Browse Topic: Steering systems

Items (2,079)
With the continuous development of automobile technology, vehicle handling performance and safety have become increasingly critical research areas. The active rear-wheel (ARW) steering system, a technology that significantly enhances vehicle dynamics and driving stability, has garnered widespread attention. By coordinating front-wheel steering with rear-wheel angle adjustments, ARW improves handling flexibility and stability, particularly during high-speed driving and under extreme conditions. Therefore, designing an efficient ARW control algorithm and optimizing its performance are vital to enhancing a vehicle's overall handling capability. This study delves into the control algorithm design and performance optimization of ARW. First, a comprehensive vehicle dynamics model is constructed to provide a solid theoretical basis for developing control algorithms. Next, optimal control theory is applied to regulate the rear-wheel steering angle, and an LQR control strategy with variable
Zhang, YiZheng, HongyuKaku, ChuyoZong, ChangfuZhang, Yuzhou
FSAE is a competition designed to maximize car performance, in which the steering system is a key subsystem, and the steering system performance directly affects the cornering performance of the car. The driver relies on the steering system for effective handling, which is also crucial for cornering and achieving faster lap times. Therefore, while improving the performance of the steering system, it is crucial to match the vehicle design to the driver's habits. Traditionally, steering systems typically use an Ackermann rate between 0% and 100% to offset the slip angle caused by tire deformation, thus achieving the purpose of reducing tire wear. Calculations have shown that a 40-60% Ackermann rate provides a similar compensation effect with little difference in tire wear. The traditional steering design method also does not consider the driver's driving habits and feedback, which is not conducive to the improvement of the overall performance of the car. In FSAE's figure-of-eight loops
Wu, HailinLi, Mingyuan
Objective: This study aims to evaluate the biofidelity of the Advanced Chinese Human Body Model (AC-HUMs) by utilizing a generic sedan buck model and post-mortem human surrogates (PMHS) test data. Methods: The boundary conditions of the simulation were derived from the PMHS test with the buck vehicle. The methodology involved the pose adjustment of the upper and lower extremities of AC-HUMs, executed through a pre-simulation approach. Subsequently, a 200 milliseconds whole body pedestrian crash simulation was conducted using the buck vehicle and the AC-HUMs pedestrian model. The trajectories of AC-HUMs during the period from initial position to head impact were recorded, including the Head CG, T1, T8 and pelvis. Based on the knee joint, the corridors of trajectories from the PMHS test were scaled to match the Chinese 50th percentile male to evaluate the biofidelity of AC-HUMs's kinematic response. Furthermore, the biomechanical responses were compared with the PMHS tests, including
Qian, JiaqiWang, QiangLiu, YuWu, XiaofanHuida, ZhangBai, Zhonghao
As the autonomy of ADAS features are moving from SAE level 0 autonomy to SAE level 5 autonomy of operation, reliance on AI/ML based algorithms in ADAS critical functions like perception, fusion and path planning are increasing predominantly. AI/ML based algorithms offer exceptional performance of the ADAS features, at the same time these advanced algorithms also bring in safety challenges as well. This paper explores the functional safety aspects of AI/ML based systems in ADAS functions like perception, object fusion and path planning, by discussing the safety requirements development for AI/ML systems, dataset safety life cycle, verification and validation of AI systems, and safety analysis used for AI systems. Among all the safety aspects listed above, emphasis is put on dataset safety lifecycle as that is not only the most important element for training ML based algorithms for ADAS usage, but also the most cumbersome and expensive. The safety characteristics associated with dataset
Mudunuri, Venkateswara RajuAlmasri, HossamFan, Hsing-HuaChandrasekaran, Mukund
Onboard sensing and Vehicle-to-Everything (V2X) connectivity enhance a vehicle's situational awareness beyond direct line-of-sight scenarios. A team led by Southwest Research Institute (SwRI) demonstrated 20% energy savings by leveraging these information streams on a 2017 Prius Prime as part of the first phase of the ARPA-E-funded NEXTCAR program. Combining this technology with automation can improve vehicle safety and enhance energy efficiency further. In the second phase, SwRI demonstrated 30% energy savings over the baseline. This paper summarizes the efforts to achieve 30% savings on a 2021 Honda Clarity PHEV. The vehicle was outfitted with the SwRI Ranger automated driving suite for perception and localization. Model-based control schemes with selective interrupt and control (SIC) were used to override stock vehicle controls and actuate the accelerator, brake, and electric power steering system, enabling drive-by-wire and steer-by-wire functionalities. Key algorithms contributing
Bhagdikar, PiyushGankov, StanislavSarlashkar, JayantHotz, ScottRajakumar Deshpande, ShreshtaRengarajan, SankarAdsule, KartikDrallmeier, JosephD'Souza, DanielAlden, JoshuaBhattacharjya, Shuvodeep
The slope and curvature of spiral ramps in underground parking garages change continuously, and often lacks of predefined map information. Traditional planning algorithms is difficult to ensure safety and real-time performance for autonomous vehicles entering and exiting underground parking garages. Therefore, this study proposed the Model Predictive Path Integral (MPPI) method, focusing on solving motion planning problems in underground parking garages without predefined map information. This sample-based method to allows simultaneous online autonomous vehicle planning and tracking while not relying on predefined map information,along with adjusting the driving path accordingly. Key path points in the spiral ramp environment were defined by curvature, where reducing the dimensionality of the sampling space and optimizing the computational efficiency of sampled trajectories within the MPPI framework. This ensured the safety and computational speed of the improved MPPI method in motion
Liu, ZuyangShen, YanhuaWang, Kaidi
The research activity aims at defining specific Operational Design Domains (ODDs) representative of Italian traffic environments. The paper focuses on the human-machine interaction in Automated Driving (AD), with a focus on take-over scenarios. The study, part of the European/Italian project “Interaction of Humans with Level 4 AVs in an Italian Environment - HL4IT”, describes suitable methods to investigate the effect of the Take-Over Request (TOR) on the human driver’s psychophysiological response. The DriSMI dynamic driving simulator at Politecnico di Milano has been used to analyse three different take-over situations. Participants are required to regain control of the vehicle, after a take-over request, and to navigate through a urban, suburban and highway scenario. The psychophysiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to
Gobbi, MassimilianoBoscaro, LindaDe Guglielmo, VeronicaFossati, AndreaGalbiati, AndreaMastinu, LedaPonti, MarcoMastinu, GianpieroPreviati, GiorgioSabbioni, EdoardoSignorini, Maria GabriellaSomma, AntonellaSubitoni, LucaUccello, Lorenzo
With the continuous development of automotive intelligence, there is an increasing demand for vehicle chassis systems to become more intelligent, electronically controlled, integrated, and lightweight. In this context, the steer-by-wire system, which is electronically controlled, offers high precision and fast response. It provides greater flexibility, stability, and comfort for the vehicle, thus meeting the above requirements and has garnered widespread attention. Unlike traditional systems, the steer-by-wire system eliminates mechanical components, meaning the road feel cannot be directly transmitted to the steering wheel. To address this, the road feel, which is derived from the vehicle's state or integrated with environmental driving data, must be simulated and transmitted to the steering wheel through a road feel motor. This motor generates feedback that mimics the road feel, similar to that experienced in a conventional steering system. This simulation enhances the driver's
Li, ShangKaku, ChuyoZheng, HongyuZhang, Yuzhou
Path tracking is a key function of intelligent vehicles, which is the basis for the development and realization of advanced autonomous driving. However, the imprecision of the control model and external disturbances such as wind and sudden road conditions will affect the path tracking effect and even lead to accidents. This paper proposes an intelligent vehicle path tracking strategy based on Tube-MPC and data-driven stable region to enhance vehicle stability and path tracking performance in the presence of external interference. Using BP-NN combined with the state-of-the-art energy valley optimization algorithm, the five eigenvalues of the stable region of the vehicle β−β̇ phase plane are obtained, which are used as constraints for the Tube-MPC controller and converted into quadratic forms for easy calculation. In the calculation of Tube invariant sets, reachable sets are used instead of robust positive invariant sets to reduce the calculation. Simulation results demonstrates that the
Zhang, HaosenLi, YihangWu, Guangqiang
To ensure the safety and stability of road traffic, autonomous vehicles must proactively avoid collisions with traffic participants when driving on public roads. Collision avoidance refers to the process by which autonomous vehicles detect and avoid static and dynamic obstacles on the road, ensuring safe navigation in complex traffic environments. To achieve effective obstacle avoidance, this paper proposes a CL-infoRRT planning algorithm. CL-infoRRT consists of two parts. The first part is the informed RRT algorithm for structured roads, which is used to plan the reference path for obstacle avoidance. The second part is a closed-loop simulation module that incorporates vehicle kinematics to smooth the planned obstacle avoidance reference path, resulting in an executable obstacle avoidance trajectory. To verify the effectiveness of the proposed method, four static obstacle test scenarios and four RRT comparison algorithms were designed. The implementation results show that all five
Wu, WeiLu, JunZeng, DequanYang, JinwenHu, YimingYu, QinWang, Xiaoliang
Advancements in sensor technologies have led to increased interest in detecting and diagnosing “driver states”—collections of internal driver factors generally associated with negative driving performance, such as alcohol intoxication, cognitive load, stress, and fatigue. This is accomplished using imperfect behavioral and physiological indicators that are associated with those states. An example is the use of elevated heart rate variability, detected by a steering wheel sensor, as an indicator of frustration. Advances in sensor technologies, coupled with improvements in machine learning, have led to an increase in this research. However, a limitation is that it often excludes naturalistic driving environments, which may have conditions that affect detection. For example, reductions in visual scanning are often associated with cognitive load [1]; however, these reductions can also be related to novice driver inexperience [2] and alcohol intoxication [3]. Through our analysis of the
Seaman, SeanZhong, PeihanAngell, LindaDomeyer, JoshuaLenneman, John
With the continuous advancement of automotive intelligence, new energy vehicles are becoming increasingly popular. These vehicles demand a steering system independent of the engine, offering better control and enhanced steering performance. The steer by wire (SBW) system, known for its high precision and fast response, fulfills these requirements by providing improved flexibility, stability, and comfort. Consequently, SBW systems have attracted significant attention in both research and application domains. As the mechanical structure of the steer-by-wire system is canceled, the road feel can not be directly transmitted to the steering wheel, and it is necessary to apply the road feel obtained according to the state of the vehicle or combined with the planning of the driving environment to the steering wheel through the road feel motor to complete the road feel simulation so that the driver can feel the feedback similar to that of the traditional steering vehicles, which can not only
Li, ShangZheng, HongyuKaku, Chuyo
This study analyzes feedback and control methods for road feel simulation in automotive steer-by-wire front steering systems based on bidirectional control. Unlike traditional road feel design methods, this research employs a force-direct feedback-position type bidirectional control structure for the SBW system. It explores the mechanism of road feel generation in Electric Power Steering systems and designs a road feel simulation algorithm based on bidirectional control. Compared to conventional methods, the force direct feedback-position type bidirectional control method enables faster and more stable simulation of road feel torque. In low-speed driving, this approach provides higher steering ease, while at high speeds, the driving stability is enhanced, and both scenarios achieve an improved road feel. In the research, a complete vehicle model is established in Simulink at first, followed by a co-simulation with CarSim. A magic formula tire model and a nonlinear two-degree-of-freedom
Wang, YuxuanZheng, HongyuKaku, ChuyoZong, Changfu
The current research landscape in path tracking control predominantly focuses on enhancing tracking accuracy, often overlooking the critical aspect of passenger comfort. To address this gap, we propose a novel path tracking control method that integrates vehicle stability indicators and road curvature variations to elevate passenger comfort. The core contributions are threefold: firstly, we conduct comprehensive vehicle dynamics modeling and analysis to identify key parameters that significantly impact ride comfort. By integrating human comfort metrics with vehicle maneuverability indices, we determine the optimal range of dynamics parameters for maximizing passenger comfort during driving. Secondly, inspired by human driving behavior, we design a path tracking controller that incorporates an anti-saturation algorithm to stabilize tracking errors and a curvature optimization algorithm to mimic human driving patterns, thereby enhancing comfort. Lastly, comparative simulations with two
Lu, JunZeng, DequanHu, YimingWang, XiaoliangLiu, DengchengJiang, Zhiqiang
A large-scale logistics transport vehicle composed of two skateboard chassis is investigated in this paper. This unmanned vehicle with dual-modular chassis (VDUC) is suitable for transporting varying size of goods. The two chassis can be used jointly or driving separately as needed, which enhancing the reconfigurability of transport vehicle. Considering the road environment uncertainty and the rollover safety problem associated with large transport vehicle, this paper proposes the path planning of VDUC using the Artificial Potential Field(APF)+Model Predictive Control(MPC) while incorporating the rollover stability index. Due to the independent operation of the two modular chassis, based on the hierarchical control approach, the path following controller of the two modular chassis are designed separately according to the vehicle’s planned path. Distributed model predictive control is applied to coordinate the front and rear modular chassis, so it can realize the path following for the
Liu, ZuyangShen, YanhuaWang, Kaidiwang, Haoshuai
As the electrification of chassis systems accelerates, the demand for fail-safety strategies is increasing. In the past, the steering system was mechanically connected, so the driver could respond directly to some extent. However, the Steer-by-Wire (SbW) system is composed of the column and rack bar as electrical signals, so the importance of response strategies for steering system failure is gradually increasing. When a steering system failure occurs, a differential braking control using the difference in braking force between the left and right wheels was studied. Recently, some studies have been conducted to model the wheel reaction force generated during a differential braking. Since actual tires and road surfaces are nonlinear and cause large model errors, model-based control methods have limited performance. Also, in previous studies assumed that the driver normally operates the steering wheel in a failure situation. However, if limited to a situation such as autonomous driving
Kim, SukwonKim, Young GwangKim, SungDoMoon, Sung Jin
Since the introduction of ABS (1978), TCS (1986) and ESC (1995) in series production, the number of modern vehicle dynamics control functions and advanced driver assistance systems (ADAS) has been continuously increasing. Meanwhile, many functions are available that influence vehicle motion (vehicle dynamics). Since these are only partially and not hierarchically coordinated, the control of vehicle motion is still suboptimal. Current megatrends (automated driving, electromobility, software-defined vehicles) and new key technologies (steer-by-wire, brake-by-wire, domain-based E/E architectures) lead to an increasing number of electrified, motion-relevant components being introduced into series production. These components enable the development of an integrated chassis control (ICC) that controls all motion-relevant components, networks them with each other and coordinates them holistically to optimally control the vehicle motion regarding an adjustable desired driving behavior. Vehicle
Wielitzka, MarkAhrenhold, TimVocht, MoritzRawitzer, JonasSchrader, Jonas
To provide an affordable and practical platform for evaluating driving safety, this project developed and assessed 2 enhancements to an Unreal-based driving simulator to improve realism. The current setup uses a 6x6 military truck from the Epic Games store, driving through a pre-designed virtual world. To improve auditory realism, sound cues such as engine RPM, braking, and collision sounds were implemented through Unreal Engine's Blueprint system. Engine sounds were dynamically created by blending 3 distinct RPM-based sound clips, which increased in volume and complexity as vehicle speed rose. For haptic feedback, the road surface beneath each tire was detected, and Unreal Engine Blueprints generated steering wheel feedback signals proportional to road roughness. These modifications were straightforward to implement. They are described in detail so that others can implement them readily. A pilot study was conducted with 3 subjects, each driving a specific route composed of a straight
Duan, LingboXu, BoyuGreen, Paul
Traditional Hands-Off Detection (HOD) is realized by analyzing the torque applied to the steering wheel by the driver (driver torque), which is less accurate. In order to solve this problem, this paper takes the Column Electric Power Steering (CEPS) system as an object, analyzes the influence of the inertia effect and damping effect of the steering wheel and steering column on the HOD, establishes two kinds of state observers to obtain the accurate driver torque, proposes the estimation method of the road condition level, and can determine the torque threshold according to the information of the road condition level and the vehicle speed, and finally compares the driver torque and the torque threshold to obtain the HOD results. Experimentally, it is proved that this method can effectively reduce the interference of road surface interference on HOD. In addition, a fault-tolerant detection mechanism is proposed and validated to calculate the HOD result based on the frequency-domain
Huang, ZhaoLinLi, MinShangguan, WenbinDuan, XiaoChengXia, ZhiJun
The advent of autonomous vehicles (AVs) marks a revolutionizing transformation in transportation, with the potential to significantly enhance safety and efficiency through advanced trajectory planning and optimization capabilities. A crucial component in realizing these benefits is the use of optimization-based control strategies for real-time path planning. Among these, model predictive path integral (MPPI) control algorithms stand out as a sampling-based stochastic control method, offering precise control in dynamic environments through random sampling. While the MPPI control has shown promising results, there has been limited investigation into the effects of different prediction horizon times on control performance of these algorithms. This paper seeks to address this gap by proposing a multi-input MPPI control method for AVs using a single-track vehicle dynamic model. Our research focuses on the influence of various prediction horizon times on trajectory optimization during lane
Yang, YanwenNegash, NatnaelYang, James
Trajectory tracking control is a critical component of the autopilot system, essential for achieving high-performance autonomous driving. This paper presents the design of a stable, reliable, accurate, fast, and robust trajectory tracking controller. Specifically, a lateral and longitudinal trajectory tracking controller based on a linear parameter time-varying model predictive control (LPV-MPC) framework is designed. Firstly, a three-degree-of-freedom vehicle dynamics model and a tracking error model are established. Secondly, a multi-objective function and constraints considering tracking accuracy and lateral stability are formulated, and the quadratic programming (QP) method is employed to solve the optimization problem. Finally, PID speed tracking control is introduced in the longitudinal control scheme for comparison with the proposed MPC longitudinal speed control. A step velocity tracking test validates the effectiveness of the MPC speed tracking controller. In the lateral
Pan, ShicongLu, JunYu, YinquanZeng, DequanYang, JinwenHu, YimingJiang, ZhiqiangLiu, Dengcheng
Steering feeling plays a critical role in the driving experience and is one of the most significant topics during a new vehicle development process. To reach a consensus for the customers’ satisfaction in both the subjective and objective characteristics in a particular market segment, there have been several studies to investigate the correlations between subjective and objective evaluations of on-center steering feeling. However, it is still not clear how to determine the steering characteristic based on the correlations. In this paper, a series of new correlations between subjective and objective evaluations are built, which focus on steering stiffness, on-center feel, torque symmetry, torque ripple etc. Firstly, a set of objective metrics which are followed by professional test drivers or tuning experts have been extracted from 12 vehicles’ on-center handling test based on ISO 13674-1 2023, these vehicles covering different motorcycle type, various brands and diverse tuning styles
Jin, AnkangLuo, KaijieYang, JianyuanZheng, Yue
A rule-based unilateral fault-tolerant control strategy is proposed to improve the vehicle's yaw stability and dynamics in case of drive system failure for multi-axle differential steering vehicles due to various unpredictable factors during driving. Meanwhile, based on the conditional integration algorithm, a multi-axis differential steering vehicle dynamics control is designed to resist integration saturation, which ensures that the vehicle tracks the reference signal accurately. In order to test the designed fault-tolerant control strategy, the first wheel drive motor in the left is set to be in a state of complete failure after the 10th second on the basis of the vehicle's forward-steering driving condition in order to construct a failure test condition; deviation angle error without fault-tolerant control is 0.22182rad and the extreme value of the yaw velocity error is 0.03687 rad/s. After fault-tolerant control, the extreme value of the center-of-mass lateral deviation angle
Zou, MingyuLu, JunZeng, DequanYu, YinquanYang, JinwenHu, YimingYu, QinWang, Xiaoliang
The speed-dependent steering assistance is a fundamental function in electric power steering (EPS) systems. However, excessive levels of steering assistance can result in system instability, causing steering oscillations that compromise steering safety. Consequently, ensuring steering stability has become a primary focus in EPS development. Currently, the design of stability compensators for speed-dependent steering assistance has primarily focused on achieving system stability, often neglecting the attenuation of the designed assist gain by the compensator. In this paper, a novel method for the design of stability compensators within speed-dependent steering assistance is presented, aimed at ensuring system stability while reducing the attenuation of the designed assist gain by the compensator. First, a dynamic model of the EPS system is established, incorporating system inertia and viscous damping. The frequency response characteristics of the EPS system are obtained through vehicle
Kong, YiWei, ZhengjunDuan, XiaochengShangguan, Wen-Bin
Because the steer-by-wire (SBW) system cancels the mechanical connection between the steering wheel and the steering wheel in the traditional mechanical steering system (MSS), various road information on the road cannot be directly transmitted to the driver through the steering wheel in the form of road sense. Consequently, drivers are unable to genuinely perceive this road information, which adversely affects their control of the vehicle. This paper investigates the road perception simulation method for SBW systems. Initially, a dynamic model of the SBW system is developed, and its validity is confirmed under conditions of step changes in steering wheel angle and dual-shifting scenarios. A state estimation approach is employed to simulate road perception torque, and a corresponding torque calculation formula is derived based on the dynamic model of traditional steering systems. A two-degree-of-freedom vehicle model is constructed to independently compute the lateral force experienced
Li, XuesongLi, ZhichengZheng, HongyuKaku, Chuyo
Along with the innovation of vehicle technology, the active steering system has an excellent effect on the prevention of uncontrolled steering events due to its significant advantage in optimising handling stability. Meanwhile, the safety boundary is an important judgement basis for the stable operation of the vehicle, and based on the safety boundary, the controller can help the driver to keep the vehicle in the stable region of the state space. In this paper, an active rear wheel steering model prediction controller is proposed based on the safety boundary to control the rear wheel steering angle to assist the front wheel steering, and constrain the actual cross-swing angular angular velocity and centre-of-mass lateral deflection angle of the vehicle within the safety boundary of the state space, so as to ensure the stable operation of the vehicle, and the main research contents are as follows: 1. Aiming at the problem that the linear two-degree-of-freedom model of the vehicle can't
Li, ZiyuZheng, HongyuKaku, ChuyoZhang, Yuzhou
Optimal control of battery electric vehicle thermal management systems is essential for maximizi ng the driving range in extreme weather conditions. Vehicles equipped with advanced heating, ventilation and air-conditioning (HVAC) systems based on heat pumps with secondary coolant loops are more challenging to control due to actuator redundancy and increased thermal inertia. This paper presents the dynamic programming (DP)-based offline control trajectory optimization of heat pump-based HVAC aimed at maximizing thermal comfort and energy efficiency. Besides deriving benchmark results, the goal of trajectory optimization is to gain insights for practical hierarchical control strategy modifications to further improve real-time controllers’ performance. DP optimizes cabin inlet air temperature and flow rate to set the trade-off between thermal comfort and energy efficiency while considering the nonlinear dynamics and operating limits of HVAC system in addition to typically considered cabin
Cvok, IvanDeur, Josko
To further optimize the automatic emergency braking for pedestrian (AEB-P) control algorithm, this study proposes an AEB-P hierarchical control strategy considering road adhesion coefficient. First, the extended Kalman filter is used to estimate the road adhesion coefficient, and the recursive least square method is used to predict the pedestrian trajectory. Then, a safety distance model considering the influence factor of road adhesion coefficient is proposed to adapt to different road conditions. Finally, the desired deceleration is converted into the desired pressure and desired current to the requirements of the electric power-assisted braking system. The strategy is verified through the hardware-in-the-loop (HIL) platform; the simulation results show that the control algorithm proposed in this article can effectively avoid collision in typical scenarios, the safe distance of parking is between 0.61 m and 2.34 m, and the stop speed is in the range of 1.85 km/h–27.64 km/h.
Wang, ZijunWang, LiangMa, LiangSun, YongLi, ChenghaoYang, Xinglong
Path planning algorithms are critical technologies for intelligent ship systems, as scientifically optimized paths enable safe navigation and efficient avoidance of waterborne obstacles. To address the limitations of current ship path planning models, which often fail to adequately consider the combined effects of wind, current, and the International Regulations for Preventing Collisions at Sea (COLREGS), this study proposes an enhanced path planning method. The method integrates environmental factors, such as wind and current, and COLREGS into an improved Artificial Potential Field(APF) framework. Specifically, the influence of wind and current is modeled as "environmental forces," while the navigation constraints imposed by COLREGS are transformed into virtual obstacles, generating corresponding repulsive forces to refine the algorithm. Simulation experiments conducted under both single-ship and multi-ship scenarios validate the feasibility and effectiveness of the proposed approach
Shangqing, FengJinli, XiaoLangxiong, GanGeng, ChenHui, LiGuanliang, Zhou
Aiming at the problem of insufficient capacity of taxiways in hub airports, which combine the safety interval, conflict resolution and fair principles, a taxiway planning model is established by taking the shortest taxiway as the optimisation goal, considering fuel consumption and exhaust emissions. Dijkstra algorithm is used to transform the taxiing path into an adjacency matrix, and conflict resolution is carried out in a weighted way. Under the premise of ensuring zero conflict of taxiways, the total taxiing distance is reduced. Based on actual operational data from a hub airport in China, the results show that the proposed taxiing path planning method is feasible, shortening the aircraft taxiing distance and improving the surface taxiing efficiency.
Feng, BochengQi, XinyueZhang, Hongbin
In commercial vehicle, Hydraulic Power Assisted Steering (HPAS) gear plays a vital role to utilize the hydraulic force to assist the steering application. HPAS gear consists of housing, sector shaft, side cover, worm shaft, valve housing and rack piston. Side cover assembly is connected with the housing assembly through bolts which is in exposure to high pressure working hydraulic fluid. Since, some of the bolts are exposed to the fluid environment in the inner surface of the housing, during high pressure running condition, torque relaxation in the bolt is observed which leads to the loosening of bolts and tends to hydraulic fluid leakage through bolts. The current phosphate coated bolts are getting relaxed and loosened due to the bolts that exposed to the oil environment which have insufficient coefficient of friction in the bolt head and thread. To overcome the bolt failure during high pressure hydraulic application, various bolt coating analysis is experimented to withstand the
Ayyappan, RakshnaGovindarasu, AnbarasuP, RajasekarD, Senthil Kumar
There are various steering technologies are available in market nowadays. Hydraulic Power Steering (HPS) is one of them. As hydraulic name is linked to it the temperature role comes to play. While doing hard cornering the hydraulic oil used to assist the working in steering system get over heated, due to which oil loses its viscosity became one of the major causes of hard steer in trucks. Also, due to limited space the large heat exchanger cannot be used there. So, objective of this Thesis is to examine an effective solution which can be compact in design and at the same time should be effective to solve this problem. After going through literature analysis, we finalize that the Principal of Pulsating Heat Pipe could be a possible solution. So, for that we design different model based on previous research work in Creo and simulate them in Star CCM+ to finalize the optimality.
Saikrishna, VNLP, RudreshaYadav, SatyendraB, RuthvikaVishwasa, Viditha
Intelligent vehicles can utilize a variety of sensors, computing, and control technologies to autonomously perceive the environment and make decisions to achieve safe, efficient, and automated driving. If the speed planning of intelligent vehicles ignores the vehicle dynamics state, it leads to unreasonable planning speed and is not conducive to improving the accuracy of trajectory tracking control. Meanwhile, trajectory tracking usually does not consider the road and speed information beyond the prediction horizon, resulting in poor tracking precision that is not conducive to improving driving comfort. To solve these problems, this study proposes a new longitudinal speed planning method based on variable universe fuzzy rules and designs the piecewise preview model predictive control (PPMPC) to realize the vehicle trajectory tracking. First, the three-degrees-of-freedom vehicle dynamics model and trajectory tracking model are established and verified. Then, the variable universe fuzzy
Zhang, JieTeng, ShipengGao, JianjieZhou, XingxingZhou, Junchao
In this work, the large-angle rotational movement and vibration suppression of a flexible spacecraft are carried out based on an adjustable system. First the spacecraft model is transformed into a canonical affine control form, then two fuzzy systems are used: The first (of Takagi–Sugeno type) estimates the feedback linearization control law as a whole, while the second (of Mamdani type) adjusts and stabilizes the control parameters using the gradient descent technique and based on the minimization of the control error rather than the tracking error. Stability results are presented in terms of Lyapunov’s theory, and simulation tests illustrate the significant transient robustness of the closed-loop system against perturbations, the accurate trajectory control, and vibration suppression of the flexible spacecraft. Consequently, as will be shown later, the error will stay confined and converges quickly to zero, confirming the smoothing property of the proposed method using fuzzy logic
Bahita, Mohamed
The increased popularity of electric vehicles featuring distributed powertrains is enabling an easy and cost-effective implementation of torque vectoring. This is a renowned technique for controlling vehicle lateral dynamics having the objective of improving both vehicle handling and stability. Nevertheless, the application of torque vectoring at the front axle can increase the difficulty of usual driving tasks. This is because differential longitudinal forces at front tires generate a steering wheel torque, which can be badly perceived by the driver, up to the point of jeopardizing the benefits of having a torque vectoring control. The aim of this article is thus to study in detail the steering torque corruption caused by front axle torque vectoring for proposing some electric power steering control strategies compensating for this effect. Indeed, the electric power steering controllers developed in this study are designed based on the analytical derivation of the torque steer theory
Asperti, MicheleVignati, MicheleSabbioni, Edoardo
To address the issues of unreasonable collision avoidance path planning algorithms and inadequate safety in high-speed scenarios, a trajectory prediction-based collision avoidance path planning algorithm has been proposed. First, a trajectory prediction model is constructed using the long–short-term memory (LSTM) network, and the trajectory prediction model is trained and tested with the HighD dataset. Second, the future trajectory of the obstacle car is predicted, the future trajectory information of the two cars is combined to generate the lane-changing decision, and the three-times B-spline curves are used to generate the collision avoidance path clusters. The optimal collision avoidance paths are generated based on the multi-objective optimization function. Finally, build a MATLAB/CarSim simulation platform to verify the reasonableness and safety of the planned paths by taking the three scenarios of the continuous overtaking, preceding car pulling out, and the neighboring car
Liu, Xiao LongZhang, LeiLi, Peng KunXie, RuWang, QingLi, Ran Ran
Accurate and responsive trajectory tracking is a critical challenge in intelligent vehicle control system. To improve the adaptability and real-time performance of intelligent vehicle trajectory tracking controllers, we propose a genetic algorithm adaptive preview (GAAP) scheme that offline optimizes the preview distance based on vehicle speed and reference path curvature. The goal is to obtain the optimal preview distance that balances tracking accuracy, stability, and real-time performance. By establishing a relationship between optimal preview distance, speed, and curvature, we enhance real-time performance through online table checking during trajectory tracking. Our trajectory tracking error model takes into account not only position errors but also heading errors. A feedback–feedforward trajectory tracking controller is then designed to achieve rapid responses without compromising robustness. Simulation tests conducted under straight circular arc condition and double lane change
Cheng, KehanZhang, HuanhuanHu, ShengliNing, Qianjia
This research, path planning optimization of the deep Q-network (DQN) algorithm is enhanced through integration with the enhanced deep Q-network (EDQN) for mobile robot (MR) navigation in specific scenarios. This approach involves multiple objectives, such as minimizing path distance, energy consumption, and obstacle avoidance. The proposed algorithm has been adapted to operate MRs in both 10 × 10 and 15 × 15 grid-mapped environments, accommodating both static and dynamic settings. The main objective of the algorithm is to determine the most efficient, optimized path to the target destination. A learning-based MR was utilized to experimentally validate the EDQN methodology, confirming its effectiveness. For robot trajectory tasks, this research demonstrates that the EDQN approach enables collision avoidance, optimizes path efficiency, and achieves practical applicability. Training episodes were implemented over 3000 iterations. In comparison to traditional algorithms such as A*, GA
Arumugam, VengatesanAlagumalai, VasudevanRajendran, Sundarakannan
The exponential growth of the agribusiness market in Brazil combined with the high receptivity among farmers of new technological solutions has driven the study and implementation of high technology in the field. This work aimed to apply servo-assisted driving technology to enable autonomous mobility in an off-road sugarcane truck responsible for harvesting sugarcane. The technology consists of a conventional hydraulic steering with a motor, ECU and torque and angle sensors responsible for reading input data converted from GPS signals and previously recorded tracking lines. The motor responsible for replacing 100% of the physical force generated by the driver acts in accordance with the required torque demand, and the sensors combined with the ECU correct the course to meet the follow-up line through external communication ports. The accuracy of the system depends exclusively on the accuracy of the GPS signal, in this case reaching 2,5 cm, which is considered extremely high accuracy
Oliveira Santos Neto, AntídioLara, VanderleiSilva, EvertonDestro, DanielMoura, MárcioBorges, FelipeHaegele, Timo
The SAE Formula, a national stage of the international competition, consists of a student project at universities in Brazil that seeks to encourage engineering students to apply the theoretical knowledge obtained in the classroom to practice, dealing with real problems and difficulties in order to prepare them for the job market. The SAE Formula prototype is developed with the intention of competing in the SAE national competition, where teams from various universities in Brazil meet to compete and demonstrate the projects developed during the year. Focusing on the vehicle dynamics subsystem, which can be divided into the braking, suspension, and steering systems of a prototype, the steering system includes main mechanical components such as the front axle sleeves, wheel hub, steering arm, steering column, rack, wheel, and tire. All these components work together with the suspension systems, including suspension arms, “bell crank,” and spring/shock absorber assembly. These components
Rigo, Cristiano Shuji ShimadaNeto, Antonio Dos Reis De FariaGrandinetti, Francisco JoseCastro, Thais SantosDias, Erica XimenesMartins, Marcelo Sampaio
Autonomous driving technology has indeed become a focal point of research globally, with significant efforts directed towards enhancing its key components: environment perception, vehicle localization, path planning, and motion control. These components work together to enable autonomous vehicles to navigate complex environments safely and efficiently. Among these components, environment perception stands out as critical, as it involves the robust, real-time detection of targets on the road. This process relies heavily on the integration of various sensors, making data fusion an indispensable tool in the early stages of automation. Sensor fusion between the camera and RADAR (Radio Detection and Ranging) has advantages because they are complementary sensors, where fusion combines the high lateral resolution from the vision system with the robustness in the face of adverse weather conditions and light invulnerability of RADAR, as well as having a lower production cost compared to the
Cury, Hachid HabibTeixeira, Evandro Leonardo SilvaSilva, Rafael Rodrigues
Single lane changing is one of the typical scenarios in vehicle driving. Planning an appropriate lane change trajectory is crucial in autonomous and semi-autonomous vehicle research. Existing polynomial trajectory planning mostly uses cubic or quintic polynomials, neglecting the lateral jerk constraints during lane changes. This study uses seventh-degree polynomials for lane change trajectory planning by considering the vehicle lateral jerk constraints. Simulation results show that the utilization of the seventh-degree method results in a 41% reduction in jerk compared to the fifth-degree polynomial. Furthermore, this study also proposes lane change trajectory schemes that can cater to different driving styles (e.g., safety, efficiency, comfort, and balanced performance). Depending on the driving style, the planned lane change trajectory ensures that the vehicle achieves optimal performance in one or more aspects during the lane change process. For example, with the trajectory that
Lai, FeiHuang, Chaoqun
SBW(Steer-by-wire) is a steering system that transmits the driver’s request and gives feedback to the driver through electrical signals. This system eliminates the mechanical connection of the traditional steering system, and can realize the decoupling of the steering wheel and the road wheel. In addition, this system has a perfect torque feedback system, which can accurately and delicately feedback the road surface information to the driver. However, vehicle driving deviation is one of the most common failure modes affecting vehicle performance in the automotive aftermarket, this failure mode can exacerbates tire wear, reducing their life cycle, at the same time, the driver must apply a counter torque to the steering wheel for a long time to maintain straight-line travel during driving. This increases the driver’s operational burden and poses safety hazards to the vehicle’s operation. Based on the steer-by-wire system and vehicle driving deviation characteristics, this paper proposes
Xiangfei, XuQu, Yuan
Path planning in parking scenarios for vehicles with Ackermann steering characteristics is a well studied problem in the literature. However, the recent emergence of four-wheel steering (4WS) chassis has brought new opportunities to the field of motion planning. Compared with front-wheel steering (2WS), 4WS vehicles offer higher flexibility and new maneuver modes such as CrabWalk. To utilize such new potential to further improve parking efficiency, this paper proposes a four-wheel steering oriented planning algorithm for parking scenarios. First, Hybrid A*-4WS is proposed to search for a coarse trajectory from the starting pose to the parking slot, with improved node expansion mechanism to incorporate four-wheel steering characteristics. Then a nonlinear programming (NLP) problem is formulated with four-wheel steering kinematic model to fully utilize the maneuver capability of 4WS vehicles, with OBCA used for collision avoidance constraints. Finally, the two algorithms are sequentially
Song, YufeiLiu, YuanzhiXiong, LuTang, Chen
This paper proposes a path-tracking and direct yaw moment integrated control strategy based on linear matrix inequality (LMI) and terminal sliding mode for autonomous distributed drive electric vehicles (A-DDEVs) equipped with a steer-by-wire (SBW) system. This strategy effectively attenuates the effects of external disturbances and parameter uncertainties on path tracking, thereby enhancing vehicle safety. The control-oriented vehicle model accounts for roll effects, with the system state matrix incorporating mismatched norm bounded uncertainties. Firstly, for overall vehicle motion control, an LMI-based integral sliding mode controller (ISMC) is designed to generate desired front wheel steering angle and additional yaw moment. This aims to converge path-tracking errors and ensure vehicle stability. A sufficient condition for the existence of a sliding surface ensuring asymptotic stability of the sliding mode dynamics is provided, along with a demonstration of the attainability of the
Li, DanyangZhao, YouqunLin, FenZhang, ChenxiYu, Song
The application trend of automated driving is gaining significant concern, making it increasingly crucial to validate automated driving within the stochastic simulated traffic flow environment from both time and cost perspectives. The stochastic traffic flow model attempts to encapsulate the variability inherent in traffic conditions through a stochastic process. This approach is particularly important as it accounts for the unpredictable nature of traffic, which is often not fully captured by traditional deterministic testing scenarios. However, while stochastic traffic flow models have made strides in simulating the behavior of traffic participants, there remains a significant oversight in the simulation of vehicles’ driving trajectories, leading to unrealistic portrayals of their behaviors. The trajectories of vehicles are a critical component in the overall behavior of traffic flow, and their accurate representation is essential for the simulation to reflect real-world driving
Gao, YiboCao, PengYang, Aixi
Learning-based motion planning methods such as reinforcement learning (RL) have shown great potential of improving the performance of autonomous driving. However, comprehensively ensuring safety and efficiency remain a challenge for motion planning technology. Most current RL methods output discrete behavioral action or continuous control action, which lack an intuitive representation of the future motion and then face the problems with unstable or reckless driving behavior. To address these issues, this work proposes an interaction-aware reinforcement learning approach based on hybrid parameterized action space for autonomous driving in lane change scenario. The proposed method can output high-level feasible trajectory and low-level actuator control command to control the vehicle’s motion together. Meanwhile, the reward functions for the local traffic environment are designed to evaluate the effect of the interaction between ego vehicle and surrounding vehicles. The contributions of
Li, ZhuorenJin, GuizheYu, RanLeng, BoXiong, Lu
There is evidence to suggest that males and females respond differently in motor vehicle collisions, making it important to study how both sexes respond to vehicle safety systems. The THOR 5th-percentile female (THOR-05F) anthropomorphic test device (ATD) was developed to represent a small female occupant better than the Hybrid III 5th-percentile female (HIII-05F) ATD. However, there are few studies in which they have been directly compared. Therefore, the objective of this study was to compare the responses of the two ATDs in matched frontal sled tests simulating a realistic driver seat environment. A 7th-generation Toyota Camry driver seat test buck was used with Camry parts (i.e., 3-point belt, modified seat, steering wheel, airbag, and column). The belt was equipped with a 4-kN load limiter and pretensioner. Rigid foam (65 psi) was used to represent the knee bolster. Thirteen tests were conducted using speeds of 30 and 56 kph. Chest bands were used to measure external chest
Boyle, David M.Albert, Devon L.Hardy, Warren N.Kemper, Andrew R.
The structural integrity of the steering wheel is important for vehicle operations. It is subjected to various load conditions during the vehicle motion. It thus becomes important to understand various aspects of the same which include stiffness, natural frequency, and regulatory requirements i.e. body block test, head form impact test, etc. Simulation plays an important role in understanding the structural integrity and validation requirements of products at the design stage itself. This paper discusses the modeling and simulation of the steering wheel at both the armature level and the complete steering wheel level. As armature is critical from a structural strength and stiffness point of view, certain simulations like modal analysis are performed first at the armature level, and design iterations were done to achieve the natural frequency target. The list of simulations performed includes modal analysis, bending rigidity, static compression, bending stiffness, body block test and
Rathore, Gopal SinghKumar, AnkitChauhan, Adesh KumarDas, A.P.Sahu, Hemanta Kumar
Turning circle diameter (TCD) of vehicle is critical parameter which is used to determine the turning capability of vehicle. TCD is the smallest circular turn that a vehicle can make of given drive track. The TCD depends on vehicle wheel lock angles, wheelbase, and geometric architecture of vehicle. The Regulation certification requirement of steering system, states that the maximum TCD should be less than 24m & TCCD (Turning clearance circle diameter) 25m (M&N category Vehicle). IS 12222:2011 & UN R79 are regulation related to Steering system. This invention relates to measuring the TCD of vehicle. The conclusion of this technical paper proposes new innovative method to overcomes and address the below limitations. It provides accurate and precise results by adjusting room for error. It eliminates the approximation ambiguity. It reduces the manual intervention of human effort to carry out the entire measurement process. It improves the safety of measurement technician, since it
Yadav, SatyendraOjha, VijayChatterjee, AnupamSaikrishna, VNLKarthik, V
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