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    Improving Position-Time Trajectory Accuracy in Vehicle Stop-and-Go Scenarios by Using a Mobile Robot as a Testbed
    (Romanian Soc Control Tech Informatics, 2023) Bakirci, Murat; Cetin, Mecit
    This study sets an example of how mobile robotic vehicles can be used effectively in research on intelligent transportation systems. Especially the stop-and-go mobility seen in heavy traffic conditions was simulated with a mobile robot, and the study is focused on how to obtain distance-time trajectories more accurately under these conditions. System identification tests of the mobile robotic platform, whose kinematic model was developed, were also carried out, and all solutions regarding robot movement were obtained. For the congested traffic simulation, various stop-and-go points are designated on a predetermined straight route segment to mimic behavior of a vehicle in congested traffic. Robot trajectories were obtained under different scenarios by using both GPS data and a kinematic model through the utilization of motor encoders. More accurate and consistent trajectories were achieved by fusing these trajectories with the Extended Kalman Filter. The main contribution of this study is demonstrating how the number of stop-and-go positions can improve the accuracy in estimating the robot/vehicle trajectory. The paper shows how the cumulative error in predicting the trajectories in reduced as the number of stops increases. For example, the trajectory estimated for a scenario involving five stop-and-go points is 94% more accurate than that for the case with a single stop.
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    Reliability of MEMS Accelerometers Embedded in Smart Mobile Devices for Robotics Applications
    (Springer Science and Business Media Deutschland GmbH, 2023) Bakirci, Murat; Cetin, Mecit
    This study focuses on assessing the reliability of data from the accelerometer sensors embedded in smart mobile devices that may potentially be used for robotics and intelligent transportation systems (ITS) applications. It is shown how bias and noise elimination can be executed more consistently from acceleration profiles obtained from an accelerometer with a high amount of error. In cases where accurate acceleration information could not be detected through noise filtering, averaged acceleration values in specific time windows were computed and introduced as measurement values to the filtering algorithm. Thus, more consistent acceleration profiles were obtained through making better state estimations. As an alternative to one dimensional bias elimination process, bias errors were detected in six different orientations in three dimensions and subtracted from raw readings. Furthermore, ratiometricity analysis, which is important in applications that require long-term data collection, but is generally overlooked, was also performed through collecting continuous acceleration data for twelve hours. Ratiometric error was numerically quantified and completely subtracted from the raw data through computation of slopes between specific error regions with linear variation assumption between these regions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Utilization of a Vehicle's On-Board Diagnostics to Reduce GPS-Sourced Positioning Error
    (Institute of Electrical and Electronics Engineers Inc., 2022) Bakirci, Murat; Cetin, Mecit
    Although GPS technology continues to evolve, significant number of transportation applications still require better positioning accuracy. This leads the studies to increase positioning accuracy to progress more intensively. With the widespread use of technologies such as smart mobile devices, especially in Intelligent Transportation Systems, new problems have emerged and therefore new solutions are needed. In this study, errors of positioning data obtained by a GPS sensor embedded in a smart mobile device were tried to be eliminated. For this, precise speed information of the vehicle was obtained through utilization of vehicle's on-board diagnostic, and by using this information, how far the vehicle actually traveled in the measurement ranges was precisely computed. The actual trajectory of the vehicle is obtained by utilizing these actual traveled distances between the measurement points. It was observed that the proposed method was highly successful. © 2022 IEEE.