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The majority of technological processes include dynamic systems, which are characterized by structural and parameter uncertainty. Conventional control procedures based on such models are unlikely to produce the desired performance since deterministic models cannot appropriately characterize these uncertainties. When dealing with complex nonlinear systems that are characterized by ill-defined and unknown elements, fuzzy-logic based system is an effective method. Fuzzy controllers—whose rule basis is built on the expertise of human experts—are frequently utilized in this context to achieve desired performance. This knowledge might not be adequate for some complex processes, thus different methods for creating IF-THEN rules have been suggested. In this paper, the design of higher-order fuzzy sets is discussed and a generalized novel algorithm is developed for implementing type-n fuzzy sets and it is applied for controlling the angle of steering for a vehicle in such a way that the vehicle tracks the desired path. In the proposed methodology, fuzzification and defuzzification are taking place n number of times, and defuzzification of higher order fuzzy values up to type-1 fuzzy set is performed using the center of gravity method. The obtained type-1 fuzzy values are used in the rule base and inference mechanism for calculating the final crisp output. The significance of the present research is that the computation cost is not as high as expected because both fuzzification and defuzzification processes are recursive and the reduced new type-1 fuzzy values have the additional ability to model the uncertainty and vagueness as compared to normal type-1 fuzzy values. A comparison of the controllers based on the type of fuzzy sets is done based on the square of error (SE). Both the disturbance signal and uncertainty scenarios were also considered. The use of higher-order fuzzy sets facilitates the controller to give the more accurate results for controlling the vehicle and the corresponding simulation results suggest the same. [ABSTRACT FROM AUTHOR]

Steering angle controller is a core module of autonomous vehicles, where a slight miscalculation can cause severe accidents. Following safety precautions, development of robust and precise steering angle predictor is an active area of research. However, existing simulator based steering angle predictors lack in predictive performance and have not been evaluated on same benchmark datasets. Furthermore, most of them are evaluated on simulated datasets and their potential on real-world data as well as in cross-domain evaluation of both types data (real-world, simulated) remain unexplored. To accelerate and expedite research related to steering angle prediction contributions of this paper are manifold: 1) It presents two benchmark datasets that are developed using Udacity and CARLA simulators. 2) Following the need for comparative study, over both simulated datasets, it benchmarks the performance of existing predictors under 2 different evaluation settings namely: same-track and cross-track evaluation. 3) In cross-domain evaluation, it explores generalization potential of predictors by training predictors on simulated data and evaluating them on 2 real-world datasets and vice versa. 4) It presents a robust and precise steering angle predictor that utilizes skip connections for proper gradient flow among different convolutional layers. In same-track evaluation where predictors are trained and evaluated on same-track data, proposed predictor outperforms existing predictors by achieving least Mean Absolute Error (MAE) of 0.13, 0.19 and 0.065 over lake track, jungle track and CARLA based datasets, respectively. Similarly, in cross-track evaluation where predictors are trained on one track and are evaluated on other track data, once again proposed predictor outperforms existing predictors by producing average least MAE errors of 0.33 and 0.06 over Udacity and CARLA datasets, respectively. Over two real-world datasets, Sully Chen and Comma.ai, the proposed predictor demonstrates superior performance compared to existing simulator-based predictors, achieving the lowest MAE of 2.41 and 0.50, respectively.

The technology for determining the location of an object on the ground is the foundation for building vehicle navigation systems and surveillance systems after them. In general, such navigation systems make it possible to determine the coordinates of the vehicle's location and its directional angle, find the direction to the destination, and calculate the coordinates of observation objects. The technical implementation of systems can be quite diverse - from implementation on mechanical elements to their implementation using microelectronics elements. The main factors in the development of navigation systems are the transition to computer-integrated systems and resource-saving technologies. This will make it possible to increase the accuracy of navigation information, obtain a significant gain in the weight and size characteristics of the equipment, reduce its energy consumption and increase reliability. The possibility of modernization of odometrical navigation systems based on integrated computer technologies is considered. [ABSTRACT FROM AUTHOR]

The electro-hydraulic actuator (EHA) system applied in rear axle steering (RAS) is used to steer the rear auxiliary wheels of large commercial vehicles and prevent oversteering. For safety reasons, commercial vehicles reduce the steering angle as the load applied to the rear wheels increases or the speed of the vehicle increases. In this study, we present a well-composed model based design (MBD) of an RAS system employing EHA used in large commercial vehicles. In order to apply loads to the rear of the vehicle to validate the legitimacy of the modeling and to replace the actual model's experiments with the simulations, the rotational speed of the motor obtained in the experiment was input to the motor of the simulation model. The organized formulas of the steering angle based on the structural form were defined to compare the steering angle against both the cylinder displacement of the actual model and the simulated model. We also applied load working on the steering wheel to check the angle difference according to the weight. The organized formulas were applied in the MBD system to compare the results of simulation modeling with the actual experimental values to confirm the modeling's validity. [ABSTRACT FROM AUTHOR]

In this paper, the parameter optimization and error analysis of the rack and pinion steering mechanism are carried out on the basis of considering the influence of kingpin parameters. The steering characteristic equation describing the motion of the steering mechanism is calculated by analyzing the spatial geometrical relationship between the wheel and kingpin and unifying the projection relation between the kingpin and the equivalent steering trapezoid. The ideal Ackermann equation is modified by the Ackermann rate and the kingpin parameters. The modified Ackermann equation is used as the objective function. The segmented fitness function and the evaluation function with weighted factors are designed. A genetic algorithm containing the three functions is used to optimize the parameters of the steering characteristic equation. The error analysis of the numerical example shows that the accuracy of steering trapezoid structure parameters, steering characteristic equation, and Ackermann equation is improved compared with that before optimization. [ABSTRACT FROM AUTHOR]

A fully autonomous vehicle must ensure not only fully autonomous driving but also the safety and comfort of its passengers. However, the self-driving technology that is currently completed focuses only on perfect driving and does not guarantee the safety and comfort of passengers. This paper proposes a braking-pressure and driving-direction determination system (BDDS), which computes the brake pressure and steering angle optimized for passenger safety by utilizing more diverse information than existing autonomous vehicles. The BDDS proposed in this paper consists of two modules. The road roughness classification module (RRCM) classifies the roughness of the road by using the pressure data applied to the suspension and the K-NN algorithm and computes the optimal brake pressure. The passenger recognition and sharing module (PRSM) identifies the current occupant status of the vehicle by using a body pressure sensor and CNN, shares the information with surrounding vehicles, and computes the optimal steering angle using passenger information and road information. As a result of the simulations described in this paper, the parameters of AI models were optimized. In addition, the RRCS was about 7% more accurate than the K-means clustering algorithm, and PRS was about 9% more accurate than the existing seat recognition system. [ABSTRACT FROM AUTHOR]

• In addressing the issue of diminishing peak side lobe levels (PSLL) in non-uniform optical phased array (OPA) as steering angle increases, we introduce a dual-adaption genetic algorithm (DAGA) based on chaos sequence, which optimizes the antenna array layout. This is the first time that an improved chaos sequence is introduced into the genetic algorithm and a dual adaptive degree function is performed to optimize a non-uniform OPA;. • Our findings indicate that, in comparison to traditional genetic algorithm, the PSLL at a steering angle of 80° improved by 2.18, 2.81, and 3.59 dB for the 64-, 128-, and 256-channel respectively;. • The PSLL for 256-channels can be optimized up to an impressive −18.46 dB using this method. Compared with related literature, according to the existing data, under the same number of channels, the steering angle optimized by this algorithm has the lowest PSLL. To address the issue of diminishing peak side lobe levels (PSLL) in non-uniform optical phased array (OPA) as steering angle increases, we introduce a dual-adaption genetic algorithm (DAGA) based on chaos sequence to optimize the antenna array layout. By leveraging chaos mapping traversal and randomness, this approach enhances the diversity of the initial antenna layout, thereby improving the algorithm's capacity to escape local optima. Concurrently, we also reduce background noise during the array steering process to enhance PSLL at large steering angle. In this study, we optimize non-uniform antenna arrays with 64-, 128-, and 256-channels. The results demonstrate that at a steering angle of 80°, the PSLL is improved by 2.18, 2.81, and 3.59 dB, respectively, compared to the conventional genetic algorithm (GA). Notably, for a 256-channel array, the PSLL can be optimized to an impressive -18.46 dB using this method. To our knowledge, this represents the lowest PSLL achieved for an equivalent number of channels. Our research offers valuable insights for the practical implementation of OPAs as transmitters in chip-scale frequency modulated continuous wave (FMCW) light detection and ranging (LiDAR) systems. [ABSTRACT FROM AUTHOR]

Mobil listrik enggang evo3 merupakan salah satu mobil listrik Institut Teknologi Kalimantan (ITK) yang akan diikutkan pada kompetisi mobil listrik di Indonesia. Pengembangan mobil listrik terus dilakukan untuk memaksimalkan performa mobil. Permasalahan yang dihadapi oleh mobil listrik enggang evo3 adalah pada saat bergerak dengan dengan lintasan lurus, berbelok, atau slalom, mobil belum bisa mengikuti lintasan dengan baik. Sudut steer yang digunakan pada mobil enggang evo3 masih belum tepat untuk kondisi lintasan pada perlombaan. Sehingga,dilakukan penelitian tentang studi pengaruh sudut steer terhadap kecepatan lurus dan berbelok pada mobil listrik enggang evo 3. Tujuan dari penelitian ini adakah untuk mengetahui sudut belok mana yang terbaik pada kecepatan dan waktu tempuh mobil enggang evo 3 pada saat berbelok dengan radius belok lintasan yang sudah diketahui pada lintasan perlombaan. Variasi yang digunakan pada penelitian adalah sudut steer 200, 250, 300. Hasil dari penelitian menunjukan bahwa sudut steer terbaik untuk kecepatan dan waktu tempuh adalah sudut steer 20o dengan waktu tempuh 9,70 s dan kecepatan 29,66 km/h. karena semakin kecil sudut steer maka semakin besar kecepatan yang di hasilkan dan semakin besar kecepatan yang dihasilkan maka semakin singkat waktu tempuh yang diperlukan.

Control of pilotless electric vehicles indoors was studied. The issue of ensuring precise correspondence of control signals to the actual motion of transport vehicles in a room was examined. During the course of analyzing the dynamic model of the electric vehicle, it was discovered that the primary reasons for the occurrence of errors consists in the indirect nature of measuring the velocity of this vehicle by means of odometers. In order to solve this problem, it is proposed to use microwave Doppler sensors of the linear velocity of the wheels, observations of which do not depend on sliding, the mass of the electric vehicle, the voltage in the buses, and other parameters. Formulas were developed that make it possible, using the Doppler frequencies of sensors, to determine the current velocity and heading angle of electric vehicle control with the use of the Ackermann condition. Based on the specified formulas, a stable system for traffic control of pilotless transport electric vehicles on a specified route was developed. The proposed system can be used in the robotic transport systems. [ABSTRACT FROM AUTHOR]

Unintentional lane departure accidents are one of the biggest reasons for the causalities that occur due to human errors. By incorporating lane-keeping features in vehicles, many accidents can be avoided. The lane-keeping system operates by auto-steering the vehicle in order to keep it within the desired lane, despite of changes in road conditions and other interferences. Accurate steering angle prediction is crucial to keep the vehicle within the road boundaries, which is a challenging task. The main difficulty in this regard is to identify the drivable road area on heterogeneous road types varying in color, texture, illumination conditions, and lane marking types. This strenuous problem can be addressed by two approaches, namely, ‘computer-vision-based approach’ and ‘imitation-learning-based approach’. To the best of our knowledge, at present, there is no such detailed review study covering both the approaches and their related optimization techniques. This comprehensive review attempts to provide a clear picture of both approaches of steering angle prediction in the form of step by step procedures. The taxonomy of steering angle prediction has been presented in the paper for a better comprehension of the problem. We have also discussed open research problems at the end of the paper to help the researchers of this area to discover new research horizons.

This study presents smooth and fast feasible trajectory generation for autonomous driving vehicles subject to the vehicle physical constraints on the vehicle power, speed, acceleration as well as the hard limitations of the vehicle steering angle and the steering angular speed. This is due to the fact the vehicle speed and the vehicle steering angle are always in a strict relationship for safety purposes, depending on the real vehicle driving constraints, the environmental conditions, and the surrounding obstacles. Three different methods of the position quintic polynomial, speed quartic polynomial, and symmetric polynomial function for generating the vehicle trajectories are presented and illustrated with simulations. The optimal trajectory is selected according to three criteria: Smoother curve, smaller tracking error, and shorter distance. The outcomes of this paper can be used for generating online trajectories for autonomous driving vehicles and auto-parking systems. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient path planning technique for the autonomous collision-free navigation of wheeled mobile robots with simple hardware based on an adaptive neuro-fuzzy inference system (ANFIS). The distance between the robot and obstacles is measured using three ultrasonic sensors that are installed on the left, front, and right of the robot. These distances from the sensors form the inputs to the ANFIS-utility function block that calculates an obstacle avoidance steering angle for the robot. The obstacle avoidance behavior of the robot is modeled under six scenarios of facing an obstacle. The instantaneous position of the robot and the target are available from Global Positioning System (GPS) modules. A simulation mobile robot in V-REP has been integrated into the ANFIS controller coded in MATLAB. The simulation results show that the proposed ANFIS-utility function-based path planning technique surpasses some of the related algorithms in terms of finding near-optimal paths.

A fully autonomous vehicle must ensure not only fully autonomous driving but also the safety and comfort of its passengers. However, the self-driving technology that is currently completed focuses only on perfect driving and does not guarantee the safety and comfort of passengers. This paper proposes a braking-pressure and driving-direction determination system (BDDS), which computes the brake pressure and steering angle optimized for passenger safety by utilizing more diverse information than existing autonomous vehicles. The BDDS proposed in this paper consists of two modules. The road roughness classification module (RRCM) classifies the roughness of the road by using the pressure data applied to the suspension and the K-NN algorithm and computes the optimal brake pressure. The passenger recognition and sharing module (PRSM) identifies the current occupant status of the vehicle by using a body pressure sensor and CNN, shares the information with surrounding vehicles, and computes the optimal steering angle using passenger information and road information. As a result of the simulations described in this paper, the parameters of AI models were optimized. In addition, the RRCS was about 7% more accurate than the K-means clustering algorithm, and PRS was about 9% more accurate than the existing seat recognition system.

In this paper, a linear two degrees of freedom linear bicycle model is proposed to investigate the vehicle handling criterion. The study is based on simulation developed using MATLAB / Simulink to predict the vehicle dynamic stability. Steering angle is given as an input to the mathematical model for various vehicular manoeuvres. This model is validated using a step input which is adjusted to give 0.3g lateral acceleration. The system model is simulated under a typical front wheel steering to examine the highway vehicle prediction output within its manoeuvre. This input is also adjusted to keep lateral acceleration value in steady state region. It is found that changing the vehicle center of gravity (CG) position, vehicle mass, tire cornering stiffness and vehicle speed all have a significant influence on the vehicle dynamic stability. [ABSTRACT FROM AUTHOR]

Vehicle sideslip angle is a major indicator of dynamics stability for ground vehicles; but it is immeasurable with commercially‐available sensors. Sideslip angle estimation has been the focus of intensive research in past decades, resulting in a rich library of related literature. This study presents a comprehensive evaluation of state‐of‐the‐art sideslip angle estimation methods, with the primary goal of quantitatively revealing their strengths and limitations. These include kinematics‐, dynamics‐ and neural network‐based estimators. A hardware‐in‐loop system is purposely established to examine their performance under four typical manoeuvres. The results show that the dynamics‐based estimators are suitable at low vehicle velocities when tires operate in the linear region. In contrast, the kinematics‐based methods yield superior estimation performance at high vehicle velocities, and the inclusion of the dual GPS receivers is beneficial even when there is large disturbance to the steering angle. Of utmost importance, it is experimentally manifested that the neural network‐based estimator can perform well in all manoeuvres once the training datasets are properly selected. [ABSTRACT FROM AUTHOR]

In this paper, a linear two degrees of freedom linear bicycle model is proposed to investigate the vehicle handling criterion. The study is based on simulation developed using MATLAB / Simulink to predict the vehicle dynamic stability. Steering angle is given as an input to the mathematical model for various vehicular manoeuvres. This model is validated using a step input which is adjusted to give 0.3g lateral acceleration. The system model is simulated under a typical front wheel steering to examine the highway vehicle prediction output within its manoeuvre. This input is also adjusted to keep lateral acceleration value in steady state region. It is found that changing the vehicle center of gravity (CG) position, vehicle mass, tire cornering stiffness and vehicle speed all have a significant influence on the vehicle dynamic stability. [ABSTRACT FROM AUTHOR]

In this paper, prior to the commercialization of a developed active steering bogie, we want to analyze steering performance experimentally according to steering angle level with the aim of obtaining steering performance data to derive practical design specifications for a steering system. In other words, the maximum steering performance can be obtained by controlling the steering angle at the 100% level of the target steering angle, but it is necessary to establish the practical control range in consideration of the steering system cost increase, size increase, and consumer steering performance requirements and commercialize. The steering control test using the active steering bogie was conducted in the section of the steep curve with a radius of curvature of R300, and steering performance such as bogie angle, wheel lateral force, and derailment coefficient were analyzed according to the steering angle level. As the steering angle level increased, the bogie indicated that it was aligned with the radial steering position, and steering performance such as wheel lateral force and derailment coefficient was improved. The steering control at 100% level of the target steering angle can achieve the highest performance of 83.6% reduction in wheel lateral force, but it can be reduced to about one-half of the conventional bogie at 25% level control and about one-third at 50% level. Considering cost rise by adopting the active steering system, this result can be used as a very important design indicator to compromise steering performance and cost rise issues in the design stage of the steering system from a viewpoint of commercialization. Therefore, it is expected that the results of the steering performance experiment according to the steering angle level in this paper will be used as very useful data for commercialization. [ABSTRACT FROM AUTHOR]

The impact of the kinematic parameters of bounce and pitch motions of wheeled vehicles’ (WVs’) sprung mass (SM) with non-linear power characteristics of the cushion system on vehicles handling is studied. The dependence of the critical value of the dynamic steering angle of directive wheels on the amplitude of bounce and pitch motions and the kinematic parameters of motion is developed. It is proven that the limit value of the dynamic steering angle of directive wheels is reduced during acceleration, and vice versa (it increases during braking, while the bounce and pitch motions are significantly reduced).

Detection of drivers' states is the essential technology not only to prevent car accidents related with their state but to develop self-driving car. Detecting technology generally uses two types of methods; physiological measures and vehicle-based measures. Vehicle-based measures have advantages compared to physiological method such as non-additional device, unsophisticated process and less computational power. For these reasons, vehicle-based measures are used for this study to build the detection system about 3 states; normal, drowsy and drunk driving. In order to achieve this purpose, three types of algorithm models are suggested using vehicle simulator experiments with twelve participants on three states; normal, drowsy and drunk. By analyzing the accuracy of each input packet data combination, the feature values, the configuration of the input data calculated through the vehicle driving data is used to derive the influential factors for predicting the driver state. The results of the models indicate high accuracy and give the possibility to be applied on detecting 3 states in real driving vehicles with the system using combination of developed models. [ABSTRACT FROM AUTHOR]

Precision agriculture, such as precise seeding or ploughing, is guaranteed by vehicle navigation accuracy. A steering angle plays an essential and fundamental role in the function of autonomous vehicle and the path planning because it controls the vehicle direction. However, the steering angle cannot be calibrated directly from Global Navigation Satellite System (GNSS) due to the limitation of GNSS parameters. In addition, the accuracy of steering angle obtained from the analysis of Global Position System (GPS) information cannot satisfy the accuracy requirements in engineering applications. In this paper, a novel approach to improve accuracy of steering angle is proposed. Low-cost Micro-electromechanical System (MEMS) and GPS are combined on an agriculture vehicle so that the steering angle can be calculated precisely. Unscented Kalman Filters (UKF) are used in simulations to estimate the steering angle. The simulation and experiment results show that the proposed method can achieve increased accuracy of estimation of steering angle than that based merely on GPS information. Because the cost of a MEMS gyroscope is very low, the proposed method is a practical way to achieve precision agriculture with high accuracy. [ABSTRACT FROM AUTHOR]

Driver drowsiness is a factor in at least 20% of serious motor vehicle accidents. Although research has shown that Whole-Body Vibration (WBV) can induce drowsiness in drivers, it is unknown whether particular frequencies are more problematic. The present study systematically investigated the influence of WBV frequency on driver drowsiness. Fifteen participants each undertook six 1-h sessions of simulated driving while being subjected to WBV of either 0 Hz (no vibration), 1–4 Hz, 4–8 Hz, 8–16 Hz, 16–32 Hz or 32–64 Hz. Subjective sleepiness, as measured by the Karolinska Sleepiness Scale (KSS), confirmed that drivers felt drowsier when exposed to the two lowest frequency ranges (1–4 Hz and 4–8 Hz). Reaction time, which measures attention and alertness, was significantly impaired by the two lowest frequency ranges. Objective driving performance measures (Standard Deviation of Lane Position (SDLP), Standard Deviation of (SD) Steering Angle, Time in Unsafe Zone) also showed significant degradation due to exposure to the two lowest frequency ranges. Exposure to 1–4 Hz or 4–8 Hz vibration caused attention to become significantly impaired within 15–20 min and driving performance to be significantly impaired by 30–35 min. The other frequency ranges had little or no effect. These findings point to a need to develop equivalent vibration-induced drowsiness contours that can be adopted as transportation safety standards. • The effects of 60 min of whole-body vibration on reaction time, and driving performance were systematically examined. • Reaction times were significantly slowed after 15–20 min of exposure to 1–4 Hz and 4–8 Hz. • Driving metrics were significantly degraded after 30–35 min exposure to 1–4 Hz and 4–8 Hz. • Higher frequencies (8–64 Hz) had a minimal effect on drowsiness and driving performance. [ABSTRACT FROM AUTHOR]

This study presents smooth and fast feasible trajectory generation for autonomous driving vehicles subject to the vehicle physical constraints on the vehicle power, speed, acceleration as well as the hard limitations of the vehicle steering angle and the steering angular speed. This is due to the fact the vehicle speed and the vehicle steering angle are always in a strict relationship for safety purposes, depending on the real vehicle driving constraints, the environmental conditions, and the surrounding obstacles. Three different methods of the position quintic polynomial, speed quartic polynomial, and symmetric polynomial function for generating the vehicle trajectories are presented and illustrated with simulations. The optimal trajectory is selected according to three criteria: Smoother curve, smaller tracking error, and shorter distance. The outcomes of this paper can be used for generating online trajectories for autonomous driving vehicles and auto-parking systems.

In this paper, prior to the commercialization of a developed active steering bogie, we want to analyze steering performance experimentally according to steering angle level with the aim of obtaining steering performance data to derive practical design specifications for a steering system. In other words, the maximum steering performance can be obtained by controlling the steering angle at the 100% level of the target steering angle, but it is necessary to establish the practical control range in consideration of the steering system cost increase, size increase, and consumer steering performance requirements and commercialize. The steering control test using the active steering bogie was conducted in the section of the steep curve with a radius of curvature of R300, and steering performance such as bogie angle, wheel lateral force, and derailment coefficient were analyzed according to the steering angle level. As the steering angle level increased, the bogie indicated that it was aligned with the radial steering position, and steering performance such as wheel lateral force and derailment coefficient was improved. The steering control at 100% level of the target steering angle can achieve the highest performance of 83.6% reduction in wheel lateral force, but it can be reduced to about one-half of the conventional bogie at 25% level control and about one-third at 50% level. Considering cost rise by adopting the active steering system, this result can be used as a very important design indicator to compromise steering performance and cost rise issues in the design stage of the steering system from a viewpoint of commercialization. Therefore, it is expected that the results of the steering performance experiment according to the steering angle level in this paper will be used as very useful data for commercialization.

For the transport of large-tonnage equipment and structures, most of them use multiple hydraulic trucks to combine. The coordinated control of the hydraulic trucks’ hydraulic system groups is particularly important. The coordinated control of two hydraulic trucks from a company was studied during the steering of combined transportation. First, the hydraulic steering mechanism was analysed, and the functional relationship between steering angle and hydraulic cylinder stroke was obtained. Then, the synchronisation control strategy was compared and analysed, and the synchronous control mode with higher precision was selected. The mathematical model of the steering system was established, and the AMESim model and Simulink model were established to verify the feasibility of the control strategy. Finally, the steering tests of no load and full load were carried out. It was found that the actual test results were basically consistent with the simulation results. It was verified that the steering system with load-sensing pump and master–slave coordinated PID control strategy can better realise coordinated steering action.

This paper presents an analysis of vehicle trajectory on curved path, in the presence of lateral sliding. The pure rolling motion is not always possible especially where working conditions are rough and not predictable. To take sliding effects into account, the variables which characterize sliding effects are introduced into the mathematical model (steering angle, vehicle speed, tire cornering stiffness and etc.). This mathematical model is linear with two freedom degrees. From the study based on the verification of force in the contact zone tire/ground, we conclude that speed exceeding 60 km/h and small steering angles can destabilize the vehicle.

Highlights • A steering angle measurement system based on the double GNSS and two MEMS gyroscopes is proposed. • The system uses the error equation of steering angle and the vehicle kinematics model to build an adaptive Kalman filter. • The lever-arm compensation is proposed to correct the speed error when calculate the measurement of Kalman filter. Abstract In automatic driving system research of precision agriculture, the wheel steering angle was usually measured by the non-contact absolute angle sensor such as Hall-effect sensor and angle encoder sensor. The problem of those angle sensors was the complex mechanical structure which result in the difficulty of installation and maintenance. However, the gyroscope had the advantages of simple installation and long working life. But the gyroscope bias causes the error accumulates over time in automatic driving system. To solve this problem, a wheel steering angle measurement system based on double Global Navigation Satellite System (GNSS) antennas and two Micro-Electro-Mechanical System (MEMS) gyroscopes was proposed. The double GNSS antennas system provided the speed, attitude angle, latitude and longitude of the vehicle. In addition, one MEMS gyroscope was mounted on the wheel and measured the steering rate and another MEMS gyroscope was mounted on the vehicle to measure the heading angular rate. Meanwhile, an adaptive Kalman filter using the above data was designed to correct the errors of integration of the gyroscope data. The adaptive filter could adjust the noise matrix according to the changes of system noise caused by road conditions and different tools. At the same time, the lever-arm compensation algorithm was used to solve the speed error caused by lever-arm. Experiment was carried out to verify the effectiveness of the system. The average error of the straight line experiment was 0.06 and the error variance was 0.215 and the curve line experiment’s mean error was 0.746 and the error variance was 0.908. The result of the experiments showed that this system could meet the request of automatic driving system. [ABSTRACT FROM AUTHOR]

An active steering system was developed to solve problems such as severe wheel, rail wear, noise and dust generation due to insufficient steering performance of EMU running on an urban railroad section with a large number of curved sections. An electromechanical type active steering system for EMU was designed and a prototype was manufactured. As a result of the performance test of the components for the active steering system, the target design specification was satisfied. Prior to the performance test with test vehicle equipped with the active steering system on test track, the steering control test simulating real track running was conducted, excellent steering performance was noted. The thrust force of the driving unit was also shown to be below the maximum thrust force of the prototype throughout most parts of the track. These results confirm that the simulation test can predict the feasibility of the steering control on the test track for the active steering test vehicle through this simulation test. [ABSTRACT FROM AUTHOR]

Today, in the construction of smart city, the development of self-driving technology plays the key role. The explosion of convolutional neural network (CNN) technology has made it possible to utilize end-to-end tasks with images. However, today's CNN has deeper, more accurate characteristics. If we do not improve the calculation method to reduce the number of network parameters, this feature makes it very difficult for us to run neural network computing in small devices. In this paper, we further optimize the network computing methods based on MobileNets to reduce number of network parameters. At the same time, in the network structure, we add BatchNormalization and Swish activation function. We designed our own network in the end-to-end prediction for steering angle in the self-driving car task. From the final simulation results, our neural network's storage space can be reduced and the execution speed of neural network can be improved while maintaining the accuracy of the neural network. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel strategy for the synthesis of uniformly excited thinned planar antenna (UE-TPA) arrays which renders maximum possible reduction in the peak side lobe level (PSLL) with minimum number of turn ‘ON’ elements over wide steering angles. The main objective of this paper is to investigate an efficient variant of genetic algorithm (GA) which yields good quality solution at affordable computational complexity. Towards this aim, authors attempted to develop a powerful synthesis tool denoted as improved binary coded GA (IBc-GA) by investigating novel chromosome arrangements and ameliorated process techniques for crossover and mutation operations to improve the flexibility as well as the global search ability in achieving the best possible reduction in PSLL without increasing computational burden. In order to corroborate the effectiveness and superiority of the proposed synthesis technique, two examples consisting of 10 × 10- and 14 × 14-elements UE-TPA arrays are numerically examined at antenna boresight as well as when the arrays are electronically steered up to 40° with respect to antenna boresight in both azimuth and elevation planes. The numerical results of 10 × 10-element UE-TPA obtained through the proposed synthesis method at antenna boresight are compared with those determined at 20° and 40° scan angles and with those of same size arrays reported in the literature. In addition, results at antenna boresight achieved by proposed method for the case of 14 × 14-element UE-TPA array are compared with those determined at 20° and 40° scan angles. It is inferred from the investigation that wide angle scanning with lowest possible PSLL and without appearance of grating lobes is achieved at comparable computational cost. [ABSTRACT FROM AUTHOR]

• The Intelligent Transportation System (ITS) can assist the behavior driver on road, based vision sensor to monitoring steering angle actuator (steering wheel). • The duality between vision sensors and smart soft-sensors is very interesting in different embedded robotics systems. • This work provides a new approach to integrating smart soft sensors into ITS system. • The proposal smart soft sensor can be applied in smart cities. Sensors are considered as a great invention that radically contributed to saving time and effort for humans while moving or transporting things. That's the reason why, researchers are constantly working on a smart vision sensor that can provide important data such as directions, temperature, speed, risks... to drivers. Nowadays, there is a new tendance of smart cities that recommend the equipment of vehicles with sensors that can facilitate communication between all categories of vehicles. In this paper, we proposed an in-depth study for developing an assistance system that assists controls the vehicle position, managed a vision sensor (camera) that provides a perception of the road environment in real-time. Then to calculate the Steering Angle (SA), we use the Smart Soft-Sensors that take into consideration the road edges in the images. Each road image is identified by the SA, these images will be trained in a GPU processor using Nvidia's End to End architecture. Then an adaptive control by applications of the proposed system, gives SA estimated to assist in controlling the actuator (Steering Wheel). The results obtained by this approach encourage integrating it into automotive embedded systems to make the right behavior on the road. [ABSTRACT FROM AUTHOR]

This study proposes a drowsiness detection approach based on the combination of several different detection methods, with robustness to the input signal loss. Hence, if one of the methods fails for any reason, the whole system continues to work properly. To choose correct combination of the available methods and to utilize the benefits of methods of different categories, an image processing-based technique as well as a method based on driver-vehicle interaction is used. In order to avoid driving distraction, any use of an intrusive method is prevented. A driving simulator is used to gather real data and then artificial neural networks are used in the structure of the designed system. Several tests were conducted on twelve volunteers while their sleeping situations during one day prior to the tests, were fully under control. Although the impact of the proposed system on the improvement of the detection accuracy is not remarkable, the results indicate the main advantages of the system are the reliability of the detections and robustness to the loss of the input signals. The high reliability of the drowsiness detection systems plays an important role to reduce drowsiness related road accidents and their associated costs.

Nowadays, a concept of tilting three-wheel vehicle is introduced, one of which is the electric tilting tricycle to provide an alternative mode of transportation. Some of the tilting tricycle design usinga tadpole trike configuration and it needs an adequate steering system that can be synergized with tilting mechanism. The steering mechanism follows the Ackermann steering geometry. Usage of Ackermann geometry means applying a mechanism of trapezoidal four-bar linkage to the tricycle. To create and maintain the simple trapezoid shape, Triple Ball Tie-rod model, a single rod which supports three ball joints, is proposed. Since the capabilities of the model are yet to be proven, this research evaluates the usageof a tie-rod model to find out its capabilities to support the works of the steering mechanism of the tricycle. The measurements are conducted after the simulation of the 3D model to extract some data such as maximum lean angle and inner and outer steering angles. Another simulation using regular tie-rod model also conducted with the same method for comparison purposes. The results of the study are maximum allowed tilting angle and generated Ackermann steering angles. Each designed models have their respectiveadvantages.

The impact of the kinematic parameters of bounce and pitch motions of wheeled vehicles' (WVs') sprung mass (SM) with non-linear power characteristics of the cushion system on vehicles handling is studied. The dependence of the critical value of the dynamic steering angle of directive wheels on the amplitude of bounce and pitch motions and the kinematic parameters of motion is developed. It is proven that the limit value of the dynamic steering angle of directive wheels is reduced during acceleration, and vice versa (it increases during braking, while the bounce and pitch motions are significantly reduced). [ABSTRACT FROM AUTHOR]

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Learning and self-adaptation ability is highly required to be integrated in path planning algorithm for underwater robot during navigation through an unspecified underwater environment. High frequency oscillations during underwater motion are responsible for nonlinearities in dynamic behavior of underwater robot as well as uncertainties in hydrodynamic coefficients. Reactive behaviors of underwater robot are designed considering the position and orientation of both target and nearest obstacle from robot's current position. Human like reasoning power and approximation based learning skill of neural based adaptive fuzzy inference system (ANFIS) has been found to be effective for underwater multivariable motion control. More than one ANFIS models are used here for achieving goal and obstacle avoidance while avoiding local minima situation in both horizontal and vertical plane of three dimensional workspace. An error gradient approach based on input-output training patterns for learning purpose has been promoted to spawn trajectory of underwater robot optimizing path length as well as time taken. The simulation and experimental results endorse sturdiness and viability of the proposed method in comparison with other navigational methodologies to negotiate with hectic conditions during motion of underwater mobile robot. [ABSTRACT FROM AUTHOR]

Although much research has been devoted to the characterization of the effects of whole-body vibration on seated occupants' comfort, drowsiness induced by vibration has received less attention to date. There are also little validated measurement methods available to quantify whole body vibration-induced drowsiness. Here, the effects of vibration on drowsiness were investigated. Twenty male volunteers were recruited for this experiment. Drowsiness was measured in a driving simulator, before and after 30-min exposure to vibration. Gaussian random vibration, with 1-15 Hz frequency bandwidth was used for excitation. During the driving session, volunteers were required to obey the speed limit of 100 kph and maintain a steady position on the left-hand lane. A deviation in lane position, steering angle variability, and speed deviation were recorded and analysed. Alternatively, volunteers rated their subjective drowsiness by Karolinska Sleepiness Scale (KSS) scores every 5-min. Following 30-min of exposure to vibration, a significant increase of lane deviation, steering angle variability, and KSS scores were observed in all volunteers suggesting the adverse effects of vibration on human alertness level. [ABSTRACT FROM AUTHOR]

Driving environments have been designed basically for travel by physically and mentally unimpaired people. On the other hand, sufficient, special considerations are not given to the vehicles driven by disabled people. In order to examine the ergonomic driving load put on both disabled and physically unimpaired people while they are on highways, the driving conditions and the muscle-stress of disabled people were evaluated on the approach to curves. Also the influence of acceleration-and-deceleration and centrifugal force on vehicles were evaluated in straight, split and inter-flows of traffic. The subjects of this study consisted of 5 physically unimpaired people and 10 disabled people who required auxiliaries for their vehicles due to handicaps of their lower limbs or to both upper and lower limbs. The study was conducted on the loop line of the Hanshin Expressway in Osaka, Japan. As a result of measuring the accelerated velocity of vehicles in motion and electromyograms of drivers of the vehicles, it was found that the driving load of disabled people is heavier than that of physically unimpaired people. It was also found that certain driving conditions are different for disabled people to travel at high speed.

This study presents high‐precision path tracking controllers to follow a parking path in which change in the movement direction is required along it. Compared with other existing path tracking controllers, the automatic control of the movement direction and the necessity of zero velocity at the switching and end points of the parking manoeuvre are considered in the controller design. To this aim, two time‐domain functions are proposed depending on the movement direction. Then, two function‐domain tracking controllers based on feedback linearisation control and sliding mode control (SMC) structures are designed. The stability of the tracking controllers is analysed and guaranteed. Unlike the conventional SMC, the control signals of the function‐domain SMC are very smooth. Moreover, designing the tracking controller in the function‐domain can be a solution to modify the tracking controllers that have problem in the control law for the steering angle at zero speed. In the proposed controllers, the steering angle and the driving velocity are fully controlled by the controllers, and the robot automatically stops at the critical points independent of the position estimation and velocity tracking errors. Simulation results demonstrate the effectiveness of the proposed controllers to steer the robot along the reference path. [ABSTRACT FROM AUTHOR]

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals' drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers' drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles. [ABSTRACT FROM AUTHOR]

The electric golf cart of LIPI is designed traditionally without calculating geometric and kinematic properties of it steering layout. Furthermore, it resulting less quality of handling and make it less safe to operate. The kinematics calculation of steering linkages has been explained by Ackerman. So, this paper's purpose is to calculate and make recommendation for electric golf cart of LIPI as a solution for improving the handling quality. The result is that maximum turning angle of the car is limited by 30° and the car has R at 372 cm. This is an ideal value according to Ackerman calculation. [ABSTRACT FROM AUTHOR]

In this paper, a new signal processing algorithm for ultrasonic sensory systems in airborne transmission is presented. The proposal is based on a phased array (PA) where the excitation signals are loosely synchronous (LS) sequences, often used in code division multiple access communication systems. Hence, by setting a different LS sequence for each steering angle, it is possible to simultaneously acquire all the information of the scanned area with a single fire, in order to detect possible reflectors in front of the sensory array. The use of these LS sequences combined with PA techniques allows to simultaneously steer the main beam in different directions with low interference. Simulation results reveal that this approach does not only provide longer distance inspection, but also noise robustness. Furthermore, this algorithm provides higher image rate than conventional PA techniques even for high-quality images, since the image rate does not depend on the number of steering angles to be explored. [ABSTRACT FROM PUBLISHER]

This study proposes a drowsiness detection approach based on the combination of several different detection methods, with robustness to the input signal loss. Hence, if one of the methods fails for any reason, the whole system continues to work properly. To choose correct combination of the available methods and to utilize the benefits of methods of different categories, an image processing-based technique as well as a method based on driver-vehicle interaction is used. In order to avoid driving distraction, any use of an intrusive method is prevented. A driving simulator is used to gather real data and then artificial neural networks are used in the structure of the designed system. Several tests were conducted on twelve volunteers while their sleeping situations during one day prior to the tests, were fully under control. Although the impact of the proposed system on the improvement of the detection accuracy is not remarkable, the results indicate the main advantages of the system are the reliability of the detections and robustness to the loss of the input signals. The high reliability of the drowsiness detection systems plays an important role to reduce drowsiness related road accidents and their associated costs. [ABSTRACT FROM AUTHOR]

This paper focuses on an efficient and robust control scheme of electronic differential system for sensorless drive based electric vehicle. It has two brushless DC motors(BLDC). Electronic differential system ensures the maximum torque and it can control both the driving wheel independently to turn at different speeds in any curve and also distribute the power to each motor according to the steering angle. Hall sensors are temperature sensitive and reduce the overall system reliability and so sensorless control method is preferred in this research work. It paves the reliable way to operate the motor in order to avoid unpredictable handling and application in harsh environment. The BLDC motor has been controlled by the method of back EMF zero crossing detection. The effectiveness and substantiation of the proposed methods are ascertained in the MATLAB/Simulink environment. Simulation results gives satisfactory performance with the proposed electronic control scheme which also ensures the stability of the vehicle in all road conditions. [ABSTRACT FROM AUTHOR]

Abstract: FlexRay is one of the next communication standard of automobile network system. Compare with traditional CAN bus, it has many advantages like dererministic communication and support fault-tolerance. This paper chooses steerby- wire (SBW) system as application object of FlexRay bus, show that FlexRay is better than CAN in safety-critical system. First, analyze the characteristics of FlexRay and desigan a simplified SBW system.Then, Measure the steering wheel angle and design FlexRay communication network, include the configuration of key parameters and distribution of tasks for two nodes of SBW system. Finally, the experiment of simplified SBW was performed. The experiment result shows that the characteristics of FlexRay are more suitable than CAN in safety-critical system. [Copyright &y& Elsevier]

We study the steady turn behaviours of some light motorcycle models on circular paths, using the commercial software package ADAMS-Motorcycle. Steering torque and steering angle are obtained for several path radii and a range of steady forward speeds. For path radii much greater than motorcycle wheelbase, and for all motorcycle parameters including tyre parameters held fixed, dimensional analysis can predict the asymptotic behaviour of steering torque and angle. In particular, steering torque is a function purely of lateral acceleration plus another such function divided by path radius. Of these, the first function is numerically determined, while the second is approximated by an analytically determined constant. Similarly, the steering angle is a function purely of lateral acceleration, plus another such function divided by path radius. Of these, the first is determined numerically while the second is determined analytically. Both predictions are verified through ADAMS simulations for various tyre and geometric parameters. In summary, steady circular motions of a given motorcycle with given tyre parameters can be approximately characterised by just one curve for steering torque and one for steering angle. [ABSTRACT FROM AUTHOR]

This paper describes the optimization of designing a two-dimensional (2-D) ultrasound phased array to be used for the treatment of both prostate cancer and benign prostatic hyperplasia. The optimization study took into consideration the physical constraints of the conventional method of treatment, and arrived at an optimized array design with the overall dimensions of 10 cm × 2.2 cm. The optimization study also addressed the following additional parameters: The maximum possible depth of penetration (DOP), the maximum possible steering angle, the Grating lobe level, the operating frequency, and the element size. In optimizing the design, the DOP and the steering angle are maximized while the grating lobe value is minimized. A 56 × 12 element 2-D array was found to be the optimum choice allowing both focusing and steering within the entire prostate without inducing damage at locations other than that of the focal point. [ABSTRACT FROM AUTHOR]