Low Vehicle Speeds Research Articles

Sustainable charged composites with amphiphobic surfaces for harsh environment–tolerant non-contact mode triboelectric nanogenerators

In this work, the sustainable charged composites with amphiphobic surfaces are reported regarding harsh environment tolerance and robust contactless mode triboelectric nanogenerators (TENGs). SiO2 and polytetrafluoroethylene (PTFE) particles are well dispersed in thermoplastic polyurethane (TPU) and polydimethylsiloxane (PDMS), respectively. Both surfaces become very rough after a chemical etching method and the surface of PTFE-PDMS is fluorinated using a fluorinated alkylsilane, resulted in the formation of amphiphobic surfaces. This significantly enhances the environment tolerance of the contactless mode TENGs as well as the charge retention characteristics of the composites. As a practical non-contact mode application, a speed sensor fabricated using two composites can stably detect a low vehicle speed less than 3.75 km/h when exposed to high humidity (∼ 99%) and various chemical oils. Over 50% of initial output voltage are still generated after 2 weeks with no more decrease after 5 days, showing a 1.4 times slower charge decay rate, compared with the reference Ni-PTFE based TENG.

Impact of the tyre dynamics on autonomous vehicle path following control with front wheel steering and differential motor torque

AbstractThis paper investigates the impact of tyre dynamics on autonomous vehicle dynamic control. The commonly used 2 degrees of freedom bicycle model and a detailed vehicle model considering tyre dynamics are built, respectively, to describe the vehicle dynamics. The two models are firstly compared with the response to front wheel steering input and differential motor torque input. The transient vehicle body vibrations are clearly demonstrated by the detailed model but overlooked by the bicycle model. The influence of tyre nonlinearity on path offset is also revealed. Then, the path following control strategy is designed based on the linear quadratic regulator control to compare the two models from the path following performance perspective. The double lane change simulation is conducted. The results show that at low vehicle speed, the path following errors of two models are very close, which proves the rationality of using the bicycle model to represent the vehicle dynamics in mild and moderate driving conditions. However, when the path following is conducted with high vehicle speed, the required lateral tyre force is large, so the tyres work with large slip angles and the tyre nonlinearity generates significant deviation on the path following errors between the two models.

Investigation of Heavy-Duty Vehicle Chassis Dynamometer Fuel Consumption and CO2 Emissions Based on a Binning-Reconstruction Model Using Real-Road Data

Global warming is directly related to heavy-duty vehicle fuel consumption and greenhouse gas (CO2 mainly) emissions, which, in China, are certified on the vehicle chassis dynamometer. Currently, vast amounts of vehicle real-road data from the portable emission measurement system (PEMS) and remote monitoring are being collected worldwide. In this study, a binning-reconstruction calculation model is proposed, to predict the chassis dynamometer fuel consumption and CO2 emissions with real-road data, regardless of operating conditions. The model is validated against chassis dynamometer and PEMS test results, and remote monitoring data. Furthermore, based on the proposed model, the fuel consumption levels of 1408 heavy-duty vehicles in China are analyzed, to evaluate the challenge to meet the upcoming China fourth stage fuel consumption limits. For accumulated fuel consumption based on the on-board diagnostic (OBD) data stream, a predictive relative error less than 5% is expected for the present model. For bag sampling results, the proposed model’s accuracy is expected to be within 10%. The average relative errors between the average fuel consumption and the China fourth stage limits are about 3%, 8%, and 0.7%, for current trucks, tractors, and dump trucks, respectively. The urban operating condition, with lower vehicle speeds, is the main challenge for fuel consumption optimization.

Are bicycle streets cyclist-friendly? Micro-environmental factors for improving perceived safety when cycling in mixed traffic

A bicycle street is a mixed traffic street where motor vehicles are forced to adapt their speed to bicycle traffic, for example by encouraging cycling in the middle of the street using centered bicycle lanes. The objective safety of cyclists increases with lower vehicle speeds and fewer motor vehicles. Despite this, cyclists’ perception of their safety is often reduced in mixed traffic streets. Subjective unsafety and risk constitute a major barrier to increased cycling.This study investigates how the design of the micro-environment of bicycle streets can improve cyclists’ perceived safety in mixed traffic. A quasi-experimental survey in which 371 participants rated their perceived safety in photo-manipulated bicycle streets was conducted. 52% of the participants were male, the mean age was 43 (20–77) years, and 76% reported that they cycle 4–5 days a week or more. The focus was on evaluating micro-environmental factors such as different designs of centered bicycle lanes, road markings, signs, traffic volume, and parked cars.It is concluded that the micro-environment has important effects on the perceived safety of cyclists. Important gains in subjective safety can be achieved with fairly simple design efforts. Many participants felt safe when there were clearly demarcated red-colored bicycle lanes in the center of the street accompanied by road markings for cyclists. The strongest effect, however, comes from reducing traffic volume. Most participants felt safe in micro-environments in which the traffic volume had been reduced, including those where no design changes had been made. Important differences between different groups of cyclists were also found.

A New Drive-by Method for Bridge Damage Inspection Based on Characteristic Wavelet Coefficient

The drive-by method has become a popular indirect approach for bridge damage inspection (BDI) because of its simplicity in deployment by evaluating the bridge health status solely via the vehicle dynamic response. Derived from the vehicle dynamic response, the recent proposed contact-point response involves no vibration signal with the vehicle frequency, bearing great potential for drive-by BDI. However, an appropriate methodology for the application of contact-point response in drive-by BDI remains lacking. The present study proposes a novel drive-by method, in which a new damage factor index, i.e., the characteristic wavelet coefficient (CWC), is established for bridge damage identification in an efficient and accurate manner. The CWC is obtained by analyzing the contact-point response via the continuous wavelet transform (CWT) and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) techniques. CEEMDAN is introduced to overcome the issue of modal aliasing and pseudo-frequency. First, the general framework of the proposed drive-by BDI method is introduced. Then, a demonstration case study is carried out to examine the effectiveness of the proposed method. Subsequently, a parametric study is carried out to explore the effects of several parameters on the performance of BDI including the scale factor, vehicle speed, environmental noise, and boundary effect. The results indicate that the proposed drive-by BDI method can better eliminate the mode mixing and pseudo-frequency problems during the extraction of the CWC, compared with the traditional ensemble empirical mode decomposition method. The extracted CWC curve is smooth, convenient for damage inspection, and has strong anti-noise performance. After adding white noise with a signal-to-noise ratio of 20, a bridge girder with a damage severity of 20% can be identified successfully. In addition, the selection of the scale factor is critical for bridge damage inspection based on the extracted CWC. The effective scale factor of the CWC extracted using the proposed method has a wide range, which improves the inspection efficiency. Finally, a low vehicle speed is beneficial to alleviate the adverse effect of the boundary effect on the damage inspection of bridge girder ends.

Dynamic behavior of crack sealant bonding interface in the asphalt pavement crack repair structure under moving vehicle load

Crack sealing with hot-applied sealant is a widely used technology for asphalt pavement crack repair, but the sealant usually occurs bond failure at an early stage. Due to the research on the mechanical changing characteristics of crack sealant bonding interface is insufficient, the systematic analysis and explanation for the early failure phenomenon is lack. Based on this, a 3D finite element (FE) model of asphalt pavement with crack repair structure is established to study the dynamic behavior characteristic of crack sealant. Firstly, the dynamic response characteristics of the crack sealant bonding interface under different repair groove sizes and forms are systematically analyzed. Then the recommended repair groove size range is given accordingly. Secondly, the effects of different vehicle speeds and axle loads on the dynamic response of the crack sealant bonding interface are analyzed. The results show that lower vehicle speeds and higher axle loads result in higher stress levels at the crack sealant bonding interface, the sensitivity of tensile stress to vehicle speed and axle load is higher than that of shear stress. Finally, the temperature stress field of the repair structure is used as a predefined field and imported into the 3D FE model. The dynamic response of crack sealant bonding interface under thermal-mechanical coupling is analyzed. The results show that the tensile stress of bonding interface is mainly affected by temperature conditions, and the vehicle load is the primary factor affecting the level of shear stress. The research findings provide a scientific insights and guidance for the evaluation of crack sealant performance and the improvement of crack repair technology.

Influences of bus traffic loading on asphalt concrete rutting

ABSTRACT Permanent deformation is the primary failure mode for the asphalt concrete (AC) pavement in urban environment. It is mainly caused by a combination of heavy traffic load, low vehicle speed and channelised traffic. A rut prediction model would therefore be a valuable tool for planning maintenance scheduling and selecting an appropriate asphalt material. This study uses the PEDRO (Permanent deformation in asphalt concrete layers for roads) model to evaluate the rutting performance of flexible pavements in dedicated bus lanes and intersections in urban areas. For this purpose, three road sections along a bus lane in Malmö, Sweden, were selected. To achieve this, AC cores from the road sections were tested using a Shear Box Tester to characterise the asphalt mixtures. Traffic data such as axle load, tyre configuration, speed, and lateral wander distribution of vehicles, and climate data were measured for the selected sections. Field measurements were carried out to assess the structural conditions of the pavements and to measure transverse profiles. This study introduced a procedure for the evaluation and local calibration of the PEDRO rutting model. The results revealed that the prediction of the transverse profiles are generally in good agreement with the rut measurements.

Analysis of Motorized Vehicles Performance at Signalized Intersections Based on Micro Simulation

Based on microsimulation, this study analyses the performance and behavior of motorized vehicles at the signalized intersection between the railway line and Ahmad Yani road-Jemursari road. For the survey of the volume of motorized vehicles, this intersection is divided into four intersections with eight directions of traffic movement and one direction of combined traffic movement. Microsimulation was carried out using Vissim software with nine parameters calibrated according to actual conditions during the peak hour observation period. The maximum queue length and motor vehicle delays for the peak hour observation period occur at intersections one in the north and two in the east. Performance of the intersection of Jl. Ahmad Yani-Jl. Jemursari is included in category F. The indicator F are traffic jams, low vehicle speeds, long queues, and vehicle delays. The following study of this paper is to make a geometric model of the intersection into a Fly Over model.

A Lightweight Two-Stream Model for Driver Emotion Recognition

In recent years, more and more attention has been paid to the traffic safety of drivers. Studies show that the motor vehicle speed will affect the incidence of traffic accidents and traffic accident casualty rate. In this paper, machine learning vision technology is used for real-time recognition of driver emotions, and a lightweight SIC-NET+RC-NET dual-stream recognition model is designed to cope with different scenarios of vehicle speed during driving. SIC-NET is a lightweight CNN network model, which greatly reduces the number of model parameters and computational power requirements, sacrifices part of accuracy, and greatly improves the real-time performance of model recognition. To improve the residual convolutional network model of inception blocks, RC-NET nested multiple micro-convolutional neural networks are used to identity mapping between different inception blocks to enhance the network training effect, expand network width and convolutional depth, and alleviate network degradation. This article stipulates that when the vehicle speed is greater than 60km/h, SIC-NET is used. When the vehicle speed is less than or equal to 60km/h, SIC-NET+RC-NRT is used. The FER2013 dataset was used for testing and validation in this paper. When SIC-NET is used, the model has better real-time performance and can provide a more timely warning when the vehicle speed is higher. When SIC-NET+RC-NET is used, the accuracy of the model in the FER2013 dataset is 69.65%, and the model can better cope with the scenario of a low vehicle speed. The experiment shows that the lightweight dual-flow model has good robustness and identification effect, which solves the problem of using the same model for different vehicle speeds and can effectively ensure the safety of the driver’s life and property.

Optimization of Gain Scheduled Controller for an Active Trailer Steering System Using an Evolutionary Algorithm

Car–trailer combinations can experience unstable motion modes such as trailer-sway, jackknifing and rollover that can lead to fatal accidents. These unstable motions can be mitigated with the use of an active trailer steering (ATS) system. Prior studies in ATS have leveraged the linear quadratic regulator (LQR) as an ATS controller but for many of these designs it was assumed that the vehicle and operating parameters were constant. In reality, vehicle and operating parameters may vary and have an impact on the stability of a car–trailer combination. In this paper, the weighting matrices of the LQR controller are determined using the GDE3 evolutionary optimization algorithm with the objective of addressing the design trade off between minimizing the car–trailer’s path-following performance for low vehicle speeds and minimizing the rearward amplification for high vehicle speeds. The effectiveness of the approach is demonstrated using a numerical simulation car–trailer model developed in the CarSim simulator. Our results show that the multi-objective tuned gain scheduling controller outperforms a non-tuned gain scheduling controller in terms of improving the lateral stability and the path following performance of car–trailer combinations in driver in the loop single lane-change maneuvers at a constant vehicle forward speed.

A Torque Conversion Solution to the Powertrain of Mobile Machine and Its Control Strategy

The demand for reducing fuel consumption and emission of mobile machines is increasing since they consume large amount of energy and generate huge exhaust each year. The wheel loader is a representative mobile machine and large wheel loader typically employs a hydrodynamic torque converter and an automatic transmission in the powertrain. The torque converter provides large torque amplification at low vehicle speed, however generates large amount of heat inside. This brings a challenge during frequent vehicle start and stop. In this study, an alternative torque conversion solution to the powertrain of mobile machine with a power split hydraulic transmission is proposed, where the hydraulic transmission is a substitute for the torque converter. It eliminates overheating problem by dissipating the heat inside through its outlet. The mathematical models of the proposed powertrain including the wheel drive and working function are developed. An engine-speed-based system optimization is conducted and a rule-based control strategy based on optimization results is developed. The engine operations and engine fuel consumptions with optimization-based and rule-based control strategies are compared using three different loading cycles (57 s, 30 s, 90 s). The results show the effectiveness of proposed powertrain solution and its control strategy.

Impact of Primary User Activity Statistics in Cognitive Vehicular Networks

Due to the scarcity of channel availability in IEEE 802.11p standard, applications related to infotainment and multimedia services are vulnerable to suffer from delays and connectivity. Cognitive radio (CR) has the potential to overcome the issue of spectrum scarcity. By making use of the CR technology, secondary users (SU) can access a radio frequency spectrum other than 802.11p through spectrum sensing. Majority of low complex existing algorithms are based on energy detection that are considering the static environment of SUs. In practice, the algorithms, which considers mobility are mainly focused on low vehicle speed. However, the combined effect of primary user (PU) activity statistics and SU mobility has not been tackled while evaluating the performance of opportunistic spectrum access. In particular, this work considers the joint impact of PU activity and vehicle mobility on spectrum sensing performance by considering single lane and double lane vehicular scenarios. We also evaluate the impact of traffic densities on sensing performance. The main contribution of this work is to show the impact of PU activity statistics on sensing performance by deriving analytical expressions for miss-detection probability. These expressions are used for analysis and simulation of cognitive radio enabled vehicular communications. From our observations, it is noted that the probability of vehicle connectivity is improved approximately by 50 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> for initial distance of SU when spectrum sensing is employed under PU activity.

Fundamentals of Motion Planning for Mitigating Motion Sickness in Automated Vehicles

This paper investigates the fundamentals of motion planning for minimizing motion sickness in transportation systems of higher automation levels. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one within specific and given boundaries and constraints in order to minimize the motion sickness and the journey time. An empirical approach based on British standard is used to evaluate motion sickness. The trade-off between minimizing motion sickness and journey time is investigated through multi-objective optimization by altering the weighting factors. The correlation between sickness and journey time is represented as a Pareto front because of their conflicting relation. The compromise between the two components is quantified along the curve, while the severity of the sickness is determined using frequency analysis. In addition, three case studies are developed to investigate the effect of driving style, vehicle speed, and road width, which can be considered among the main factors affecting motion sickness. According to the results, the driving style has higher impact on both motion sickness and journey time compared to the vehicle speed and the road width. The benefit of higher vehicle speed gives shorter journey time while maintaining relatively lower illness rating compared with lower vehicle speed. The effect of the road width is negligible on both sickness and journey time when travelling on a longer road. The results pave the path for the development of vehicular technologies to implement for real-world driving from the outcomes of this paper.

Low Vehicle Speeds Regenerative Anti-lock Braking System

The utilization of Regenerative Anti-lock Braking System (RABS) for saving energy in electric and hybrid vehicles has been previously studied, but to the best of our knowledge this study is the first to assess enhancing regenerative braking performance at low speeds. The proposed system detects the type of the road condition and adapts braking performance with road condition. RABS comprehensive model is constructed using Matlab/Simulink simulation for optimization of the the control system performance during braking on different terrains. Additionally, an experimental test rig is constructed on a hybrid golf cart where two modes of control are tested on different road conditions; the speed reducing mode and the stopping mode. Efficiency of converting lost braking energy to useful charge to the batteries reaches up to 30% at speeds lower than 10 km/hr.

A novel dynamics model of a trailer bogie brake system and its application in stability analysis

The dynamic performance of the trailer bogie brake system is essential for the safe operation of a high-speed train during the braking process. In this work, we developed a novel ten-degree-of-freedom (ten-DOF) dynamics model of a trailer bogie brake system based on dynamic and tribological theories. The non-linear factors including disc-pad non-linear friction and wheel-rail non-linear interactions were considered. The field test results demonstrated that more intense vibrations occur at low vehicle speeds, which is also supported by numerical simulations based on the novel dynamics model. The abnormal vibration is caused by the limit cycle oscillation of the brake unit, and it leads to the instability of the whole system. To further understand the instability of the trailer bogie brake system, the equilibrium points and the linear stability of the system under different braking conditions and suspension parameters were investigated based on the Lyapunov theory. Then, the non-linear vibration response and stability of the trailer bogie brake system affected by the suspension parameters were further calculated by numerical integration methods. The results demonstrated that the mounting stiffness of the brake unit approached 3.4×107N/m and the primary suspension stiffness approached 6.0×105N/m or remained within the range of 10×105-14×105N/m, causing more violent vibrations and increased system instability. A primary suspension damping exceeding 2.4×104N·s/m was conducive to improving system stability.

Design and optimization of an automatic hydraulic steer-by-wire system for an agricultural chassis

To meet the requirements of fast steering at low vehicle speed and slow steering at high vehicle speed, the automatic steering of agricultural chassis must control both the wheel steering angle and the steering angle’s angular speed. This study applied hydraulic steer-by-wire technology to the automatic steering control of agricultural chassis. First, the transmission mechanism of the designed steering system was optimized. According to the rule of least squares, aiming at the minimum sum of squares of errors between 10 ideal outer wheel angles and real outer wheel angles, the optimal solution of hole spacing on both sides of the steering hydraulic cylinder piston rod was 925 mm. The outer wheel angle error of the optimized steering mechanism throughout the steering stroke was less than 0.15°. Additionally, a hydraulic steer-by-wire system was developed, and the parameters of its critical components were calculated. Then, the compound control strategy of the steering cylinder piston rod displacement and moving speed was formulated for this automatic steering system. The entire control system included a valve control signal calculation model, an initial velocity calculation model, a correction velocity calculation model, and an attenuation velocity calculation model, and the formulae of each model were deduced. Based on the optimized parameters and the developed control strategy, a simulation model was built in AMESim, and simulation results showed that the proposed control strategy could achieve simultaneous controls of piston rod displacement and speed at different vehicle speeds and loads. The horizontal and vertical displacements of the right wheel center were plotted for typical vehicle speeds and steering commands. The results of this study provided a new idea for the application of hydraulic steer-by-wire technology in the automatic steering of agricultural chassis. Keywords: optimal design, steering mechanism, automatic steering, simulation analysis DOI: 10.25165/j.ijabe.20221501.6755 Citation: Jin Y H, Yuan Y W, Zhu L C, Wang D C, Zhao B, Fang X F. Design and optimization of an automatic hydraulic steer-by-wire system for an agricultural chassis. Int J Agric & Biol Eng, 2022; 15(1): 132–138.

Modeling commercial vehicle drivers’ acceptance of advanced driving assistance system (ADAS)

PurposeAdvanced driving assistance system (ADAS) has been applied in commercial vehicles. This paper aims to evaluate the influence factors of commercial vehicle drivers’ acceptance on ADAS and explore the characteristics of each key factors. Two most widely used functions, forward collision warning (FCW) and lane departure warning (LDW), were considered in this paper.Design/methodology/approachA random forests algorithm was applied to evaluate the influence factors of commercial drivers’ acceptance. ADAS data of 24 commercial vehicles were recorded from 1 November to 21 December 2018, in Jiangsu province. Respond or not was set as dependent variables, while six influence factors were considered.FindingsThe acceptance rate for FCW and LDW systems was 69.52% and 38.76%, respectively. The accuracy of random forests model for FCW and LDW systems is 0.816 and 0.820, respectively. For FCW system, vehicle speed, duration time and warning hour are three key factors. Drivers prefer to respond in a short duration during daytime and low vehicle speed. While for LDW system, duration time, vehicle speed and driver age are three key factors. Older drivers have higher respond probability under higher vehicle speed, and the respond time is longer than FCW system.Originality/valueFew research studies have focused on the attitudes of commercial vehicle drivers, though commercial vehicle accidents were proved to be more severe than passenger vehicles. The results of this study can help researchers to better understand the behavior of commercial vehicle drivers and make corresponding recommendations for ADAS of commercial vehicles.

Evaluating the cooling performance of light commercial vehicle with water-cooled engine systems - an approach beyond regulatory standards

The objective of the paper is to evaluate the Engine cooling performance of the light commercial vehicle by data acquisition. The data acquisition is done following Indian standard, IS: 14557:1998. Sometimes, the ambient temperature conditions and actual vehicle parameters may differ, then as mentioned in standard, thus making it necessary to go beyond standard conditions. The methodology of testing is to acquire data and compare the thermal behaviour in five different vehicle configurations. In the first case, a subjected vehicle was operated with a conventional fixed fan that is permanently engaged and a smaller radiator, which more or less resulted in overheating of the vehicle. Then in the second case, data is acquired with a viscous fan, bigger core radiator, fresh air cleaner. The viscous fan operates only when the coolant temperature goes beyond a specified limit. It gives a better cooling performance, lower cabin noise, and higher fuel efficiencies. In the third case, a fresh air cleaner is replaced with a clogged air cleaner, to simulate extreme dusty, off-road conditions like mining, where power and torque demand is maximum and the vehicle operates at lower vehicle speeds. In the fourth and fifth cases, experiments were conducted to check the actual performance of the vehicle on plain roads and hilly routes for a better driving simulation. The specific finding of the paper is that a vehicle may clear the cooling performance according to the standard requirements, but it may fail in the actual field conditions. So, a factor of safety must be considered while designing an engine cooling system, which makes it fit for worse field applications. Finally, the gathered data is used to upgrade the engine cooling management system.

Nonlinear behaviors of the disc brake system under the effect of wheel−rail adhesion

In this study, a three-degree-of-freedom dynamic model of a disc brake system for a high-speed train is established by considering disc−pad nonlinear friction, wheel−rail adhesion and different numbers of brake units. The stability and nonlinear behaviors of the brake system are systematically explored by using the numerical integration method. The results show that the brake system alternately presents periodic and chaotic motions with the increment of the normal brake force. The violent and chaotic friction-induced stick−slip vibration occurs only in a low vehicle speed range, and the same phenomenon is observed in a field test. Moreover, the chaotic region of the disc brake system with three brake units is less than that of the system with two, indicating a better stability performance.

Viscoelastic analysis of surface responses in flexible pavements under different loading conditions

Due to time-temperature dependent behavior of asphalt concrete (AC), viscoelastic analysis is necessary for understanding the mechanism of top-down cracking (TDC). In this study, a new approach for determining the viscoelastic surface responses of multi-layered asphalt pavements was developed to solve the complicated oscillating behavior and slow convergence of the integrand of Laplace-transformed step-response function at pavement surface. By employing the Lucas algorithm, the irregular oscillations were reduced to regular oscillations by separating the integrand into high- and low-frequency components. The results calculated from the proposed approach were widely verified against finite element (FE) results. According to horizontal strains calculated at pavement surface, mechanism of TDC initiation was investigated under stationary and moving loads. The results indicated that high temperature and low vehicle speed were among the predominant factors contributing to TDC initiation. In addition, TDCs were more likely to initiate at a very close distance to the tire edge.