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Road geometric design. (a) Horizontal curve. (b) Longitudinal slope. (c) Vertical curve. (d) Superelevation. (e) Road crown. (f) Composite longitudinal slope.
Source publication
According to the accident analysis of vehicles in the curve, the skidding, rollover, and lateral drift of vehicles are determined as means to evaluate the lateral stability of vehicles. The utility truck of rear-wheel drive (RWD) is researched, which is high accident rate. Human-vehicle-road simulation models are established by CarSim. Through the...
Citations
... Subsequently, construction issues were detected in the design by comparing the document with a built road. Construction is liable if an existing road has a defect that was not anticipated in the design; in other cases, the road design bears accountability (Yin et al., 2020;Choong et al., 2021). ...
... where (k) is a reduction constant, and (c) is the coefficient value of the centrifugal force in the road curve. Roadway superelevation should give positive psychological effect on drivers [7,8,9], but because of the mistake in assumption that the drivers use Vd for the whole section of the road, this positive effect is missing. It is very obvious that neither are the drivers familiar with a term called design speed, nor they are driving with that speed. ...
In this paper, the theoretical concept of roadway superelevation based on speed in free traffic flow is derived. The influence of the radius of the horizontal curve on speed in free traffic flow as a basis of this analysis is taken from a more detailed experimental research for two-lane rural highways. This method is new and differs from others that use constant design speed value. However, this method gives similar results when compared to the empirical methods of computing roadway superelevation, where design speed is constant but it is assumed that when the curve radius is greater than the minimum, the driving speeds are greater than the design speed. Presented work defines and explains that assumption and takes it into account when computing roadway superelevation.
... Sideslip is the most common situation in lateral instability [59]. Figure 8 illustrates the forces acting on a vehicle on a curved segment during its travel. ...
Understanding the sideslip risks of various trajectory patterns, as well as the impact of rainfall on them, is critical for improving road safety. However, the lack of precise classification indicators hampers systematic analysis of the variations in vehicle trajectory patterns. To address this, this study proposes a parameterized classification method for trajectories on curved segments, employing the radius and offset of the trajectory as the primary classification features and dividing the trajectories into nine patterns. These patterns represent variations from smaller to larger radii and inside to outside lane offsets, reflecting different driving behaviors and vehicle stability during vehicle cornering. Concurrently, the friction coefficient utilization rate is used to effectively compare vehicles’ sideslip risk under different weather conditions. Based on this, we construct a framework using computer vision technology for automatically identifying trajectory patterns and measuring sideslip risk. We conducted an empirical study on a highway-curved segment with high sideslip risk in China and collected two datasets under clear and rainy conditions for analysis. The classification results show that the proposed method can effectively classify trajectories according to nine trajectory patterns. Comparative analysis reveals that vehicle trajectories in both the inside and outside lanes are notably more affected by rainfall compared to the middle lane. Meanwhile, trucks demonstrate a higher susceptibility to rainfall than cars. In addition, the analysis of the sideslip risk for different trajectory patterns discovers several high-risk patterns. This study provides an effective approach for monitoring and analyzing the sideslip risk on curved segments, thereby contributing to the enhancement of road design and traffic safety management.
... Nonetheless, the vehicle tends to rush out of the curve at this moment and cannot be driven properly due to the occurrence of a sideslip. Importantly, while non-tripping rollover may not occur in this state, tripping rollover may occur as a result of sideslipping collisions with obstacles, curbs, guardrails, and so on [34,67]. This discrepancy arises because the simulation modeling assumes an ideal state for the road slope during the sideslipping process, ignoring the impacts of collisions with barriers, potentially resulting in minor discrepancies between the simulation result and the actual situation. ...
Many northern hemisphere countries have experienced exceptionally heavy snow, blizzards, and cold snaps in recent years, causing considerable public concern about the high crash rate and safety issues in road traffic. This study used the CarSim dynamics simulation to recreate several vehicle driving scenarios in snow and ice conditions. To explore the influence of speed, curve radius, and road adhesion coefficient on vehicle sideslip and rollover, four lateral stability evaluation indicators, namely lateral offset, lateral acceleration, yaw rate, and roll angle, are chosen. Unfavorable combinations of these factors result in vehicle deviation from their intended trajectory and dramatically increase the likelihood of sideslip and rollover incidents. In particular, road adhesion coefficients ranging from 0.10 to 0.20 lead first to sideslip, while coefficients of 0.21 to 0.35 lead straight to rollover. Additionally, in the initial segment of the curve, cars are more susceptible to lateral instability. Curve radius has the greatest influence on sideslip when the three influencing factors are combined, while speed is the key component affecting rollover incidents. Smaller curve radii and higher speeds are major factors in such incidents. The results are helpful for proper road alignment parameter selection and dynamic speed-limit measures. This can provide a theoretical basis for traffic management departments to take targeted measures, which is of great significance to improving road traffic safety in snowy and icy weather.
... From the perspective of driving dynamics, the additional cornering resistance of a vehicle, also known as curve driving resistance, is mainly determined by the road surface friction coefficient, wheel angle, and tire load (Peng et al., 2020). The actual horizontal curve road section is usually accompanied by a superelevation, which will reduce the lateral force coefficient of the curved road (Yin et al., 2020). The effect of the installation of superelevation on the curve driving resistance and carbon emissions is currently unknown. ...
The high carbon emissions of vehicles traveling on horizontal curve road sections cannot be ignored. Facing the difficulty of accurately quantifying the carbon emission of driving on horizontal curves and the unknown causes of high carbon emission, this study proposes to construct a carbon emission prediction model applicable to road sections with different planar geometries. The direct and indirect effects of horizontal curve alignment on vehicle carbon emissions are represented in the model in terms of travel stabilization and speed changes, respectively. A lateral force coefficient parameter was introduced into the model to integrate the carbon emission quantification problem for different planar geometry sections. Meanwhile, field tests were conducted to assess the reliability of the model and the research findings. The model reveals that the geometric parameters of horizontal curves that affect carbon emissions are the radius of the circular curve, the superelevation, and the length of the gentle curve. The root causes of high carbon emissions on horizontal curve road sections are curve driving resistance and speed fluctuations. Under the free-flow driving condition of the highway, the maximum curve radius affecting the carbon emissions of passenger cars and trucks is 400 m and 550 m, respectively. The research results can realize the carbon emission quantification of vehicles on the road sections with different plane geometries. Also, it is helpful to control the high carbon emission of vehicles traveling on horizontal curve road sections.
... However, if the height of the trip is low, its effect will not be large. According to Yin et al., slope and road geometry have an important influence on the vehicle's lateral instability, which is the precursor to rollover [6]. The contact between the wheels and the road is characterized by the ability to hold between them. ...
In this article, the author introduces a new fuzzy control solution to direct active anti-roll bars (hydraulic stabilizer bars) in order to enhance the vehicle’s roll stabilization efficiency. The original fuzzy algorithm designed in this work can satisfy all the roll stability, comfort, and response speed requirements, while previous algorithms could only meet one of these criteria. In addition, a fully dynamic model is established to simulate the vehicle’s roll oscillations instead of only using a simple half-dynamic model combined with the single-track dynamic model. The calculation and simulation processes take place in the Simulink environment. Two cases of steering are used as input to the simulation problem; the car’s speed is gradually increased through three levels. According to results of research, the roll angle and roll index of the car increase as the speed and steering angle increase. The interaction between the road and wheel decreases sharply as the roll angle increases, which can lead to a rollover. In the first case, the rollover occurs only when the car travels at v 3 without the stabilizer bar and has a maximum roll angle of 9.81°. In the second case, this occurs for the (None) situation when traveling at speed v 1 with a maximum roll angle of 9.52° and for the (Passive) situation when traveling at speed v 2 with a peak value of 11.93°. Meanwhile, the vehicle’s stability is still well guaranteed when utilizing active anti-roll bars controlled by an original fuzzy algorithm.
... Wang et al. [37] simulated driving experiments under snowy weather in a bridge and tunnel connection segment, and finally found that the large lateral offset can be prevented by increasing the friction coefficient of pavement and radius of circular curve. Yin et al. [38] investigated the skidding, roll-over, and lateral slip of the vehicle by accounting radius of circular curve and superelevation and found that the safety margin of the vehicle's skidding, roll-over, and lateral slip increased when the radius of the circular curve and superelevation increases. Alrejjal et al. [39] focused on the roll-over propensity influenced by horizontal and vertical alignments under different weather conditions, thus revealing that the lateral acceleration was amplified due to a tight degree of curvature and steep downgrades. ...
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.
... In simple curves, the lateral acceleration is instantaneously imposed on the vehicle and its passengers when entering the curve [8]. In addition, the variation of lateral acceleration is sensible when the superelevation is introduced prior to the curve and at the curve entrance and the safety is decreased [9]. A radius is introduced in the AASHTO Green Book as the application of the maximum radius in the spiral curve. ...
Most road design standards recommend using a spiral curve for transitions. The main advantages of using this curve are the gradual increase in the centrifugal force, creating a suitable space for presenting superelevation, and providing a correct perception of the curve for the driver. In this research, vehicle dynamic simulation software CarSim and TruckSim is used to assess the forces imposed on the vehicles. In this regard, 360 scenarios are considered for sedans, SUVs, and trucks, which consist of variations of the road geometry (simple or spiral horizontal curve), curve radius, and type and speed of the vehicle. In addition, the regression analysis is performed to examine the relationships between the lateral acceleration (as a dependent variable) and the vehicle speed, curve radius, and vehicle type (as independent variables). The results indicate that in all cases, safety in the spiral horizontal curve is greater than that in the simple horizontal curve, and the maximum side friction factor, lateral acceleration, roll rate, roll angle, yaw rate, and lateral distance in the simple horizontal curve are higher than those in the spiral horizontal curve. Moreover, the difference percentage of the side friction factor, lateral acceleration, yaw rate, and lateral distance between the simple and spiral horizontal curves is the highest in SUVs, followed by sedans and trucks, while the difference percentage of the roll rate and roll angle is the highest in sedans, followed by SUVs and trucks. The results of regression analysis illustrate that the coefficient of determination (R2) in the proposed model is 0.972, 0.964, and 0.981 for sedans, SUVs, and trucks, respectively, indicating the strong relationships between the dependent and the explanatory variables as well as the capability of the model to cover the data.
... Sun and his associates proposed a new method based on vehicle dynamics for road safety study [10][11][12][13][14]. e method analyzes dynamic responses of a vehicle model on a given road considering road geometry (i.e., longitudinal, horizontal, and vertical alignments), pavement friction coefficient, operating speed of the road, pavement roughness [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33], weather conditions, wind speed, driver behavior (i.e., lane-changing behavior), roadside environment, vehicle trajectory (i.e., lane-keeping and lane-departing), and other factors. ...
... is method has been used for quantitatively assessing road safety in terms of rollover, skidding, and other types of accident for improving road geometry design, transportation operations management, road maintenance, and transportation safety [10][11][12][13]. ...
... e road center line is considered as the vehicle target trajectory, and the vehicle is controlled to travel along the center line. Detailed parameters of the SUV model and the driver model can be found in authors' previous work [12,13]. ...
In this paper, a closed-loop simulation of vehicle dynamics in CarSim is utilized as surrogate measures to study the effect of pavement roughness and differential settlement on risk of vehicle rollover and skidding. It is found that the influence of pavement roughness on vehicle rollover is significant and the influence of pavement roughness on vehicle skidding is insignificant. The influence of pavement roughness of grade A and B on safety margin of vehicle rollover can be negligible. Pavement roughness of grade C and D significantly reduces the safety margin of vehicle rollover. A 5 cm settlement difference on pavement reduces the safety margin of vehicle skidding on a good road. When the settlement difference is 5 cm, the vehicle rollover and skidding are greatly affected by the lane-changing speed. It provides an effective and general method based on vehicle dynamics for studying transportation safety as well as for setting up criteria for pavement maintenance.
... Analysis of the evolution of trends in traffic accidents and vehicle design has shown that controllability is one of the key operational properties of a vehicle that influences safety. Vehicle controllability is the ability to move following the trajectory designed by the driver [20,21]. The driver sets the desired direction using the steering wheel mechanism, and the controllability tasks are focused on the steering wheel mechanism [22,23]. ...
Two trends could be observed in the evolution of road transport. First, with the traffic becoming increasingly intensive, the motor road infrastructure is developed; more advanced, greater quality, and more durable materials are used; and pavement laying and repair techniques are improved continuously. The continued growth in the number of vehicles on the road is accompanied by the ongoing improvement of the vehicle design with the view towards greater vehicle controllability as the key traffic safety factor. The change has covered a series of vehicle systems. The tire structure and materials used are subject to continuous improvements in order to provide the maximum possible grip with the road pavement. New solutions in the improvement of the suspension and driving systems are explored. Nonetheless, inevitable controversies have been encountered, primarily, in the efforts to combine riding comfort and vehicle controllability. Practice shows that these systems perform to a satisfactory degree only on good quality roads, as they have been designed specifically for the latter. This could be the cause of the more complicated car control and accidents on the lower-quality roads. Road ruts and local unevenness that impair car stability and traffic safety are not avoided even on the trunk roads. In this work, we investigated the conditions for directional stability, the influence of road and vehicle parameters on the directional stability of the vehicle, and developed recommendations for the road and vehicle control systems to combine to ensure traffic safety. We have developed a refined dynamic model of vehicle stability that evaluates the influence of tire tread and suspensions. The obtained results allow a more accurate assessment of the impact of the road roughness and vehicle suspension and body movements on vehicle stability and the development of recommendations for the safe movement down the road of known characteristics.
