A Novel Vehicle Stationary Detection Utilizing Map Matching and IMU Sensors

Amin, Md. Syedul; Reaz, Mamun Bin Ibne; Nasir, Salwa Sheikh; Bhuiyan, Mohammad Arif Sobhan; Ali, Mohd

doi:10.1155/2014/597180

Cited by 8 publications

(4 citation statements)

References 26 publications

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“…Indirectly with the combination of vehicle counting and machine learning approach as well as the sensor installing as a part of the vehicles detect crashes. [82][83][84] This approach uses simple statistical models for analysis electrical signal generated from the mechanical pressure. [85] Not found publication articles on using this sensor as a solution to this problem at this moment.…”

Section: Piezoelectric Sensormentioning

confidence: 99%

Review of IoT Sensor Systems Used for Monitoring the Road Infrastructure

Micko

Papcun

Zolotová

2023

Sensors

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An intelligent transportation system is one of the fundamental goals of the smart city concept. The Internet of Things (IoT) concept is a basic instrument to digitalize and automatize the process in the intelligent transportation system. Digitalization via the IoT concept enables the automatic collection of data usable for management in the transportation system. The IoT concept includes a system of sensors, actuators, control units and computational distribution among the edge, fog and cloud layers. The study proposes a taxonomy of sensors used for monitoring tasks based on motion detection and object tracking in intelligent transportation system tasks. The sensor’s taxonomy helps to categorize the sensors based on working principles, installation or maintenance methods and other categories. The sensor’s categorization enables us to compare the effectiveness of each sensor’s system. Monitoring tasks are analyzed, categorized, and solved in intelligent transportation systems based on a literature review and focusing on motion detection and object tracking methods. A literature survey of sensor systems used for monitoring tasks in the intelligent transportation system was performed according to sensor and monitoring task categorization. In this review, we analyzed the achieved results to measure, sense, or classify events in intelligent transportation system monitoring tasks. The review conclusions were used to propose an architecture of the universal sensor system for common monitoring tasks based on motion detection and object tracking methods in intelligent transportation tasks. The proposed architecture was built and tested for the first experimental results in the case study scenario. Finally, we propose methods that could significantly improve the results in the following research.

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Section: Piezoelectric Sensormentioning

confidence: 99%

Review of IoT Sensor Systems Used for Monitoring the Road Infrastructure

Micko

Papcun

Zolotová

2023

Sensors

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“…In this study; due to the features of small size, low power consumption, low cost, high data transfer rate, high sensitivity, high resolution and low noise ratio in the Cartesian coordinate system, which can give 3dimensional numerical output, produced by Analogue Device, MEMS-based semiconductor The accelerometer ADXL345 is preferred. The ADXL345 accelerometer has become very popular in recent years and is widely used in many different applications [7][8][9][10][11][12][13]. Figure 1 shows the block structure of ADXL345 [14].…”

Section: 1acceleration and Accelerometermentioning

confidence: 99%

Development of Driver Analysis System to Improve Driving Comfort and to Reduce Mechanical Abrasion in Vehicles

Böğrek

Sümbül

2019

Teknik Bilimler Dergisi

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The purpose of this study is; to develop a system that can detect road disturbances and can warn the driver. For this purpose, a measurement method which tracking as a 3-axis of the road situation with a semiconductor MEMS-based accelerometer has been developed to be used to detect vehicle vibration and drive conditions which has a serious effect on the driving quality of the road. With the developed measuring system, road wear and tear can be successfully reported. Thanks to the improved system, the driver can also be warned by detecting vehicle suspension damage. In addition, a driver performance report may be drawn up under the project that is very important for fleet and service owners (universities, municipalities and other similar public and corporate entities). Thus, the damage caused by the bad use of the vehicles can be reduced to the minimum; the operating costs can be reduced.

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“…Both velocity and angular velocity were suggested to be compared with a specified threshold, while the standard deviation (STD) was proposed to calculate the vehicle acceleration in a sliding window and was used to compare it with the threshold deduced from the stationary data [6,15]. An attitude heading reference system was put forward to detect the stationary states with acceleration data, which achieved an 87% correction rate in a vehicular test [17,18]. A neural network was also trained to use velocity and IMU measurements for stationary detection in GNSS outages [16,19].…”

Section: Introductionmentioning

confidence: 99%

Stationary Detection for Zero Velocity Update of IMU Based on the Vibrational FFT Feature of Land Vehicle

Li,

Nie,

Suvorkin

et al. 2024

Remote Sensing

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The inertial navigation system (INS) and global satellite navigation system (GNSS) are two of the most significant systems for land navigation applications. The inertial measurement unit (IMU) is a kind of INS sensor that measures three-dimensional acceleration and angular velocity measurements. IMUs based on micro-electromechanical systems (MEMSs) are widely employed in vehicular navigation thanks to their low cost and small size, but their magnitude and noisy biases make navigation errors diverge very fast without external constraint. The zero-velocity update (ZVU) function is one of the efficient functions that constrain the divergence of IMUs for a stopped vehicle, and the key of the ZVU is the correct stationary detection for the vehicle. When a land vehicle is stopped, the idling engine produces a very stable vibration, which allows us to perform frequency analysis and a comparison based on the fast Fourier transform (FFT) and IMU measurements. Hence, we propose a stationary detection method based on the FFT for a stopped land vehicle with an idling engine in this study. An urban vehicular navigation experiment was carried out with our GNSS/IMU integration platform. Three stops for 10 to 20 min were set to analyze, generate and evaluate the FFT-based stationary detection method. The FFT spectra showed clearly idling vibrational peaks during the three stop periods. Through the comparison of FFT spectral features with decelerating and accelerating periods, the amplitudes of vibrational peaks were put forward as the key factors of stationary detection. For the consecutive stationary detection in the GNSS/IMU integration process, a three-second sliding window with a one-second updating rate of the FFT was applied to check the amplitudes of peaks. For the assessment of the proposed stationary detection method, GNSS observations were removed to simulate outages during the three stop periods, and the proposed detection method was conducted together with the ZVU. The results showed that the proposed method achieved a 99.7% correct detection rate, and the divergence of the positioning error constrained via the ZVU was within 2 cm for the experimental stop periods, which indicates the effectiveness of the proposed method.

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A Novel Vehicle Stationary Detection Utilizing Map Matching and IMU Sensors

Cited by 8 publications

References 26 publications

Review of IoT Sensor Systems Used for Monitoring the Road Infrastructure

Review of IoT Sensor Systems Used for Monitoring the Road Infrastructure

Development of Driver Analysis System to Improve Driving Comfort and to Reduce Mechanical Abrasion in Vehicles

Stationary Detection for Zero Velocity Update of IMU Based on the Vibrational FFT Feature of Land Vehicle

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