title: A novel vehicle stationary detection utilizing map matching and IMU sensors.
abstract: 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.
authors.affiliation: Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia.
authors.forename: Md Syedul
authors.identifier: 0000-0002-5630-069X
authors.initials: MS
authors.lastname: Amin
authors.affiliation: Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia.
authors.forename: Mamun Bin Ibne
authors.initials: MB
authors.lastname: Reaz
authors.affiliation: Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia.
authors.forename: Salwa Sheikh
authors.initials: SS
authors.lastname: Nasir
authors.affiliation: Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia.
authors.forename: Mohammad Arif Sobhan
authors.initials: MA
authors.lastname: Bhuiyan
authors.affiliation: Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia.
authors.forename: Mohd Alauddin Mohd
authors.initials: MA
authors.lastname: Ali
mesh_terms: D000465:Algorithms; D040362:Geographic Information Systems / Q000592:standards*; D055617:Micro-Electrical-Mechanical Systems / Q000379:methods / Q000592:standards*; D008962:Models, Theoretical; D018986:Motor Vehicles; D015203:Reproducibility of Results; D018511:Systems Integration