traffic flow prediction is one of the most significant research topics in traffic engineering. It is instrumental in designing a more modern transport network to manage traffic signals and reduce congestion. Short-term traffic flow is a challenge that a third-world country like Bangladesh is all too familiar with. Like the other cities of Bangladesh, Khulna Metropolitan City is gradually becoming more aware of this situation. The Khulna-Jashore National Highway (N-7), which runs through the city and provides a linear shape, serves as the backbone of the Khulna Metropolitan City traffic flow. This study developed an Artificial Neural Network (ANN) model for the short-term Traffic Flow Prediction on Two-Lane Highway in Khulna Metropolitan City, Bangladesh. Data was collected from March 1, 2021, through June 30, 2021, during 600–900 hours and 1200–1500 hours. Good-quality electronic cameras recorded the vehicles at the full designated length. The regression graphs displayed the network outputs with targets for the training, validation, and test sets. The various speed level parameters for which the fit is reasonable for all data sets, with R values of 0.98426 in each case. The various traffic volume parameters for which the fit is reasonable for all data sets, with R values of 0.96758 in each case. The model's superiority is indicated by its low mean squared error values. This study demonstrated that the neural network has a good prediction effect on specific road traffic flow, which can achieve the goal of short-term prediction and has improved practicability through testing on real traffic data. This study provides an opportunity to provide a suitable alternative for short-term traffic flow forecasting in Khulna Metropolitan City with traffic flow conditions for two-lane undivided highways.

Influence of horizontal alignment elements on operating speed of vehicles on two-lane highways

Earlier studies acknowledged that the design speed does not principally assure consistency in the design of highway geometric elements. Methodologies for estimating operating speeds are limited to specific or local traffic conditions and design standards, as in various studies conducted on two-lane and multi-lane highways. The present study develops operating speed models of the vehicle types observed on horizontal curves and tangent sections on two-lane highways in southern parts of India. Geometric features of the curve section and adjacent tangent sections, such as the radius of the curve, curve length, deflection angle, degree of curvature, gradient, carriageway width, and shoulder width, are obtained from the field. The speed data collected at 24 locations on the highway, including curved and tangent gradient sections, are used to analyze and model operating speed. The results indicate that the inverse of the square root of the radius appears to be an influencing parameter for modeling the operating speed of vehicles. The operating speed is sensitive for a curve radius of up to 600 m; thereafter, the operating speed appears insignificant. On tangent sections, the gradient has a larger influence on the operating speeds of all vehicle types. The operating speed models are validated and compared with models available in the literature. The proposed models developed in the present study are helpful to traffic engineers for predicting the operating speed on two-lane highways.

Environmental impacts from traffic on highway construction work zones: Framework and simulations

Emissions from internal combustion engine vehicles on highways are the major contributors to global warming in the United States. Transportation sector pavement-related emissions come from gasolines and diesel use in vehicles from pavement-vehicle interaction, which is affected by pavement conditions, and by the trucking of new pavement materials and demolition. The objective of this study was to develop a framework for determining the fuel use resulting in environmental impacts caused by construction work zones (CWZs) on a range of vehicles and to produce initial calculations of these impacts by modeling traffic closure conditions for highway maintenance and rehabilitation activities. The study included two common highway categories—freeways/multi-lane highways and two-lane highways. The framework was demonstrated using three CWZ operations under different traffic congestion levels. In the simulation results for a freeway with a CWZ and heavy congestion, fuel consumption increased by 85% and the carbon-dioxide equivalent emissions increased by 86%. Changing CWZ traffic congestion from heavy (average speed 5 mph) to medium (average speed 25 mph for a freeway section) reduced fuel consumption by 40% on a freeway. This study also included use of a pilot car in a CWZ on a two-lane road typical of lower traffic volume state highways and county roads to compare with the drive cycles in MOVES used for the scenarios. The pilot-car operation scenario results indicate that a one-lane closure with pilot-car operation on a two-lane road might consume 13% excess fuel because of idling time and the slow movement of vehicles following the pilot car.

Determination of Passenger Car Unit and Capacity at Grades of Two Lane Undivided Highway: A Case Study of Khurkot–Dhulikhel Section of BP Highway

The majority of Nepal’s National Highway and feeder road system comprises two-lane highways with heterogeneous traffic conditions. Factors such as lane width, gradient, lateral clearance, and shoulder conditions can influence the passenger car unit (PCU) and roadway capacity. Recognizing that grade magnitude (%) is an important yet unexplored roadway factor in Nepal, and the present study primarily aims to estimate the passenger car unit on two-lane undivided hilly roads with gradients under prevailing heterogonous traffic conditions. This study aims to determine the PCU values and roadway capacity at grade under mixed nature traffic flow for a two-lane undivided highway. In this research, the necessary data were collected at five sections of BP highways using a digital video recorder, which was then analyzed to assess traffic characteristics and calculate PCU values. Using the PCU values, the road capacity was estimated using Greenshield’s model. For capacity estimation, flow and density were addressed using dynamic PCU values. This study reveals that the PCU of all categorized vehicles increases linearly with the increase in gradient while roadway capacity decreases with an increase in grade. It was observed that PCU values obtained for two-wheelers in all sections are smaller than the PCU values specified in NRS 2013, whereas for buses, trucks, and LCVs, they are higher than the PCUs given in NRS 2013. The study highlights the impact of road grade on the PCU for different vehicle categories on a highway. Additionally, the study demonstrates that the developed capacity values are realistic and consistent with the values presented in the Highway Capacity Manual (HCM) of developing countries such as Indonesia and China. These results are expected to be beneficial for practitioners and the ongoing effort to develop a highway capacity manual.

Critical radius prediction for small radius curved section of two-lane secondary highways based on speed characteristics

Small radius curved sections of two-lane secondary highways have low technical indicators, complex alignments, and frequent accidents. In order to improve the safety of traffic operation, the article investigates the curved sections of two-lane secondary highways with different radii and obtains the travelling speeds of different vehicle types at different section locations. By studying the trajectory characteristics and speed characteristics of vehicles travelling in curves, the velocity difference ratio, which responds to the continuity of driving speed, was defined. Then, based on this, this paper investigates the vehicle motion law of small radius curved road sections. The results show that the speed change of large cars in small radius curves is similar to a “U" shape, while the speed change of small cars is similar to a “V" shape. The speed adjustments of the larger cars occur mainly within the range of gentle curves, whereas the speed changes of the smaller cars are large throughout the range of curves. There is a significant exponential function relationship between curve radius and 85 % percentile speed, from which the curve radius threshold can be predicted. This provides a basis for engineering construction of curved road sections and optimization of curve design indicators, which greatly improves the traffic safety level of curved road sections.

Calibration and development of safety performance functions for two-way stop-control intersections on rural two-lane highways in Louisiana

The first edition of the Highway Safety Manual (HSM) contains a simplistic version of the crash prediction model for two-way stop-controlled intersections (TWSC) on rural two-lane highways. This model considers AADT on major and minor roads, with the base conditions defined as no intersection skewness, no turning lanes, and no lighting. A crash modification factor (CMF) will be applied if an intersection has conditions different from the base condition. However, the HSM model does not take account of curvature. It is well known that curved TWSC intersections are less safe than non-curved ones, particularly on rural two-lane roadways. This paper presents the development of crash prediction models incorporating intersection geometrics for TWSC intersections on rural two-lane highways in Louisiana. Then, it compares the results from the developed model with the calibrated HSM model. The negative binomial model was used with 5126 TWSC intersections verified one by one, including both three- and four-leg intersections from all parishes (counties). The estimation results indicate that AADT, curve radius, and intersection skewness angle significantly impact expected crash frequency for both three- and four-leg intersections. This research utilizes cumulative residual plots, mean absolute error, and root mean square error for comparative analysis of HSM models, HSM models with calibration, and Louisiana-specific models. The results show that Louisiana-specific SPFs outperformed the calibrated SPFs with superior reliability. Calibration factors of 0.58 for three-leg intersections and 0.46 for four-leg intersections are estimated, suggesting that the original HSM model overpredicts crashes in Louisiana.

Overtaking maneuvers on two-lane highways under the microscope: Exploration of a multidimensional framework for the analysis of safety, comfort and efficiency using simulator data

An unreasonable overtaking attempt on two-lane highways could cause drivers to suffer in terms of driving safety, comfort, and efficiency. Several external factors related to the traffic environment (e.g., speed and car type of surrounding vehicles), were found to be the significant factors in drivers’ overtaking performance in the previous studies. However, the microscopic decision-making (e.g., the moments of the occupation of the opposite lane) mechanisms during overtaking, by means of which drivers react to changes in the external traffic environment and adjust their overtaking trajectories, are still need to be explored. Hence, this study had three goals: (i) To explore the spatial characteristics of micro-decisions (MDs) (such as the start and end point) in overtaking trajectories; (ii) To measure three types of performance indicators (i.e., safety, comfort, and efficiency) for the execution of overtaking maneuvers; (iii) To quantitatively explain the microscopic decision-making mechanism in overtaking. Data for overtaking trajectories were collected from driving a simulation experiment where 52 Chinese student drivers completed a series of overtaking maneuvers on a typical two-lane highway under different traffic conditions. Two analyses were conducted: firstly, the distributions of the relative distance between the ego and surrounding vehicles at four key points (i.e., the start, entry, back, and end) in the overtaking trajectory were investigated and clustered to uncover the spatial characteristics of the MDs. Secondly, the safety, comfort, and efficiency of the overtaking were measured by the aggregations of multi-targets collision risks, triaxial acceleration variances, and spatial consumptions respectively based on the Data Envelopment Analysis (DEA), which were further applied in a two-stage SEM model to reveal the quantitative interrelationships among the external factors, microscope decisions and performances in overtaking. We confirmed that the MDs could be considered as the mediating variables between the external factors and overtaking performances. In the presence of the more hazardous traffic environment (e.g., faster traffic flow and impeded by a truck), the safety, comfort and efficiency of overtaking would be deteriorated inevitably. But drivers would execute the overtaking under the longer passing sight distance, migrate their trajectories forward, and shorten the spatial duration to significantly improve the overtaking performances. Based on this mechanism, a overtaking trajectory optimization strategy for the advanced or automatic driving system, was confirmed and concluded that 1) the passing gap should be firstly planned according to the sight distance acceptance of different drivers, which directly determine the upper limit of the safety performance in the overtaking; 2) the trajectory forward migration and shortening the whole duration in overtaking could be effective to enhance the overtaking performances of the overtaking on the two-lane highway; 3) the guidance of the stable control of the steering wheel and gas/brake pedals is essential in the overtaking.

Examining the impact of different LED road stud layouts on driving performance and gaze behaviour at night-time

The risks associated with night-time driving on dimly lit roads are substantial and are attributable to the limitations of human visual abilities. As a result, drivers often struggle to distinguish road geometry from ordinary road markings, thus increasing the likelihood of mistakes. These circumstances contribute to a 60 % higher likelihood of road crashes compared to daytime conditions. To mitigate these risks, active LED road studs, which previous studies have shown to have a positive influence on driving performance, can be used. However, there remains a gap in research regarding the optimal arrangement of these studs along road markings for an improvement in driver behaviour and traffic safety. In this study, we assessed the influence of five different LED road stud layouts (unlit, edge, centre, edge-centre, and lane) during night-time driving on two-lane rural highways with curves of different radii (120, 210, 300, 440 m) and directions (left, right). Following a within subject design, thirty-five participants drove in a simulator along a road track with 8 spiralled curves (4 radii × 2 directions) linked to straights. We monitored the longitudinal (i.e., speed), transversal (i.e., lateral position and standard deviation of lateral position) and gaze behaviours.Our findings indicate that the presence of LED road studs promotes safer driving, by helping drivers to adjust their speed when negotiating curves. Transversal behaviour analysis revealed layout-dependent effects on lateral position. The presence of road studs both at the lane centreline and edge allows drivers to maintain centred trajectories and improve steering control. Gaze behaviour analysis uncovered interesting patterns, demonstrating a strong correlation between road stud layout and the driver's focus on specific road targets. Illuminated markings prompt drivers to concentrate their gaze on distinct points, subsequently altering their transversal behaviour.

Crash modification factors for high friction surface treatment on horizontal curves of two-lane highways: A combined propensity scores matching and empirical Bayes before-after approach

Horizontal curves are locations that, as a result of the changing alignment, may be a contributing factor in roadway departure crashes. One low-cost countermeasure to mitigate crashes at these locations is the installation of the high friction surface treatment (HFST), which increases roadway friction and is intended to help keep drivers on the roadway when traversing a horizontal curve. This treatment has been implemented at numerous curves in Pennsylvania, but the overall safety effectiveness is not known. The purpose of this study is to estimate a suite of Crash Modification Factors (CMFs) for HFST applied to curve sections of undivided two-lane roadways. A novel combination of the empirical Bayes observational before-after study design and propensity score matching was used to estimate CMFs for multiple crash types, crash severities, and roadway settings (urban and rural). Propensity score matching was implemented to identify the most appropriate reference group to use within the empirical Bayes methodology. The results indicate that the installation of HFST is associated with a statistically significant decrease in all crash types and severities considered.

Modeling 85th percentile speed differential for evaluating geometric design consistency on two-lane rural highways

Modeling 85th percentile speed differential for evaluating geometric design consistency on two-lane rural highways

Fatal Crash Occurrence Prediction and Pattern Evaluation by Applying Machine Learning Techniques

Background Highway safety remains a significant issue, with road crashes being a leading cause of fatalities and injuries. While several studies have been conducted on crash severity, few have analyzed and predicted specific types of crashes, such as fatal crashes. Identifying the key factors associated with fatal crashes and predicting their occurrence can help develop effective preventative measures. Objective This study intended to develop cluster analysis and ML-based models using crash data to extract the prominent factors behind fatal crash occurrences and analyze the inherent pattern of variables contributing to fatal crashes. Methods Several branches and categories of supervised ML models have been implemented for fatality prediction and their results have been compared. SHAP analysis was conducted using the ML model to explore the contributing factors of fatal crashes. Additionally, the underlying hidden patterns of fatal crashes have been evaluated using K-means clustering, and specific fatal crash scenarios have been extracted. Results The deep neural networks model achieved 85% accuracy in predicting fatal crashes in Kansas. Factors, such as speed limits, nighttime, darker road conditions, two-lane highways, highway interchange areas, motorcycle and tractor-trailer involvement, and head-on collisions were found to be influential. Moreover, the clusters were able to discern certain scenarios of fatal crashes. Conclusion The study can provide a clear image of the important factors related to fatal crashes, which can be utilized to create new safety protocols and countermeasures to reduce fatal crashes. The results from cluster analysis can facilitate transportation professionals with representative scenarios, which will benefit in identifying potential fatal crash conditions.

Safety and Economic Effects of Median Guardrails in No-Passing Zone Sections of a Two-Lane Two-Way Rural Highway

Safety and Economic Effects of Median Guardrails in No-Passing Zone Sections of a Two-Lane Two-Way Rural Highway

Assessment of Design Consistency for Two-Lane Rural Highways with Low Tortuosity Alignment

One technique employed to enhance road safety involves assessing the alignment’s consistency. A prevalent measure of consistency is evaluating speed variations along the alignment. A key consideration in this assessment is determining the speed upon which the road alignment should be based. This research reveals that on two-lane rural highways with low tortuosity alignments, operating speeds on horizontal curves and tangents consistently exceeded not only the design speeds but also the maximum permissible design speed for the road category. Consequently, using the design speed to assess consistency on these roads is deemed impractical, and utilizing operating speed poses challenges due to speeds exceeding the maximum permissible limit. The objectives of this paper are twofold: to explore the relationship between design consistency and safety levels on two-lane rural highways with low tortuosity alignments (which have been insufficiently covered in research) and to propose speed-control measures to limit the maximum operating speed to the maximum permissible speed. The study findings suggest that on roads with a low tortuosity alignment, operating speeds depend much more on the general characteristics of the alignment (evaluated in the operating speed models through the desired speed). Further, assessing speed consistency is feasible only with a rigorous control of the maximum operating speed (desired speed). Additionally, a specific type of speed control is recommended, achieved by limiting the curvature change rate (CCR) of the road section based on the desired speed (environmental speed), whose evaluation becomes a crucial factor.

Optimal lane management policy for connected automated vehicles in mixed traffic flow

The management of lanes for mixed traffic flow consisting of connected automated vehicles (CAVs) and human-driven vehicles (HDVs) can effectively improve the operational efficiency of highways. This paper proposes an optimal lane management policy for connected automated vehicles in mixed traffic flow on highways. Firstly, the functioning characteristics of the mixed traffic flow are analyzed in three aspects, including car-following mode, headway, and platoon size. Secondly, the vehicle probability distributions under different lane management strategies are derived based on the Markov chain and conditional probability. Then, a calculation model for the capacity of mixed traffic flow was constructed by considering the features of lane management strategies, and sensitivity analyses were performed on the model parameters. Finally, a joint optimization model of CAVs dedicated lanes is proposed with the objective of maximum throughput based on constraints such as lane operation strategies, vehicle type ratios, and road resources. The numerical experiments lead to the following conclusions. (1) For two-lane highways, when the traffic demand is less than 6000 veh/h, the mixed driving lane management strategy should be applied; and when the traffic demand reaches 8000 veh/h, and the CAVs penetration rate is more than 0.56, one CAVs dedicated lane is required. Also, the higher the traffic demand, the lower the critical penetration rate of CAVs. (2) In the three-lane highway scenario, no dedicated lane is required when traffic demand is less than 8000 veh/h; one CAVs dedicated lane is needed when demand exceeds 8000 veh/h with CAVs penetration rate greater than 0.38; and two CAVs dedicated lanes are necessary when demand increases to 12800 veh/h and CAVs penetration rate is more than 0.79. (3) As for four-lane highways, the minimum traffic demand for installing one dedicated lane is 15600 veh/h, and the critical penetration rates for one, two, and three dedicated lanes are 0.32, 0.71, and 0.96, respectively. (4) The increase of CAVs dedicated lane usage willingness and platoon size promote the throughput, and the former CAVs dedicated lane usage willingness works more obviously. These research conclusions can provide theoretical and applied practical support for CAVs dedicated lanes management in the future.

Integrated Overtaking Model and Safety Analysis for Truck Platooning Requirements on Two-Lane Undivided Highways

Truck platooning is a promising solution for enhancing efficiency and reducing fuel consumption in freight transportation. However, overtaking truck platoons poses safety challenges that need to be addressed. This paper employs an overtaking model incorporating lane change dynamics, and a collision risk assessment to evaluate the safety risks involved in overtaking truck platoons. The safety assessment is presented through a numerical analysis that considers three aspects: roadway geometry, traffic conditions, and driver behavior. Scenarios representing different truck platoon lengths, driver behavior, and opposing traffic conditions are evaluated, highlighting their impact on safety. Two major findings from the assessment are that the overtaking distance and time increase linearly as the truck platoon length increases, and potential driver hesitation and the presence of opposing vehicles are shown to increase collision risks. Safety implications are that the length of truck platoons needs to be regulated on two-lane undivided highways; and driver behavior should be considered in the safety assessment and regulation of truck platooning, but further investigations are needed. From the perspective of overtaking, this paper emphasizes the need for safety guidelines and regulations for truck platooning. Policymakers, transportation agencies, and industry stakeholders may utilize the findings to establish standardized safety measures and protocols.

Modelling Yielding of Slow-Moving Vehicles: Application of Drone Data

Overtaking on two-lane undivided highways poses complex challenges, with attention traditionally focused on the overtaking vehicle. Yet, slow-moving vehicle (impeder) behaviour has been largely overlooked. This study investigates the yielding process whereby impeders actively support overtaking vehicles. This phenomenon can have implications for safety in autonomous environments and optimising Traffic control strategies. Empirical data, including drone-captured trajectories, were analyzed to develop predictive models for yielding behaviour. Prediction accuracies up to 82% and 85% for speed and space yielding were achieved, respectively. Integrating these models into microsimulation tools can supplement policy decisions, optimize Traffic flow, and mitigate accidents, yielding significant societal benefits.

Formation Mechanism and Analysis of Intelligent Connected Vehicles Fleet under Meta-Cellular Automata Simulation Conditions

Abstract This paper analyzes the intelligent networked fleet formation mechanism under adaptive cruise control (CACC). By constructing a communication architecture system including network layer, coordination layer, control layer and physical layer, and based on environment sensing technology and 5G network, a layered control structure for autonomous driving vehicles is established. In the study, the inter-vehicle distance control strategy is proposed, and combined with the theory of metacellular automata, the study constructs an intelligent networked fleet model, which adopts the full speed difference model and adaptive cruise control vehicle following model. The simulation analysis is carried out through the actual data of a section of G6 Beijing-Tibet Expressway, and the simulation environment is a two-lane highway of 3000m, considering different CAV vehicle penetration rates (0% to 100%). The results show that with the increase of CAV penetration, the traffic flow and the congestion significantly improved. The intelligent Connected Vehicles fleet performs well in the obstacle avoidance task, effectively reducing unnecessary lane changes and shortening the congestion time compared to the conventional system, with the distance error controlled within 1m. This study shows that the intelligent connected vehicles-connected fleet has significant advantages in improving traffic flow’s operational efficiency and safety.

Analysis and Modelling of Acceleration Behavior on the Horizontal Curves of Two-Lane Undivided Rural Highways Passing Through Mountainous Terrain

Analysis and Modelling of Acceleration Behavior on the Horizontal Curves of Two-Lane Undivided Rural Highways Passing Through Mountainous Terrain

Injury severity of single-vehicle weather-related crashes on two-lane highways

Roadway safety is immensely affected during adverse weather conditions. Therefore, this study seeks to quantify such effects on the injury severity of involved drivers in single-vehicle crashes on two-way highways. This should be done by identifying risk factors and accommodating the heterogeneous impacts of these factors by accounting for the heterogeneity in means and variances of random parameters in the estimated model using seven years of police-reported crash data from 2010 to 2016 in Oregon. The study findings confirm the superior performance of the mixed logit model with heterogeneity in the means and variances in terms of statistical fit comparable to the traditional mixed logit model and mixed logit model with heterogeneity in the means only. The estimation results reveal that some factors such as female drivers, fatigued drivers, crashes in the early morning (between 4:00 am and 8:00 am), and crashes that occurred in darkness with no streetlights were found to increase serious injury outcomes. The empirical findings can offer evidence-based insights to help in decision-making and countermeasure selection that is aimed at improving safety under adverse weather conditions.

Relationship between Horizontal Curve Geometry and Single-Vehicle Crash Occurrence on Rural Secondary Highways

Single-vehicle crashes are overrepresented on rural two-lane highway curves. While prior work investigated the relationship between crash occurrence and aggregate curve characteristics, several important aspects related to curve geometry remain uninvestigated. To this end, research was undertaken to evaluate the safety effects associated with several specific horizontal curve-related geometric characteristics (including curve type, curve direction, tangent distance between curves, and curve design speed) on rural two-lane undivided highways, considering non-animal single-vehicle crashes. Eight years of crash data were obtained for 277 mi and 557 mi of curved state and county highway segments, respectively, within Michigan. Several mixed-effects negative binomial models, with county- and site-specific random intercepts, were developed separately for state and county highways. The model results indicated that several key geometric factors were associated with crash occurrence on rural two-lane highways, including curve type, curve direction, tangent distance approaching the curve, inner-curve tangent distance, and curve design speed. Each of the following geometric characteristics was associated with elevated single-vehicle crash occurrence: (1) compound and reverse curves (compared with simple curves); (2) left-turning curves (compared with right-turning); (3) curves with design speeds lower than the speed limit (compared with curves with higher design speeds); (4) longer tangent distances approaching a simple curve or the initial curve in a series; and (5) shorter inner-curve distances between successive compound or reverse curves. Compound or reverse curves should be avoided in favor of simple curves with an elongated inner-curve distance. Enhanced warning signage should be considered where such curve designs cannot be avoided.