Standard Road Research Articles

Road mirage angle

A video is taken of a road-sign mirage from the passenger seat in a car traveling at constant speed on a highway. The video spans the duration of seeing the mirage of the sign, viewing the vanishing of the mirage as the car approaches, and passing the road sign. The mirage angle, defined as the angle with respect to the horizontal at the moment the observer notes the vanishing of the mirage, can be determined from the video, the speed of the car, and known dimensions of the standard road sign. The value can be checked with a theoretical formula using the ambient weather temperament and consulting references to determine the temperature of the air in contact with the road surface. Agreement between observation and theory is within the error bounds. In the conclusion, a quick observational estimate is made in the car without needing the video.

The Role of Rural Infrastructure in Reducing Production Costs and Promoting Resource-Conserving Agriculture

The development of rural infrastructure plays an essential role in improving rural livelihoods and enhancing sustainable and environmentally friendly agricultural production. However, little is known about whether rural infrastructure enables the promotion of resource-conserving agriculture and reduces production costs. Understanding the relationship between rural infrastructure and production costs can provide significant information for policy-makers in their efforts to promote resource-saving agriculture that is beneficial to environmental performance. This study contributes to the literature by analyzing the heterogeneous effects of irrigation infrastructure and standard and substandard roads on agricultural production costs, using an unconditional quantile regression model and provincial data from China for the period 1995–2017. The empirical results show that the effects of rural infrastructure on production costs are mixed. In particular, irrigation infrastructure affects production costs positively in the lower quantiles, but it negatively affects production costs in the higher quantiles. In the higher 80th and 90th quantiles, standard and substandard roads affect production costs both negatively and significantly. Our findings suggest that improving rural infrastructure enables the promotion of resource-conserving agriculture and enhances environmental performance, especially for those paying high production costs.

Effect of Travel Time for Thyroid Surgery on Treatment Cost and Morbidity

Regionalizing surgical care to high-volume centers has improved outcomes for endocrine surgery. This shift is associated with increased travel time, costs, and morbidity within certain patient populations. We examined travel time-related differences in demographics, health-care utilization, thyroid-specific disease, and cost for patients undergoing thyroid surgery at a single high-volume center. Data were extracted from the 2005 to 2014 ACS-NSQIP and clinical data repository for patients undergoing thyroid surgery. Travel times between patients' home address and the hospital were calculated using Google Earth under assumptions of standard road conditions and speed restrictions. Travel time was divided into <2 hours versus ≥2 hours. Primary outcomes were hospital cost and 30-day morbidity. Factors associated with travel time and primary outcomes were analyzed using appropriate bivariate tests and multivariable regression modeling. A total of 1046 thyroid procedures were included, with median (IQR) travel time of 68.8 (40.1-107.2) minutes. Eight hundred forty-seven (80.9%) patients traveled <2 hours compared with 199 (19.1%) traveled ≥2 hours. Patients traveling ≥2 hours were more likely to have complex thyroid disease (37.7% vs 27.6%, P = 0.005), uninsured status (31.1% vs 11.8%, P < 0.001), lower preoperative morbidity risk (2.3% vs 2.7%, P = 0.02), and longer length of stay (1.21 vs 1.07 days, P = 0.04), but similar median operative times (163 vs 165 minutes, P = 0.89). Average cost was higher for patients traveling ≥2 hours ($7300 vs $6846 [2014 USD], P = 0.05). Despite observed patient differences, hospital costs and postoperative morbidity did not differ after adjustment. Existing management practices and the nature of the disease process may be protective against the potential negative effects of regionalization.

Validity and reproducibility of commercial cycling power meters in hot and cold environmental temperatures

Power meters are a training tool used to help cyclists improve performance by objectively monitoring intensity. Some power meters are well established and validated, whereas others are relatively new. Most power meters have been tested for validity and reliability in laboratory and field settings of similar conditions; however, the reproducibility of these power meters across different temperatures has not been established. To examine the potential differences of the CompuTrainer, PowerTap, Stages, and Vector power meters in hot and cold compared to a room temperature environment. Recreationally trained male (n=7) and female (n=3) participants each completed three incremental cycling trials in hot (33°C), cold (7°C), or room temperature (RT, 20°C) conditions. The power meters were placed on a standard road bicycle and power output was logged and recorded. The CompuTrainer was higher in the room temperature trial compared to the cold and the hot, but not between the hot and cold trial. The PowerTap was not different in RT and cold, but was lower in hot compared to RT and compared to cold. The Stages was not different between RT and cold, but was lower in the hot compared to RT and compared to cold. The Vector was not different between RT and cold but was lower in the hot compared to RT and compared to cold. These data indicate that environmental temperature may affect the reproducibility of power meters. It is important to recognize the potential differences between temperatures when choosing a power meter.

A Simplified Method of Detecting Spot Surface Defects by using Quasi-3D Data from a Conventional Road Profiler

It is important to maintain safety and ride quality for toll expressway users in Japan. However, since porous asphalt became the standard road surface, spot defects have gradually spread nationwide. To deal with the problem, this research attempted to develop a less costly but effective way of identifying surface defects. Since transverse data for rutting measurement was the only basic data available for general road profilers, first, quasi-three-dimensional (3D) profile data was successfully obtained by deleting gradient effects on the profiles in both the transverse and longitudinal directions. Among other elements, the standard deviation (SD) of the quasi-3D profile height using spot defect size was best matched for identifying spot defects, including pumping of underlying layer materials of the pavement. To improve the efficiency of detecting spot surface defects, deep learning was examined by converting the SD values into visual images. As a result, it was verified that a simplified classification with basic color information of red, green, and blue gave practically the same engineering judgement. Finally, this method of identifying irregularly emerging target defects using deep learning was validated by relearning the target visuals. A good result with high accuracy was achieved with just 150 images for each defect level. This approach may be universally applied anywhere surface profilers are used.

Complex analysis focused on influence of biodiesel and its mixture on regulated and unregulated emissions of motor vehicles with the aim to protect air quality and environment

The main task of this study is to perform a complex analysis dealing with influence of biodiesel and its mixture on regulated and unregulated gaseous emissions of diesel engine, which is installed in a motorcar as a driving unit determined for standard road traffic. As a real technical platform intended for realisation of the required experiments, a motor vehicle equipped with the TDI engine was chosen because just this kind of engine was directly affected by the affair “dieselgate”. This type of piston combustion engine is widely used in the traffic, together with negative impacts on the air quality. Various diesel fuel mixtures, which represented the applied experimental fuels, were created by mixing of the ultra-low sulphur diesel fuel (ULSDF) with the biodiesel, using different mixture ratios. The individual experiments were performed during a 13-mode test cycle especially developed for the diesel engine in such a way, so that it was possible to identify influence of the engine loading and engine speed on the regulated and unregulated gaseous emissions of the given TDI diesel engine. It is possible to say according to the obtained results that a higher portion of the biodiesel in the fuel mixture reduces the amount of the hydrocarbons (HC), carbon monoxide (CO) and particulate matters (PM) in the gaseous emissions, but it increases volume of the nitrogen oxides (NOX). A higher portion of the biodiesel causes a growth of the formaldehyde emissions and acetaldehyde emissions in the case of unregulated diesel engine emissions. The same trend is also typical for the 1,3-butadiene, propene and ethene. The biodiesel additive increases emissions of benzene; however, it reduces emissions of the toluene and xylene within the aromatic substance emissions. The obtained results confirm a fact that all the gaseous emissions are influenced by the engine operational regimes, especially by the engine loading status.

Deconfliction of Motion Paths With Traffic Inspired Rules

In this letter, we investigate how to resolve conflicting motions for mixed robot–robot and human–robot multiagent systems. This letter is motivated by atypical driving conditions, such as parking lots, where driving rules are not as strictly enforced as on standard roads. As a result, navigation algorithms should take into account the human drivers’ behaviors, especially if they prove to be in conflict with the common rules of the road. In this letter, we make use of safety barrier certificates with a direction bias to deconflict agents’ behavior in a near-to-collision scenario, in compliance with local traffic rules. We also propose a tool to identify the driving direction bias—both for human and autonomous agents.

A contemporary adaptive air suspension using LQR control for passenger vehicles

Long rides on irregular roads and infrastructure problems like uncomfortable seating have a very bad impact on human body. The passengers suffer not only physical pain but also stress related problems. Airsprings gain more popularity in passenger vehicles with an increase in demand for ride comfort. Ride comfort and vehicle handling, being the two critical factors of a suspension system often contradict each other. This led to an extensive research on active automobile suspension systems. The authors of this article propose an innovative design of adaptive air suspension system with LQR control strategy. The proposed LQR controller is tuned by Particle Swarm Optimization. A dynamic model of an air suspension system used in passenger vehicles was designed and simulated for both passive and adaptive systems in MATLAB. An experimental evaluation was done to check the performance of the adaptive air suspension system on a vibration shaker table. Air suspension is a non-linear system and thus the authors have derived a stiffness equation for the same with minimal assumptions. A comparative analysis between the most commonly used PID controller and proposed LQR controller was performed over bumps, potholes and ISO standard random roads in MATLAB. Simulation results showed that adaptive air suspension system improves the ride comfort by reducing the maximum displacement amplitude of the vehicle over random roads by 31% while ensuring the stability of the vehicle by reducing the settling time by 85%. The experimental results of an adaptive air suspension system subjected to random vibrations of frequencies between 5 Hz to 20 Hz, exhibited a reduction of sprung mass acceleration by about 30% demonstrating that the proposed controller is effective for random vibration inputs.

A Unique Barrier Wall and Underpass to Reduce Road Mortality of Three Freshwater Turtle Species

Road mortality has become a primary threat to turtle populations. A variety of strategies have been applied to reduce turtle mortality; however, the effectiveness of these solutions remains largely untested. The few tests that have been conducted have often found the mitigation actions to be ineffective or prohibitively expensive for implementation at a landscape level. Thus, there is a need for inexpensive, effective, and rigorously tested methods for reducing turtle mortality on roads. Here, we investigate the potential efficacy of an inexpensive mitigation strategy, consisting of a barrier wall fabricated from High Density Polyethylene (HDPE) half-pipe, partnered with a pre-existing semiaquatic HDPE culvert as an ecopassage. We used survey data and a Before-After-Control-Impact (BACI) experimental design to assess the effectiveness of the mitigation and quantified the use of the ecopassage at the impact site after the barrier wall was installed. We found a significant interaction between the treatment effect and time period, with the impact site (but not control sites) showing significantly lower turtle counts after mitigation. The barrier wall reduced the number of turtles accessing the road by 94%, and there was no evidence of turtles circumnavigating the barrier. Turtles used the pre-existing culvert to pass under the road. We conclude that HDPE half-pipe partnered with an existing semiaquatic HDPE culvert can reduce road access by, and road mortality of, turtles. The use of standard road construction materials for barrier walls and underpasses results in a cost-effective design scalable to a landscape level.

Cost Effective Alternative Solution for the Renovation of Concrete Pavements

The renovation of concrete pavements (typically motorways) is commonly done by deep replacement of the existing damaged concrete layers including underlying basal layers with newly installed layers with a new surfacing. This technology is rather expensive and time consuming. New alternative solution based on including of intermediate mechanically stabilised layer into road structure is presented. Full scale laboratory model of this structure has been realised. Results and observations are presented. Main contribution of new approach is possibility to remain old concrete layers on place and cover them by new pavement. Standard road structures where concrete layers are overlaid by new pavement in combination with long-term intensive dynamic loading and temperature changes are prone to reflective cracking. Proposed technology avoids that problem and enables cost effective reconstruction of damaged road.

Research on the real-time identification approach of longitudinal road slope and maximum road friction coefficient

Real-time knowledge of maximum road friction coefficient and road slope is crucial for active vehicle control systems. Most recent researches mainly assume that the road slope is constant and the influence on the identification of the maximum road friction coefficient is not considered. In this paper, the IMM Kalman filter method for the identification of road longitudinal slope is developed. Considering the axle load transfer caused by the road slope, the current road type is recognised by comparing the samples of the estimated instantaneous road friction coefficient with each standard road, then the maximum road friction coefficient can be easily determined by an online lookup table. Finally, experimental tests on the braking system hardware-in-the-loop test rig driven by the driving simulator are conducted. The results demonstrate that the identification approach can identify the current road slope and maximum road friction coefficient with good adaptability to various vehicle conditions.

Modeling of an active torsion bar automotive suspension for ride comfort and energy analysis in standard road profiles

Chassis technology is evolving towards active suspension, in which actuators can provide forces to each wheel individually. This overcomes the traditional trade-off between comfort and handling, at the expense of increased complexity and electric consumption. To reduce power demand, regenerative solutions capable of harvesting a certain amount of energy otherwise dissipated in vehicle suspensions and to enhance vehicle dynamics for improving ride comfort and road safety at the same time have been researched. In this paper, an active suspension based on a torsion bar is modeled and analyzed under the excitation from standardized road profiles according to the ISO 8608 norm. A skyhook controller was implemented in a quarter-car model for assessment of the ride comfort, power consumption and harvesting potential of a DC motor according to the four-quadrant operation, working as a generator. From simulations, results show that for a velocity of 50 km/h it is possible to harvest 50-60 W from a vehicle driving in a class C road with ride comfort trade-off. This constitutes around 25% of the power consumption of the active suspension system.

Aerodynamic Design of a Solar Road Vehicle

Solar road vehicles have very specific design requirements. This makes their aerodynamic characteristics quite different from classic sedan vehicles. In the present study, the computational model of a typical solar road vehicle was developed to investigate its aerodynamic forces and flow characteristics. Computations were performed assuming the steady viscous flow and using the Reynolds-averaged Navier Stokes equations along with the k-ω turbulence model. The obtained results indicate some important findings that are commonly not present for classic sedan vehicles. In particular, a contribution of the viscous drag force to the overall drag force is considerably larger (41 %) than it is the case for the standard passenger road vehicles, where the form drag force dominates over the viscous drag force. Surface pressure distribution patterns indicate a favorable aerodynamic design of this vehicle. In particular, larger pressure coefficients on the top of the vehicle body as compared to the bottom surface contribute to increasing a downforce and thus the vehicle traction. The airfoil-shaped crosssection of the designed cockpit canopy has favorable properties with respect to reduction of the aerodynamic drag force.

Vehicle Exhaust Emission Characteristics and Their Contributions in Jiangsu Province

An hourly vehicular emission inventory with 1 km×1 km resolution was developed for Jiangsu Province in 2015, using the COPERT model and ArcGIS technology. The improved "standard road length" method, as well as road network information and monthly, weekly, and daily variations of the congestion delay index were used to increase temporal-spatial resolution. The contributions of different vehicle types, emission standards, and road types to total vehicular emissions were analyzed. Results showed that vehicular emissions of NOx, HC, CO, PM2.5, SO2, OM, and BC were 490.9, 166.3, 1614.8, 16.9, 1.9, 3.6, and 6.7 thousand tons, respectively. On average, Suzhou and Xuzhou contributed 34%-45% of the total. Evaporative emissions of HC were 20.2 thousand tons, accounting for 12% of total HC emissions. Small passenger cars and motorcycles were the major HC and CO contributors, accounting for over 30% of total emissions. Heavy-duty diesel trucks contributed 36%-54% to NOx, PM2.5, SO2, OM, and BC emissions, representing much higher emissions than other vehicles. Heavy-duty and medium-duty diesel trucks in Suzhou and Xuzhou are the main sources of NOx and PM2.5emissions. China Ⅲ diesel vehicles account for the largest share (42%-55%) of NOx, PM2.5, SO2, and BC emissions. China Ⅲ heavy-duty diesel trucks and China 0 medium-duty diesel trucks are the primary and secondary contributors of NOx, PM2.5, OM, and BC emissions, with a total share of 40%-56%. China 0 motorcycles contributed about 16% to total HC and CO.

Speed independent road classification strategy based on vehicle response: Theory and experimental validation

Abstract This paper presents a speed-independent road classification strategy (SIRCS) based on sole measurement of unsprung mass acceleration. The new method provides an easy yet accurate classification methodology. To this purpose, a classification framework with two phases named off-line and online is proposed. In the off-line phase, the transfer function from unsprung mass acceleration to the road excitation is firstly formulated, and a random forest-based frequency domain classifier is then generated according to the standard road definition of ISO 8608. In the online phase, unsprung mass acceleration and vehicle velocity are firstly combined to calculate the equivalent road profile in the spatial domain, and then a two-step road classifier attributes the road excitation to a certain level based on the power spectral density (PSD) of the equivalent road profile. Simulations are carried out for different classification intervals, varying velocity, system uncertainties and measurement noises. Road experiments are finally performed in a production vehicle to validate the proposed SIRCS. Measurement of only unsprung mass acceleration to identify road classification and less rely on the training data are the major contributions of the proposed strategy.

Lane Detection Based on Connection of Various Feature Extraction Methods

Lane detection is a challenging problem. It has attracted the attention of the computer vision community for several decades. Essentially, lane detection is a multifeature detection problem that has become a real challenge for computer vision and machine learning techniques. Although many machine learning methods are used for lane detection, they are mainly used for classification rather than feature design. But modern machine learning methods can be used to identify the features that are rich in recognition and have achieved success in feature detection tests. However, these methods have not been fully implemented in the efficiency and accuracy of lane detection. In this paper, we propose a new method to solve it. We introduce a new method of preprocessing and ROI selection. The main goal is to use the HSV colour transformation to extract the white features and add preliminary edge feature detection in the preprocessing stage and then select ROI on the basis of the proposed preprocessing. This new preprocessing method is used to detect the lane. By using the standard KITTI road database to evaluate the proposed method, the results obtained are superior to the existing preprocessing and ROI selection techniques.

Wheel Force Sensor-Based Techniques for Wear Detection and Analysis of a Special Road.

Automobile proving ground is important for the research of vehicles which are used for vehicle dynamics, durability testing, braking testing, etc. However, the road in automobile proving grounds will inevitably be damaged with the extension of the service life. In most previous research, equipment similar to a laser profilometer was used to detect the quality of the road, the principle of which is to reflect the quality of the road by measuring the roughness of the pavement. This method ignores the elastic deformation of the road itself when the vehicle is traveling and it is difficult to compensate for the error. Therefore, this paper presents a new method based on a force sensor to reduce the impact of elastic deformation, such as tire deformation, pavement deformation, and wheel rim deformation. In this study, force sensors mounted on the wheels collect the three-dimensional dynamic force of the wheel. The presented method has been tested with two sets of cobblestone road loads, and the result shows that the load intensities imposed by the test vehicle on the target road are 88.3%, 91.0%, and 92.05% of the intensity of the load imposed by the test vehicle on a standard road in three respective dimensions. It is clear that the proposed method has strong potential effectiveness to be applied for wear detection and analysis of a special road.

Beyond Standard Zonal Congestion Pricing: A Detailed Impact Analysis

AbstractThis study formulates three fundamental extensions of the standard optimal road use analysis: (1) considering fuel and emissions as variable costs, (2) maximizing the social welfare inside ...

Using road markings as a continuous cue for speed choice

The potential for using road markings to indicate speed limits was investigated in a driving simulator over the course of two sessions. Two types of experimental road markings, an “Attentional” set designed to provide visually distinct cues to indicate speed limits of 60, 80 and 100 km/h, and a “Perceptual” set designed to also affect drivers’ perception of speed, were compared to a standard undifferentiated set of markings. Participants (n = 20 per group) were assigned to one of four experimental groups (Attentional-Explicit, Attentional-Implicit, Perceptual-Explicit, Perceptual-Implicit) or a Control group (n = 22; standard road markings). The Explicit groups were instructed about the meaning of the road markings while those in the Implicit and Control groups did not receive any explanation. Participants drove five 10 km simulated roads containing three speed zones (60, 80 and 100 km/h) during the first session. The participants returned to the laboratory approximately 3 days later to drive five more trials including roads they had not seen before, a trial that included a secondary task, and a trial where speed signs were removed and only markings were present. The findings indicated that both types of road markings improved drivers’ compliance with speed limits compared to the control group, but that explicit instruction as to the meaning of the markings was needed to realise their full benefit. Although previous research has indicated the benefit of road markings used as warnings to indicate speed reductions in advance of horizontal or vertical curves, the findings of the present experiment also suggest that systematically associating road markings with specific speed limits may be a useful way to improve speed limit compliance and increase speed homogeneity.

A feedback linearization controller combined with a data-driven subspace-based prediction method for vehicle handling stabilization

Obtaining precise yaw rate and lateral velocity as well as developing a nonlinear controller becomes more and more essential for improving the vehicle handling performance. Different from traditional methods, a data-driven subspace-based prediction approach is introduced by integrating propagator with predictor-based subspace identification method in this paper. Based on an identifiable vehicle model, the prediction process is validated by standard road tests data. To employ this data-driven prediction method in the vehicle handling stabilization and solve the controlling problem of nonlinear lateral dynamic system, a feedback linearization controller based on the new piecewise tire model is elaborately developed. On account of that the one-step prediction output reduces the time delay between actuator and lateral dynamic response, the subspace-based controller can theoretically improve the vehicle handling performance. By road simulation results, the proposed feedback linearization controller combined with a data-driven subspace-based prediction method greatly enhances the handling performance and provides a more effective technique for both vehicle parameter estimation and handling stabilization.