Search Results (84)

Bicycle riding requires a high standard width and continuity of lanes, as an appropriate width directly improves the service level of the lanes. Therefore, the width of bicycle lanes should be designed considering the characteristics of the bicycle traffic flow and the actual conditions of an area. In order to explore the relationship between bicycle traffic flow characteristics and lane width, this study references the vehicle traffic flow model and introduces the concept of bicycle traffic flow width, defined as the average width of bicycle traffic flow over a certain distance in a unit of time. Based on measured data, this study analyzes the relationships among bicycle traffic flow, lane width, and other parameters. The research results show that when the bicycle lane width is between 2.0 and 3.4 m, there is a clear linear relationship between the speed of bicycle traffic flow and the traffic flow width, with bicycle traffic flow width increasing as speed increases. Furthermore, overly wide bicycle lanes can result in more instances of bicycle over-speeding. These findings will guide the design of bicycle lanes. Full article

This study investigates the structural performance and load-bearing capacity of single- and double-story modular bridge configurations using both experimental testing and finite element analysis. A full-scale field test was conducted on a 45.7 m double-story bridge subjected to truck loading at ten distinct positions along the span. Midspan deflections and axial strains of key members were measured and analyzed at each loading position to assess the bridge’s response under service loads. The experimental data were used to validate three-dimensional finite element (FE) models and refine modeling techniques for the double-story modular bridge. The validated FE models enabled further analysis of the structural performance of double-truss–double-story (DD) and quadruple-truss–single-story (QS) modular bridge configurations, both in single- and double-lane setups. The numerical results demonstrated that the double-story configuration with double truss lines per side provided a notable improvement in stiffness and load-carrying capacity compared to the single-story configuration with quadruple truss lines. Moreover, single-lane bridges exhibited better performance than their double-lane equivalents, emphasizing the impact of bridge width on structural stability. Wider, double-lane bridges were found to be more prone to out-of-plane buckling at midspan, with the top chords experiencing significantly greater deformation. Buckling analyses indicated that, although the DD and QS configurations had comparable critical loads, their failure mechanisms differed. Finally, live load factors predicted through the models were compared with the requirements of the Canadian Highway Bridge Design Code (CHBDC), confirming that the DD configuration in a two-lane setup meets code expectations and demonstrates effective structural performance. Full article

Traditional methods for predicting pavement performance rely on complex finite element modelling and empirical equations, which are computationally expensive and time-consuming. However, machine learning models offer a time-efficient solution for predicting pavement performance. This study utilizes a range of machine learning algorithms, including linear regression, decision tree, random forest, gradient boosting, K-nearest neighbour, Support Vector Regression, LightGBM and CatBoost, to analyse their effectiveness in predicting pavement performance. The input variables include axle load, truck load, traffic speed, lateral wander modes, asphalt layer thickness, traffic lane width and tire types, while the output variables consist of number of passes to fatigue damage, number of passes to rutting damage, fatigue life reduction in number of years and rut depth at 1.3 million passes. A k-fold cross-validation technique was employed to optimize hyperparameters. Results indicate that LightGBM and CatBoost outperform other models, achieving the lowest mean squared error and highest R² values. In contrast, linear regression and KNN demonstrated the lowest performance, with MSE values up to 188% higher than CatBoost. This study concludes that integrating machine learning with finite element analysis provides further improvements in pavement performance predictions. Full article

The design of passenger-dedicated lane width is essential for freeway reconstruction and expansion projects. However, the technical standard of lane width established in China is based on trucks. This study aims to propose a passenger-dedicated lane width calculation method for freeways based on overtaking behavior. Computer vision technology was used to extract vehicle trajectories and dimensions from videos captured by an unmanned aerial vehicle (UAV). Statistical methods such as cumulative frequency statistics, typical percentile statistics and regression analysis were employed to elaborate on the lateral displacement and distance of vehicles during overtaking. The results show that vehicles’ lateral displacements are mainly related to behaviors such as lane changing, lateral distance maintenance and lane keeping. The body width sum of parallel vehicles has little effect on the geometric center distance but significantly reduces the wheel distance when increasing. The general value of the passenger-dedicated lane width on freeways is recommended to be 3.5 m, and the limit value is 3.25 m. Compared with existing lane width calculation methods, this study pays more attention to the relationship between vehicle width and lateral distance, which can better cope with the challenges caused by vehicle diversity in lane width design. Full article

Adjacent existing box girder bridges should be spliced in the long-span bridge expansion project. A type of integral splicing composite structure for connecting the adjacent flange plates is designed herein. The mechanical characteristic of the integral splicing composite structure is tested using a local full-scale model, and a refined simulation model is also proposed for the optimization of the integral splicing composite structure. The loop bar in the joint connection segment and the application of Ultra-High-Performance Concrete (UHPC) material can guarantee the effective connection between the existing flange plate and the splicing structure. The embedded angled bar can delay the interface debonding failure and interface slip. The UHPC composite segment below the flange plate (segment CF) can bend together with the existing flange plate. In this study, an innovative integral splicing composite structure for a long-span bridge extension project is proposed and verified using both a local full-scale model test and finite element simulation. The adaptation of UHPC material and loop bar joint connection form can meet the cracking loading requirements of the splicing box girder structure. By proposing a refined simulation model and comparing the calculation result with the test result, it is found that the flexural performance of the integral splicing composite structure depends on the size of the composite segment below the flange plate (segment CF). Increasing the width of segment CF is beneficial to delay the interface debonding failure, and increasing its thickness can effectively delay the cracking load of the flange plate. Finally, the scheme of segment CF with one side width of 200 cm and a minimum thickness of 15 cm can improve the flexural resistance of the spliced structure and avoid the shear effect caused by the lane layout scheme and the location of the segment CF end. Through the research in this paper, the reasonable splicing form of a long-span old bridge is innovated and verified, which can be used as a reference for other long-span bridge splicing projects. Full article

Reducing vehicle lane widths has been proposed as an effective strategy to decrease vehicle speeds and enhance road safety. However, the safety benefits of narrower travel lanes remain a topic of debate due to mixed findings in the literature. This study examines the relationship between lane width, vehicle speed, and crash occurrence to comprehensively understand their impact on road safety and transportation planning. Using data from 320 urban arterial sections in Utah, the analysis reveals that narrower lane widths are associated with reduced vehicle speeds. For every additional foot of lane width, 85th and 95th percentile speeds increase by 1.012 mph and 1.088 mph, respectively. Furthermore, injury crash modeling indicates that a one-foot increase in lane width is associated with a 38.3% increase in the odds of an injury crash on a roadway section. These findings contribute to the growing evidence supporting the implementation of narrower lane widths as a strategy to improve road safety, foster multimodal infrastructure, and promote sustainable urban transportation systems. We recommend that UDOT adopt a minimum lane width of 10 or 11 feet for arterials in highly urbanized areas, such as downtowns and major activity centers. Full article

In modern society, vehicle accidents have been a factor that has adversely affected national development for a long time. Many countries have tried to solve this issue, and various solutions have been studied. This study aims to design a process for analyzing vehicle accidents to support safety interventions. In the data preprocessing section, a resampling technique was used to solve the data imbalance problem. Then, we applied five different machine learning models for classification by applying hyperparameter optimization. After classification, model-agnostic interpretation techniques were used to interpret the results of a series of machine learning models. Through the above series of processes, we were able to design a process that analyzes vehicle accident data and derives the factors that affect the accident. The classification model that uses XGBoost with ENN (Edited Nearest Neighbor) shows almost 84.3% accuracy. As a result, for “Length” and “Volume”, we found that certain points (Length: 200 m, 29,233 veh/day) were more likely to have an accident. Moreover, variables, such as volume or the volume of heavy vehicle, the probability of an accident increases as the value increases, but in the case of “Lane width” and “Shoulder width”, it can be confirmed that the probability of occurrence decreases as the value increases. These interpretations have meaningful information that could suggest policy recommendations for reducing traffic accidents and can be helpful in establishing effective traffic accident countermeasures. Full article

The vehicular trajectory offset represents a critical controlling element in the design of lane width. In light of the paucity of extant research on the lane widths for dedicated autonomous vehicle lanes, this study deployed the PreScan-Simulink co-simulation platform. Based on the established typical lateral and longitudinal control methods for autonomous vehicles, we initially identified the primary factors influencing trajectory offset through multifactorial coupled analysis. Subsequently, we conducted quantitative research on vehicle trajectory offset using S-shaped curves to elucidate the patterns in geometric elements’ impact on trajectory offset. Following this, we established a model of the relationship between design speed and trajectory offset under different vehicle types. Ultimately, we calculated the lane width values for scenarios involving varying positions and numbers of dedicated lanes. The results demonstrate that vehicle speed significantly impacts the trajectory offsets of autonomous vehicles. For passenger cars, the mean offset at speeds between 60 and 130 km/h is approximately 10 cm. At higher speeds of 140–150 km/h, the offset is more variable. The range of offset exhibited by trucks at speeds between 60 and 100 km/h is [8 cm, 16 cm]. In the case of a single dedicated lane, the width of the inner lanes intended for passenger cars is [2.60 m, 3.00 m], while the outer lanes designed to accommodate trucks have a width of [3.00 m, 3.20 m]. In scenarios with two dedicated lanes, the width of lanes for passenger cars can be reduced further, whereas the required lane width for trucks remains largely unchanged compared to that for single-lane setups. The conclusions show that the width of lanes adapted to autonomous vehicles could be reduced, which could help to optimize the use of road space, thus potentially reducing the occupation of land resources, reducing the environmental impact of road construction, and contributing to sustainable development. This study also provides valuable insights for the design of lanes dedicated to autonomous vehicles. Full article

In traffic engineering, vehicle speed is a critical determinant of both the risk and severity of road crashes, a fact that holds particularly important for signalized intersections. Accurately selecting vehicle speeds is crucial not only for minimizing accident risks but also for ensuring the proper calculation of intergreen times, which directly influences the efficiency and safety of traffic flow. Traditionally, the design of signal programs relies on fixed speed parameters, such as the posted speed limit or the operational speed, typically represented by the 85th percentile speed from speed distribution data. Furthermore, many design guidelines allow for the selection of these critical speed values based on the designer’s own experience. However, such practices may lead to discrepancies in intergreen time calculations, potentially compromising safety and efficiency at intersections. Our research underscores the substantial variability in the speeds of passenger vehicles traveling intersections under free-flow conditions. This study encompassed numerous intersections with the highest number of accidents, using unmanned aerial vehicles to conduct surveys in three Polish cities: Toruń, Bydgoszcz, and Warsaw. The captured video footage of vehicle movements at predetermined measurement sections was analyzed to find appropriate speeds for various travel maneuvers through these sections, encompassing straight-through, left-turn, and right-turn relations. Our analysis focused on how specific infrastructure-related factors influence driver behavior. The following were evaluated: intersection type, traffic organization, approach lane width, number of lanes, longitudinal road gradient, trams or pedestrian or bicycle crossing presence, and even roadside obstacles such as buildings, barriers or trees, and others. The results reveal that these factors significantly affect drivers’ speed choices, particularly in turning maneuvers. Furthermore, it was observed that the average speeds chosen by drivers at signalized intersections did not reach the permissible speed limit of 50 km/h as established in typical Polish urban areas. A key outcome of our analysis is the recommendation for a more precise speed model that contributes to the design of signal programs, enhancing road safety, and aligning with sustainable transport development policies. Based on our statistical analyses, we propose adopting a more sophisticated model to determine actual vehicle speeds more accurately. It was proved that, using the developed model, the results of calculating the intergreen times are statistically significantly higher. This recommendation is particularly pertinent to the design of signal programs. Furthermore, by improving speed accuracy values in intergreen calculation models with a clear impact on increasing road safety, we anticipate reductions in operational costs for the transportation system, which will contribute to both economic and environmental goals. Full article

Village streets are indispensable spaces for people to perform outdoor activities, and they also directly affect the outdoor wind environment in villages. At present, people are paying more attention to the wind environment comfort of urban residential areas and urban commercial streets, but there is a lack of attention and research on the wind environment comfort of village and town streets. By summarizing the field research and meteorological data of Lefeng Village, we propose the outdoor wind environment evaluation requirements applicable to the Hanjiang River’s Chuan Dao area in the winter and summer seasons. We found that more than 80% of the outdoor wind environment in the summer is less than 1 m/s. Based on the numerical simulation method of computational fluid dynamics, and on the basis of the characteristics of the streets and lanes in the Hanjiang River’s Chuan Dao area, we found that the wind environment is poor in the winter and summer seasons; regarding streets and lanes, we propose three appropriate values, namely building density, building height, and street width. It is suggested that it is appropriate for the building density of the area to be less than 36%, the height of the building to be less than 15 m, and the width of the street to be 6–11 m when the street is open to traffic and 3–6 m when only pedestrians are passing through the area. Full article

This research investigates the lane width standards and guidelines implemented by various State Departments of Transportation (DOTs) to reduce vehicle speeds and enhance road safety. Lane width reduction is often perceived as a strategy to mitigate speed and improve safety. Still, its effectiveness and implications vary across different contexts, including regions, urban/rural settings, or other geometric design features. Drawing from interviews with five State DOTs and a review of their road design manuals, this study aims to identify suggested lane widths depending on the contexts, design exception process when narrowing or widening lane widths, and introduce representative before/after studies. The findings indicate that State DOTs tend to have lower recommended lane widths in urban areas than in rural areas. Moreover, lane width standards among these states vary due to several factors, including the geographical location of roadways (urban or rural areas), design or posted speeds, traffic volume, road classification, and geometric road design features. Design exceptions are required if the existing or proposed design element is incompatible with both AASHTO and department governing criteria. In conclusion, the findings will provide valuable insights and recommendations for policymakers, transportation planners, and road engineers to inform optimal lane width and decision-making processes. Full article

The automated truck’s steering system can potentially control its lateral movement (i.e., wander mode) within the lane. The controlled wander mode of automated trucks could affect the transverse loading distribution of the wheels and consequently influence pavement fatigue damage in the long term. This study examines the effects of potential wander modes on pavement fatigue damage, considering the effects of lane width, market penetration rate, flexible pavement layers’ thickness, and stiffness of the materials. This study uses a finite element model to calculate the flexible pavement response. The mechanistic–empirical method is used to compute the total fatigue damage index for a specific design period, incorporating the wander mode effect. Comparing the fatigue damage indices indicates that automated trucks could either reduce the damage index value from −1.41% to −7.05% (i.e., mitigator scenario) or increase it from +11.6% to +278.57% (i.e., aggravator scenario), depending on their deployment scenarios. Moreover, the findings show that using a uniform-wander mode instead of a zero-wander mode or increasing the thickness and stiffness of the pavement layers could effectively reduce the adverse effect of automated trucks on fatigue damage and reduce the damage indices from −0.06% to −42.95%. However, their impact is considerably influenced by market penetration rate and lane width. Full article

Globally, road traffic collisions cause over a million deaths annually, with pedestrians accounting for 23%. In developing countries, most pedestrian deaths occur on urban arterial roads, particularly at midblock crossings. This study analyzes the factors influencing driver yielding behavior at midblock crosswalks on urban arterial roads in Thailand. This study analyzed the factors influencing driver yielding behavior at the midblock crosswalk before and after the upgrade from a zebra crossing (C1) to a smart pedestrian crossing (C2), which is a smart traffic signal detecting and controlling pedestrians and vehicles entering the crosswalk. Video-based observations were used to assess driver yielding behavior, with multinomial logistic regression applied to develop driver yielding behavior models. The results revealed that the chances of a driver yielding at C2 were higher than at C1, and the yielding rate increased by 74%. The models indicate that the number and width of traffic lanes, width and length of crosswalks, vulnerable group, number of pedestrians, pedestrian crossing time, number of vehicles, vehicle speed, headway, post-encroachment time between a vehicle and pedestrian, and roadside parking are the significant factors influencing yielding behavior. These findings propose measures to set proper crosswalk improvements (e.g., curb extensions), speed reduction measures, enforcement (e.g., parking restrictions), public awareness campaigns, and education initiatives. Full article

The documentation of roadway factors (such as roadway geometry, lane marking retroreflectivity/classification, and lane width) through the inventory of lane markings can reduce accidents and facilitate road safety analyses. Typically, lane marking inventory is established using either imagery or Light Detection and Ranging (LiDAR) data collected by mobile mapping systems (MMS). However, it is important to consider the strengths and weaknesses of both camera and LiDAR units when establishing lane marking inventory. Images may be susceptible to weather and lighting conditions, and lane marking might be obstructed by neighboring traffic. They also lack 3D and intensity information, although color information is available. On the other hand, LiDAR data are not affected by adverse weather and lighting conditions, and they have minimal occlusions. Moreover, LiDAR data provide 3D and intensity information. Considering the complementary characteristics of camera and LiDAR units, an image-aided LiDAR framework would be highly advantageous for lane marking inventory. In this context, an image-aided LiDAR framework means that the lane markings generated from one modality (i.e., either an image or LiDAR) are enhanced by those derived from the other one (i.e., either imagery or LiDAR). In addition, a reporting mechanism that can handle multi-modal datasets from different MMS sensors is necessary for the visualization of inventory results. This study proposes an image-aided LiDAR lane marking inventory framework that can handle up to five lanes per driving direction, as well as multiple imaging and LiDAR sensors onboard an MMS. The framework utilizes lane markings extracted from images to improve LiDAR-based extraction. Thereafter, intensity profiles and lane width estimates can be derived using the image-aided LiDAR lane markings. Finally, imagery/LiDAR data, intensity profiles, and lane width estimates can be visualized through a web portal that has been developed in this study. For the performance evaluation of the proposed framework, lane markings obtained through LiDAR-based, image-based, and image-aided LiDAR approaches are compared against manually established ones. The evaluation demonstrates that the proposed framework effectively compensates for the omission errors in the LiDAR-based extraction, as evidenced by an increase in the recall from 87.6% to 91.6%. Full article

Research on the excavation mechanical properties of underpass tunnels has already had certain results, but only a few of them consider the effects of dynamic and static loads on the excavation mechanical properties of underground tunnels at the same time; particularly, there is a lack of research investigating double-line highway tunnels with angled underpasses of existing railway tunnels. In this paper, based on the tunnel project of the new double-line Shiqian Highway Tunnel passing under the Hurong Railway with an oblique angle, based on the method of over-advance geological prediction and investigations into the palm face surrounding the rock, the rock degradation caused by dynamic and static loads is quantified using the perturbation system. Additionally, the mechanical parameters of the rock under the influence of dynamic and static load coupling in the influence area of the cross-tunneling project are determined using the Hoek–Brown criterion, and the mechanical characteristics of the excavation of a tunnel under the double-lane highway tunnel passing under the existing railroad are constructed with the mechanical characteristics of the double-lane highway tunnel, taking into consideration the influence of the dynamic and static load coupling in a three-dimensional model. The results show that, in line with the new tunnel rock movement law for the top of the arch sinking, the bottom plate bulging, the side wall outward movement, the height and width of the arch, and the bottom plate arch show an increase with the tunnel excavation, while the side wall rock displacement effect is smaller; the left and right line tunnel disturbed area of the rule of change is similar; the existing tunnel bottom plate displacement is larger than the top plate and the left and right side wall, under the influence of the excavation time step. Typical profile point displacement is mainly determined by the distance from the excavation surface; von Mises stress extremes are observed in the top plate and side walls of the existing tunnel, which occur in the tunnel structure, and there are unloading and pressure-bearing zones in the bottom plate; the new tunnel has the same rock disturbance angle under the four calculation conditions and, based on the displacement control criterion, the excavation method is preferred and the upper and lower step blasting excavation method is recommended. Full article