Integrated Vehicle Accident Detection and Location System

Amin, Md. Syedul; Reaz, Mamun Bin Ibne; Nasir, Salwa Sheikh

doi:10.12928/telkomnika.v12i1.13

Cited by 6 publications

(2 citation statements)

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“…However, the performance severely degrades or even complete outage occurs in tunnels, in urban areas with skyscrapers, or in parking garages. On the other hand, the INS can provide continuous navigation information with high data rates which does not depend on any external sources like the satellites of the GPS [ 6 ]. But the downside is that the accuracy of the INS largely depends on the quality of the IMU sensors.…”

Section: Introductionmentioning

confidence: 99%

A Novel Vehicle Stationary Detection Utilizing Map Matching and IMU Sensors

Amin

Reaz

Nasir

et al. 2014

The Scientific World Journal

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Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.

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Section: Introductionmentioning

confidence: 99%

A Novel Vehicle Stationary Detection Utilizing Map Matching and IMU Sensors

Amin

Reaz

Nasir

et al. 2014

The Scientific World Journal

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“…It is comprised of the methods and technologies to determine the time varied position, velocity and attitude of a moving body [1][2]. Global Positioning System (GPS) and Inertial Navigation System (INS) are popular navigation devices of the modern days [3].…”

Section: Introductionmentioning

confidence: 99%

Attitude Heading Reference System based vehicle stationary state detection

Amin

Reaz

Nasir

et al. 2014

2014 International Conference on Electrical Engineering and Information &Amp; Communication Technology

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Vehicle navigation is a crucial requirement for many applications. Global Positioning System (GPS) can provide accurate navigation information. But the GPS performance degrades and even a complete outage may occur in urban areas due to line of sight problem. Inertial Navigation System (INS) can provide navigation information during a GPS outage. However, due to bias, drift, noise and other errors, the position information quickly diverges which is more sever for low cost INS. These errors can be corrected in a stationary state. Detecting the stationary state to correct the INS error is crucial for navigation system. This paper proposes a novel stationary detection technique by the threshold approach with an Attitude Heading Reference System (AHRS) built from the Inertial Measurement Unit (IMU) sensors and acceleration information. The stationary state is detected from variance of the acceleration data and the heading of the vehicle. The test result shows that the 87% correct stationary state is detected from both the acceleration and heading information. The stationary state detection can help to correct the INS errors.

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