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Many driver assistance systems require knowledge of the vehicle environment. As these systems are increasing in complexity and performance, this knowledge of the environment needs to be more complete and reliable, so sensor fusion combining long, medium and short range sensors is now being used. This paper analyzes the feasibility of using ultrason...
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... the worst resolution occurs when sensor 2 detects the obstacle. In the following sample sensor 1 (n = 1) has detected the obstacle, since in this case the speed estimation passes from ( ) Table 1 contains the main features of the ultrasonic sensors considered. From these data, the LV-EZ3 sensor is the one that provides greater benefits, as the range, even though limited, is the longest of the sensors considered and, additionally, the sampling frequency exceeds 250 Hz, specified in the section above. ...
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Citations
... Support vector machines (SVM) are used to distinguish targets such as wooden strips and blocks. But the high prices make more people choose ultrasonic sensors instead of laser sensors [9]. Therefore, the identification system based on ultrasonic sensors can improve the system's stability and reduce costs. ...
In this paper, an ultrasonic target identification system based on Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) is proposed to improve the productivity efficiency of industrial production. The proposed system can accurately identify targets of different shapes. Two pieces of 3 × 3 PMUTs arrays with a resonant frequency of 115 kHz are used as the transmitter and receiver of the PMUTs-based ultrasonic sensor. The sensor is small in size and has high instability. In addition, the PMUTs based ultrasonic sensors have lower environmental requirements than vision sensors and are less expensive than laser sensors. Therefore, the sensors are suitable for large-scale use in industry. The characteristics of the proposed system are investigated in the shape experiments on the square, circle, frame, and ring targets. The four kinds of targets are acrylic plates with a thickness of 5mm. The experimental results show that the system can accurately identify the shapes of the four targets through the grid-based scheme. Besides, the identification process is automatically completed by the 3D mobile platform. The proposed system has demonstrated a cost-effective method to identify targets of different shapes, which can more efficiently guide the robotic manipulator’s grasping and other behaviors.
... Target detection is widely used in the fields of autonomous driving [1,2], target tracking [3,4], obstacle avoidance [5,6], and so on. Among various target detection methods, the method of ultrasonic sensors based on Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) has attracted much attention due to its small size, low cost, low power consumption, compatible with Complementary Metal Oxide Semiconductor (CMOS) process and simple system structure, which is an economical method to install on the robotic manipulator for detecting glass substrates in the automated production line. ...
... Compared with the above sensors, ultrasonic sensors are cheap and robust in a variety of environmental conditions. In autonomous driving, Jiménez et al. used ultrasonic sensors to replace laser sensors, which effectively reduced the cost [1]. Li et al. used a linear ultrasonic sensor array with an improved Kalman filter algorithm to achieve dynamic tracking of targets with different materials and shapes [3]. ...
In this paper, an ultrasonic target detection system based on Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) is proposed, which consists of the PMUTs based ultrasonic sensor and the sensor system. Two pieces of 3 × 3 PMUTs arrays with the resonant frequency of 115 kHz are used as transmitter and receiver of the PMUTs-based ultrasonic sensor. Then, the sensor system can calculate the target’s position through the signal received by the above receiver. The static and dynamic performance of the proposed prototype system are characterized on black, white, and transparent targets. The experiment results demonstrated that the proposed system can detect targets of different colors, transparencies, and motion states. In the static experiments, the static location errors of the proposed system in the range of 200 mm to 320 mm are 0.51 mm, 0.50 mm and 0.53 mm, whereas the errors of a commercial laser sensor are 2.89 mm, 0.62 mm, and N\A. In the dynamic experiments, the experimental materials are the targets with thicknesses of 1 mm, 1.5 mm, 2 mm and 2.5 mm, respectively. The proposed system can detect the above targets with a maximum detection error of 4.00%. Meanwhile, the minimum resolution of the proposed system is about 0.5 mm. Finally, in the comprehensive experiments, the proposed system successfully guides a robotic manipulator to realize the detecting, grasping, and moving of a transparent target with 1 mm. This ultrasonic target detection system has demonstrated a cost-effective method to detect targets, especially transparent targets, which can be widely used in the detection and transfer of glass substrates in automated production lines.
... A brief review of the state-of-the-art ultrasonic sensor with wave propagation, atmospheric attenuation, sound wave reflection, and target tracking, along with market penetration of ultrasonic sensors, is presented in [135]. Most of the studies on ultrasonic sensor performance are presented in [136][137][138][139][140][141][142][143][144][145][146][147], which focus on the ability of sound waves to detect, reflect, and track the target. Besides, sound wave propagation in the presence of changing winds and temperatures, as well as several new designs to enhance resolution, have been introduced. ...
... However, the results of all experiments show that good resolution is achieved within a shorter timeframe and the target wave reflection is accurate and reliable. The authors of [136][137][138][139][140][141][142][143][144][145][146][147], suggest the use of ultrasonic sensors for near-field perception based on their experimental studies. ...
Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.
... Proximity sensors will be used in this part. The results of tests on a test track using these sensors demonstrate their ability to accurately determine the kinematic variables of the obstacles encountered, despite a clear limitation in range [4]. The sensors are using the ultrasound, microwave and electromagnetic waves for that detections. ...
... The paper will focus on multiple safety systems including blind spot detection [3], emergency barking system and short-radar obstacle detector and proximity sensors will be used as well. The results of tests on a test track using these sensors This work was supported in part by the RCSA and STLR Grant., University of Central Oklahoma, Edmond, OK 73034 USA demonstrate their ability to accurately determine the kinematic variables of the obstacles encountered, despite a clear limitation in range [4]. The sensors are using the ultrasound, microwave and electromagnetic waves for the detection. ...
This paper proposes and presents a complete global system that can be deployed and used with any vehicle including heavy trucks. The proposed system intended to enhance the safety of the vehicle by decreasing human errors while driving and monitor the health condition of the driver. The paper will demonstrate the environment that the RF propagates using the frequency-domain method to connect all systems together. The paper will focus on the proximity sensors and their detection of blind spots and sudden breaks and it will demonstrate the role of electromagnetic waves in the short-range radar to detect obstacles. The proposed system will utilize the IoT to send the triggered data to a server for processing and taking further actions.
... The most commonly used are laser sensor, IR sensor and computer vision. Different studies compare the advantage and limitation of these technologies [2]. ...
Rail transports are facing lots of challenges in our day to day life such as collision detection and derailment. Relevant obstacle information about obstacle is given prior to the locomotive driver by using two ultrasonic sensors. This ultrasonic sensor has transmitter and receiver. This transmitter continuously transmits the ultrasonic waves. One Sensor at the front end of the train detects the distance of the obstacle from the train. Another sensor fixed near the wheel which detects the discontinuity of track continuously. Based on the ultrasonic sensor output, time between the transmission of ultrasonic waves and its reception the distance of the obstacle is calculated and continuously it displays the distance between the obstacle and train. If an obstacle is detected timer starts to run for (20sec), if the obstacles seems there after that preset time, then the information about the obstacle is sent to the microcontroller. Then the alarm starts to blow automatically to alert the loco pilot and control the speed of the train. Otherwise, there is no need to stop the train, as the obstacle seems to be out of the railway track.
... For car and other vehicle drivers, there are many types of collision warning system. These systems rely on global position system (GPS) based inter-vehicle communications method [32,33], radar [34], laser-scanners [35], ultrasonic [36] and camera-based approaches [37,38], etc., for collision detection as given in Table 2.2 below. ...
In many countries, motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. Collision detection systems can be used to minimize these fatalities. However, most of the existing collision detection systems do not identify the type of potential hazard faced by motorcyclists. Every collision warning system used a distinctive collision detection technique, which limits its performance and makes it imperative to study its effectiveness. Unfortunately, no such work has been reported in that particular domain for motorcyclists. Therefore, it is important to study the physiological response of the motorcyclist against these collision warning systems. In this research, a rear end vehicle detection and classification method is presented for motorcyclists. For collision detection, vision technique and acoustic technique have been used. For visual and acoustic techniques, appearance features and power spectrum have been used, respectively, to detect the approaching vehicle at the rear end of the motorcycle. As for the vehicle classification, only an acoustic technique is utilized; an acoustic power spectrum and energy features are used to classify the approaching vehicles. Two types of datasets which are comprised of self-recorded datasets (obtained by placing a camera at the rear end of a motorcycle) and online datasets (for vision-based vehicle detection and for audio based vehicle classification techniques) are used for validation. Proposed methodology successfully detected and classified the vehicle for self-recorded datasets. Similarly, for online datasets, the higher true positive rate and less false detection rate has been achieved as compared to the existing state of the art methods. Moreover, an event-related potential (ERP) based physiological study has been performed on motorcyclists to investigate their responses towards the rear end collision warning system. Two types of auditory warnings (i.e., verbal and buzzer) are used for this warning system. To study the response of the motorcyclists, the N1, N2, P3, and N400 components have been extracted from the Electroencephalography (EEG) data. These introduced systems have shown positive effects at neural levels on motorcyclists and reduce their reaction time and attentional resources required for processing the target correctly. In summary, the proposed rear-end collision warning system with auditory verbal warnings significantly increases the alertness of the motorcyclist and can be helpful to avoid the possible rear-end collision scenarios.
... Salah satunya adalah informasi tentang jarak kendaraan terhadap sebuah objek tertentu. Komputer mampu melakukan pengukuran jarak dengan tingkat akurasi yang tinggi dengan instrumen seperti laser [1] dengan metode Light Detection and Ranging (LIDAR), ultrasonik [2]yang memanfaatkan pemantulan gelombang suara, dan radar [3] yang memanfaatkan pemantulan gelombang radio. Instrumen laser dan radar sulit diaplikasikan pada kendaraan karena dimensi instrumen yang besar, sedangkan ultrasonik memiliki sudut deteksi yang terbatas. ...
Navigasi kendaraan adalah proses pengenalan jalan dan mengarahkan kendaraan pada lintasan yang diinginkan. Penelitian tentang navigasi kendaraan umumnya berfokus pada pengembangan Advanced Driver Assistance System (ADAS) untuk meningkatkan keselamatan dalam berkendaradengan tujuan jangka panjang untuk mewujudkan kendaraan otonom. Pada umumnya navigasi kendaraan dilakukan dengan menggunakan banyak jenis instrumen pengukuran yang berukuran besar dan sulit diaplikasikan pada kendaraan secara umum. Penelitian ini dilakukan untuk menguji ADAS dengan menggunakan instrumen sederhana dan mudah untuk dipasang pada kendaraan. Navigasi dimulai dengan proses deteksi sisi jalan dengan mengamati area jalan pada jarak 10m hingga 14m di depan kendaraan menggunakan teknik pengolahan citra. Hasil deteksi sisi jalan digunakan untuk menghasilkan rekomendasi arah gerak kendaraan yang diubah ke dalam bentuk rekomendasi putaran kemudi bagi pengemudi. Rekomendasi arah gerak kendaraan diperoleh melalui perhitungan sudut yang dibentuk oleh kendaraan terhadap titik tengah lajur jalan pada jarak yang telah ditentukan. Pengujian dilakukan secara real-time dengan menggunakan sebuah Embedded PCdapat mencapai waktu pengolahan citra 13,962 ms dengan tingkat keberhasilan deteksi jalan sebesar 89,7% dan estimasi tingkat kesesuaian data rekomendasi putaran kemudi sebesar 91,04% yang dibandingkan terhadap putaran kemudi oleh pengemudi
... A model will be made for the estimation of the displacements through the accelerations taken as in [10,20,21]. The results obtained will be compared to the values acquired by the wire and low-cost ultrasonic sensors [22]. The incorporation of the OBDII communication between the ADAQ and the vehicle will be studied [23,24]. ...
... Sensors 2018, 18, x 18 of 20 through the accelerations taken as in [10,20,21]. The results obtained will be compared to the values acquired by the wire and low-cost ultrasonic sensors [22]. The incorporation of the OBDII communication between the ADAQ and the vehicle will be studied [23,24]. ...
This project addresses the need for the implementation of low-cost acquisition technology in the field of vehicle engineering: the design, development, manufacture, and verification of a low-cost Arduino-based data acquisition platform to be used in <80 Hz data acquisition in vehicle dynamics, using low-cost accelerometers. In addition to this, a comparative study is carried out of professional vibration acquisition technologies and low-cost systems, obtaining optimum results for low-and medium-frequency operations with an error of 2.19% on road tests. It is therefore concluded that these technologies are applicable to the automobile industry, thereby allowing the project costs to be reduced and thus facilitating access to this kind of research that requires limited resources.
... As there are hundreds of thousands kilometers of highways, it is not easy to monitor all vehicles at any time. Traditional TRV detection methods include: ultrasound based systems [3,[7][8][9], capacitive sensor based systems [10], infrared sensors [11], laser and radar sensors [12], traffic video based systems [13], computer vision techniques [2,14], RFID technology [15], etc. The former vehicle detection sensors or monitoring cameras were always installed along the highway in fixed positions [16], there might be problems associated with this kind of measurement placement such as: (a) in tunnels or on multiple lane sections of the highways, where sensors might detect vehicles erroneously due to the reception of unnecessary reflected signals; (b) although thousands of sensors have been adopted, they still cannot cover all spots of the highways. ...
... After a careful survey and detailed feasibility analysis on different sensor types above, we choose ultrasonic sensors in this study. Ultrasonic sensors have been widely used in ITS and VANET area applications such as vehicle tracking and classification [7,[22][23][24][25], obstacle detection and mapmaking [26,27], vacant parking slot detection [28], smart traffic signaling [29], ultrasonic ranging and localization [30], etc. Ultrasonic sensors are a well accepted technology for distance sensing applications, because of the inexpensive and easy-to-adopt nature, and reliable and stable measurement performance within their measuring range. Figure 1 shows that a vehicle is driving in the passing lane while three other cars are driving on the carriageway. ...
With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%.
