Steering Model Research Articles

A Basic Study for Active Steering Wheel System for Steering Burden Evaluation by Driving Position Focus on Driver’s Arm Size

As automated driving has not yet been established, on narrow roads where there is no separation between pedestrians and vehicles, it is essential to switch to manual driving. However, when the driver turns the steering wheel from one hand to another on narrow roads, it causes steering burdens and operational errors if the steering feel or burden is not proper. Thus, this study aims to construct an active steering wheel system that provides an appropriate steering feel or burden by controlling the steering reaction torque, driving position and steering gear ratio for each driver. In this paper, we focused on and examined the driving position among these. A two-dimensional steering model that considers the size of the arms for each driver was established to evaluate steering burden. In addition, a basic study was conducted on the appropriate driving position. Then, based on the joint movements and angles calculation, the appropriate driving position that considers the size of the arms was studied by evaluating the joint power. As a result, it was found that if the steering wheel position is too close to the driver, the amount of joint movement increases, and if it is too far away, the joint movement decreases. Therefore, it was found that the appropriate steering wheel position for each driver’s arm length can be considered by using the joint power.

Integrin-mediated electric axon guidance underlying optic nerve formation in the embryonic chick retina

Retinal ganglion cell (RGC) axons converge on the optic disc to form an optic nerve. However, the mechanism of RGC axon convergence remains elusive. In the embryonic retina, an electric field (EF) exists and this EF converges on the future optic disc. EFs have been demonstrated in vitro to orient axons toward the cathode. Here, I show that the EF directs RGC axons through integrin in an extracellular Ca2+-dependent manner. The cathodal growth of embryonic chick RGC axons, which express integrin α6β1, was enhanced by monoclonal anti-chicken integrin β1 antibodies. Mn2+ abolished these EF effects, as Mn2+ occupies the Ca2+-dependent negative regulatory site in the β1 subunit to eliminate Ca2+ inhibition. The present study proposes an integrin-mediated electric axon steering model, which involves directional Ca2+ movements and asymmetric microtubule stabilization. Since neuroepithelial cells generate EFs during neurogenesis, electric axon guidance may primarily be used in central nervous system development.

Soft Computing Based Sliding Surface Adjustment of Second Order Sliding Mode Controllers: An Application to Ship Steering Model

Soft Computing Based Sliding Surface Adjustment of Second Order Sliding Mode Controllers: An Application to Ship Steering Model

Ground vehicle lane-keeping assistance system via differential flatness output feedback control and algebraic derivative estimation

Vehicle run-off-road is one of the most frequent and fatal traffic accidents in the United States. Various lane-keeping assistance (LKA) systems have been developed in the last decade to help drivers stay on the road. Most of them are built upon linear driver–vehicle–road (DVR) models and treat road curvature as a disturbance. Albeit effective, their control performance would degrade if road curvature varies rapidly. This paper proposes a novel nonlinear DVR model by integrating a driver steering model into vehicle–road kinematics, which explicitly considers road curvature. Particularly, this nonlinear DVR system has been proven to be differentially flat, and a flatness-based LKA system is designed. Additionally, Model-Free Control is introduced to compensate for system modeling errors. Hardware-in-the-loop simulations and diver-in-the-loop experiments validate the proposed control framework and demonstrate the performance enhancement with respect to a representative linear robust LKA system.

Performance Research of Dual Power Flow Continuous Differential Steering System for Tracked Vehicle

The tracked vehicle has good passability and adaptability for different complex environments, and also can maintain a stable posture with the ability to regulate flexible posture. Therefore, it is necessary to design a steering system with continuous and accurate steering radius and high transmission efficiency. The dynamic model of differential steering system was established including input rotate speed and output rotate speed. The dynamic model between input rotate speed and steering radius was obtained according to the relationship of output rotate speed and steering radius. The dynamic model of steady steering including the length, gauge, ground instantaneous center offset and so on of tracked vehicle was built, which could be used to predict the steady state steering characteristic of tracked vehicle.

Analyzation of the Application Scenarios of Ackerman Geometry based on Vehicle Steering Model

A complete set of models about vehicle steering are established to testify the feasibility of Ackerman geometry applied in various scenarios. The relationship between different parameters from cars and how they affect the steering ability is studied by Python. Linear model and nonlinear model are built to adapt to small and big slip angle. The mechanism section is tested with data from two types of cars: BMW M3 and Chevrolet Cavalier. We find that M3 has a better steering capability since it can generate more lateral force with less sideslip. The relationship between slip angle and lateral force illuminates our research about Ackerman geometry. The result indicates that regular Ackerman principle is beneficial in the big wheel steering angle with low-speed conditions, because it can reduce the slip angle and tire-road interaction, making cornering smoother and reducing tire wear. However, in small wheel steering angle with high-speed conditions, the Ackerman principle has some limitations and should be amended, which adds to the slip angle and thus increase the lateral force to get better steering. That is basically the reason why Reverse Ackerman is widely applied in Formula 1.

Analysis of the Car Model and Ackermann’s Steering Geometry

In order to solve the problem of the inside and outside wheels that trace out circles of different radii in a turn, Ackermann's steering geometry was developed. It is a geometric design of the connecting linkage arrangement in the steering of a vehicle to address the steering problems. However, because other factors also influence the design of steering structures, the majority of cars do not have a steering structure that is 100% Ackermann geometry or 100% Anti-Ackermann geometry. The dominant explanation for it has primarily relied on complicated calculations considering the whole structure of a car. In this study, only the most important variable—the slip angle during steering—is taken into account in all computations, which are based on a vehicle force model. Python is used to stimulate the graph and traveling path of the vehicle on lane change and U-turn steering. The research presented in this paper illustrates the significance and distinction between employing Ackerman and Anti-Ackerman geometry and provides guidance on how to select the appropriate steering model for a certain vehicle.

Modeling driver steering behavior in restricted-preview boundary-avoidance tasks

In the design of human-like steering support systems, driver models are essential for matching the supporting automation's behavior to that of the human driver. However, current driver models are very limited in capturing the driver's adaptation to key task variables such as road width and visibility (i.e., ‘preview’ of the road ahead). This paper uses a recently proposed, novel control-theoretical model for centerline tracking to investigate driver steering in lane-keeping tasks with restricted and unrestricted preview, in an attempt to substantially extend this model's validity. Using data from a tailored driving simulator experiment, three driver control loops (feedforward, heading and position feedback) are separately quantified using system identification techniques. The results show that when preview is restricted, drivers use all of the remaining preview to anticipate the curves of the road ahead, and are no longer able to ‘smooth’ tight curves in the road trajectory (i.e., corner cutting). When sufficient preview and lane width are available, the time to line crossing increases, and steering behavior is less aggressive and more intermittent, or more ‘satisficing’. The novel driver steering model captures these adaptations very well (over 95% of the steering actions) and can thereby be instrumental in realizing human-like steering automation and support systems.

Trajectory Tracking of Autonomous Vehicle Using Clothoid Curve

This paper proposes a clothoid-curve-based trajectory tracking control method for autonomous vehicles to solve the problem of tracking errors caused by the discontinuous curvature of the control curve calculated by the pure pursuit tracking algorithm. Firstly, based on the Ackerman steering model, the motion model is constructed for vehicle trajectory tracking, Then, the position of the vehicle after the communication delay of the control system is predicted as the starting point of the clothoid control curve, and the optimization interval of the curve end point is determined. The clothoid control curves are calculated, and their parameters are verified by the vehicle motion and safety constraints, so as to obtain the optimal clothoid control curve satisfying the constraints. Finally, considering the servo system response delay time of the steering system, the steering angle target control value is obtained by previewing the curvature of the clothoid control curve. The field experiment is conducted on the test road, which consists of straight, right-angle turns and lane-change elements under three sets of speed limitations, and the test results show that the proposed clothoid-curve-based trajectory tracking control method greatly improved the tracking accuracy compared with the pure pursuit method; in particular, the yaw deviation is improved by more than 50%.

LQR Trajectory Tracking Control of Unmanned Wheeled Tractor Based on Improved Quantum Genetic Algorithm

In the process of trajectory tracking using the linear quadratic regulator (LQR) for driverless wheeled tractors, a weighting matrix optimization method based on an improved quantum genetic algorithm (IQGA) is proposed to solve the problem of weight selection. Firstly, the kinematic model of the wheeled tractor is established according to the Ackermann steering model, and the established model is linearized and discretized. Then, the quantum gate rotation angle adaptive strategy is optimized to adjust the rotation angle required for individual evolution to ensure a timely jumping out of the local optimum. Secondly, the populations were perturbed by the chaotic perturbation strategy and Hadamard gate variation according to their dispersion degree in order to increase their diversity and search accuracy, respectively. Thirdly, the state weighting matrix Q and the control weighting matrix R in LQR were optimized using IQGA to obtain control increments for the trajectory tracking control of the driverless wheeled tractor with circular and double-shifted orbits. Finally, the tracking simulation of circular and double-shifted orbits based on the combination of Carsim and Matlab was carried out to compare the performance of LQR optimized by five algorithms, including traditional LQR, genetic algorithm (GA), particle swarm algorithm (PSO), quantum genetic algorithm (QGA), and IQGA. The simulation results show that the proposed IQGA speeds up the algorithm’s convergence, increases the population’s diversity, improves the global search ability, preserves the excellent information of the population, and has substantial advantages over other algorithms in terms of performance. When the tractor tracked the circular trajectory at 5 m/s, the root mean square error (RMSE) of four parameters, including speed, lateral displacement, longitudinal displacement, and heading angle, was reduced by about 30%, 1%, 55%, and 3%, respectively. When the tractor tracked the double-shifted trajectory at 5 m/s, the RMSE of the four parameters, such as speed, lateral displacement error, longitudinal displacement error, and heading angle, was reduced by about 32%, 25%, 37%, and 1%, respectively.

Development of automatic gain-tuning algorithm for heading control using free-running test data

This study proposes an automatic gain-tuning algorithm for ships. The proposed algorithm is designed to tune the gains of the ship controller automatically, rather than using trial and error. The forward speed and steering models were derived by linearizing and simplifying the 3-degrees of freedom (DOF) nonlinear equation of motion of the ship. The initial control gains were calculated using an error dynamics model constructed by combining the steering and system models of the controller. The maneuvering simulations and sensitivity analysis of the control performance at various control gains were performed for gain-tuning. System identification was conducted based on derived dynamics models and free-running test data. The tests verified that the gain-tuning algorithm corrects the gains more accurately and rapidly than trial and error. In addition, the algorithm reduced overshoot by 85% compared to the initial control gains.

The Concrete Expression of the Move to Emptiness Technique Steering Model

The Concrete Expression of the Move to Emptiness Technique Steering Model

Study on emergency evacuation in underground urban complexes.

With progressive urbanization and the development and utilization of urban underground space, underground urban complexes (UUCs) have been increasingly used. UUCs have brought much convenience to people's lives. However, due to their enclosed nature and complexity, it has been an urgent issue to avoid (or reduce) casualties and allow rapid and safe evacuation of people during an emergency. In this study, the evacuation simulation software Pathfinder was used. Based on the steering model, the variation of the total evacuation time and pedestrian flow at main exits with different simulated evacuation measures, congestion at key nodes and people's path selection were compared and analyzed. Then, the critical locations in the spatial layout of UUCs that were prone to evacuation bottleneck effects were focused on and determined. The evacuation effectiveness of UUCs in an emergency was studied to investigate the problems of emergency evacuation in UUCs. It is found that in UUCs, the bottleneck effects were likely to occur at stairway entrances and exits as well as supermarket checkout counters and caused severe congestion. These locations should be focused on during emergency evacuation. For key locations prone to evacuation bottlenecks, increasing the width of exits or setting up auxiliary evacuation channels could be an effective measure to improve evacuation efficiency. In addition, formulating rational evacuation rules can be a favorable measure for emergency evacuation. However, during the evacuation, the herd mentality in people has an uncertain (positive or negative) impact on evacuation effectiveness. Setting up diversion walls may improve evacuation efficiency and reduce congestion to a certain extent, while evacuation confusion and chaos are prone to occur after diversion. These findings in this study have significant implications for improving the emergency management of UUCs.

Development of a tractor operator-operation environment coupled biomechanical model and analysis of lower limb muscle fatigue

For the quantitative analysis and evaluation of tractor pedal operation comfort, this study developed a tractor operator-operation environment coupled biomechanical model in AnyBody Modeling System. First, operator model and operation environment model were generated according to Chinese adult male anthropometric dimensions and Dongfanghong LX804 tractor design parameters. To couple these two models, the connections between operator model's palms, feet, pelvis and operation environment model's steering wheel, joystick, pedals, seat were created. The release scheme of limb joint angle constraints was designed, which allowed limbs to fulfill the kinematic requirement of operating devices. Then, to drive the model, a driver device with a rotation angle range of 0°-42°and a spring with a stiffness of 37.85Nm/rad were added to pedal hinge based on the driving data of pedal force and pedal travel collected by sensors. Subsequently, to validate the model, the surface electromyography signals of lower limb muscles were acquired using the test system of Cometa MiniWave. The average relative error between the lower limb muscle activity calculated from electromyography signals and that computed from the model was 9.2%. Finally, the model was employed to simulate the dynamic process of pedal operation and analyze lower limb fatigue. The results demonstrated that the fatigue exhibited a tendency of first decreasing and then increasing as pedal rotation angle increased, and reached a lower level within the pedal rotation angle range of 8°-17°.

Design and analysis of electric power-assisted steering in vehicles for mountain forests

This study investigates the problem of vehicle exploitation in the mountainous and wooded regions of the Russian Federation. Considering how critical rollover accidents are in the logging industry, it is vital to ensure safe and stable driving. This study aims to develop a model of electric power steering (EPS) control using a quasi-continuous sliding-mode controller in MATLAB/Simulink. Experiments were carried out under the following conditions: maximum slope angle, 30°; maximum steering angle, 30°; maximum driving speed, 7 m/s. The dynamic characteristics of the suspension and EPS systems were optimized using the receding horizon optimization technique. The theoretical and experimental results suggest that the model reaches its critical state of stability (−0.2) at a speed range of 0–7 m/s with a steering angle of 25°. After optimization, critical stability (0.3) occurs at the driving speed of 7 m/s when the steering angle is 30°. The paper discussed the possibility of installing the EPS control system into vehicles that operate in mountainous wooded areas.

The Price for Inclusion: Financial/Educational Dilemmas in the Inclusive School System in Denmark

This qualitative case study investigates the rationales, dilemmas, and shortcomings of the so-called “inclusion-promoting steering models” in which Danish schools have to pay a price for every student they cannot include in their school. For more than 10 years, the government has promoted such financial steering models and a rising number of municipalities have adopted the system, so that more than one-half of the existing Danish municipalities work with them. According to its advocates, this model supports the inclusion of students in schools in several direct ways. This case study shows that this model is based on some strong rationales, as it offers opportunities to promote the development of inclusive schools. However, the study also reveals that this comes at a price, as the model sometimes poses difficult dilemmas on school leaders and hinders the inclusion of all students.

Modeling Human Steering Behavior in Haptic Shared Control of Autonomy-Enabled Unmanned Ground Vehicles.

A human steering model for teleoperated driving is extended to capture the human steering behavior in haptic shared control of autonomy-enabled Unmanned Ground Vehicles (UGVs). Prior studies presented human steering models for teleoperation of a passenger-sized Unmanned Ground Vehicle, where a human is fully in charge of driving. However, these models are not applicable when a human needs to interact with autonomy in haptic shared control of autonomy-enabled UGVs. How a human operator reacts to the presence of autonomy needs to be studied and mathematically encapsulated in a module to capture the collaboration between human and autonomy. Human subject tests are conducted to collect data in haptic shared control for model development and validation. The ACT-R architecture and two-point steering model used in the previous literature are adopted to predict the operator's desired steering angle. A torque conversion module is developed to convert the steering command from the ACT-R model to human torque input, thus enabling haptic shared control with autonomy. A parameterization strategy is described to find the set of model parameters that optimize the haptic shared control performance in terms of minimum average lane keeping error (ALKE). The model predicts the minimum ALKE human subjects achieve in shared control. The extended model can successfully predict the best haptic shared control performance as measured by ALKE. This model can be used in place of human operators, enabling fully simulation-based engineering, in the development and evaluation of haptic shared control technologies for autonomy-enabled UGVs, including control negotiation strategies and autonomy capabilities.

Fully Automated Directional Drilling Used on the Norwegian Continental Shelf

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 204016, “Fully Automated Directional Drilling Is Now a Reality: An Example From the Norwegian Continental Shelf,” by Jorge Heredia, SPE, Julien Marck, SPE, and Sara Heller, Halliburton, et al. The paper has not been peer reviewed. _ This paper presents an automated directional-drilling process executed on a commercial well in the Norwegian sector of the North Sea, where an intelligent rotary-steerable system (RSS) completed a well section in a single run with all drilling commands automatically computed, optimized, and downlinked by a drilling-automation platform. The section was complex, consisting of two intervals requiring steering in three dimensions separated by a tangent section. Directional-drilling engineers onshore supervised the operation remotely. No override was required, and the automated system was able to drill the entire section while sending steering decisions automatically. Advances in Drilling Automation Two primary automation controllers that were used in recent steering-automation successes on the Norwegian Continental Shelf are discussed in the complete paper. Recent advancements in RSS technologies use downhole sensors, high-speed processors, and survey packages to provide the backbone for an autonomous downhole navigation system. This type of development enables an automated closed-loop attitude-hold feature. Once configured, the only required downlinks correct trajectory, therefore reducing the total number of downlinks required to steer per section and creating a consistent wellbore quality between wells. This system was applied during the tangent portion of the well discussed in the complete paper. A second development is that of steering automation and advisory systems for deviated steering applications. These systems respond to real-time information from surface systems, including continuous inclination and azimuth measurements from downhole sensors and surface-drilling parameters. The real-time information then is fused with a physics-based digital twin model of the bottomhole assembly (BHA) to produce a calibrated steering model. Based on this hybrid model, the system combines control and optimization algorithms to reconstruct the borehole geometry between the last-available survey and the borehole depth and then provide recommendations for steering magnitudes and direction to meet drilling objectives while accounting for safety margins and drilling constraints. Benefits of the advisory system include reducing human error by removing unnecessary intervention, and automating calculations based off continuous real-time sensor information as opposed to the conventional method of requiring manual interpretation of data. The presented results illustrate the effect of these integrated systems on the improvement of borehole quality and placement and how the controller overcomes typical field situations successfully, such as challenging formations and wellbore conditions and changes in targets and steering objectives. The drilling-automation platform allows the directional-drilling operator to remain onshore in a remote drilling center as opposed to being on the offshore platform. Previous challenges and risks associated with holding operations remotely are being left behind as Internet bandwidth increases and no requirement exists to rely simply on phone and email correspondence; instead, onshore operators can view computers and cameras located at the rigsite in real time.

Systems Modelling of Steering System using OpenModelica

Steering system is one of the key vehicle-driver interface that impacts driving fatigue and perception of quality by driver. It is also a safety critical system governed by several Homologation requirements. While Homologation rules mandates the steering effort to be within certain limits, for a driver, asymmetric behavior in terms of angle & torque between LH & RH turn is also undesirable. The sub-attributes are affected indirectly by packaging constraints in each vehicle platform and model. For meeting the stringent targets in each variant and to maintain minimal unique parts, several design iterations would be needed. Physical testing involves higher cost and time. Hence development of a steering system simulation model becomes essential. This paper details the development of a steering model to simulate and analyze the steering system performance of commercial vehicles. A single steer model with hydraulic assistance is developed using OpenModelica (OM), an open source system modelling software. The parameters such as steering wheel effort, wheel lock angles, Ackermann error and Turning circle diameter (TCD) are computed along with prediction of dry park effort. Based on iterations, an optimized configuration with reduced asymmetry can be derived.

LTV-MPC Approach for Automated Vehicle Path Following at the Limit of Handling.

In this paper, a linear time-varying model predictive controller (LTV-MPC) is proposed for automated vehicle path-following applications. In the field of path following, the application of nonlinear MPCs is becoming more common; however, the major disadvantage of this algorithm is the high computational cost. During this research, the authors propose two methods to reduce the nonlinear terms: one is a novel method to define the path-following problem by transforming the path according to the actual state of the vehicle, while the other one is the application of a successive linearization technique to generate the state–space representation of the vehicle used for state prediction by the MPC. Furthermore, the dynamic effect of the steering system is examined as well by modeling the steering dynamics with a first-order lag. Using the proposed method, the necessary segment of the predefined path is transformed, the linearized model of the vehicle is calculated, and the optimal steering control vector is calculated for a finite horizon at every timestep. The longitudinal dynamics of the vehicle are controlled separately from the lateral dynamics by a PI cruise controller. The performance of the controller is evaluated and the effect of the steering model is examined as well.