Sensor-based Target Location Technology in Intelligent Transport Systems
DOI:
https://doi.org/10.54097/13y8ra77Keywords:
Intelligent Transport System (ITS), Laser sensors, infrared sensors, ultrasonic sensors, sensor fusion.Abstract
This paper explores the critical role of sensor-based targeting in Intelligent Transport Systems (ITS). The rapid growth of vehicles put forward challenges to congestion and emissions, and most contraries’ departments use ITS to solve the problem. The key to ITS is positioning the traffic participants precisely to collect the necessary data for the system operation. This study provides a review of previous research on sensor-based target localization and its importance in ITS. It discusses various sensors suitable for ITS applications, detailing their functionality and contribution to system efficiency, accuracy, and safety. In addition, this paper designs an experimental case that provides a deeper analysis of these sensors. This experiment tries to use minimum mean squared error and Kalman filtering to reduce error. The results of the study show that methods similar to minimum mean squared error and Kalman filtering can reduce the error effectively. This research contributes to understanding the use of sensors in ITS, digging their potential to revolutionize modern transport systems.
Downloads
References
J. Dargay, D. Gately, and M. Sommer, ‘Vehicle Ownership and Income Growth, Worldwide: 1960-2030’, Energy J., vol. 28, no. 4, Oct. 2007, doi: 10.5547/ISSN0195-6574-EJ-Vol28-No4-7.
L. E. Y. (Luz E. Y. Mimbela and L. A. Klein, Summary of vehicle detection and surveillance technologies used in intelligent transportation systems. Washington, DC: Federal Highway Administration, Intelligent Transportation Systems Joint Program Office, 2000.
Sikder Sunbeam Islam, K. Dey, Mohammed Rafiqul Islam, and Mohammad Kurshed Alam, ‘An infrared based intelligent Traffic System’, in 2012 International Conference on Informatics, Electronics & Vision (ICIEV), Dhaka, Bangladesh: IEEE, May 2012, pp. 57–60. Doi: 10.1109/ICIEV.2012.6317334.
R. Stahn, G. Heiserich, and A. Stopp, ‘Laser Scanner-Based Navigation for Commercial Vehicles’, in 2007 IEEE Intelligent Vehicles Symposium, Istanbul, Turkey: IEEE, Jun. 2007, pp. 969–974. doi:
L. Alonso, V. Milanés, C. Torre-Ferrero, J. Godoy, J. P. Oria, and T. De Pedro, ‘Ultrasonic Sensors in Urban Traffic Driving-Aid Systems’, Sensors, vol. 11, no. 1, pp. 661–673, Jan. 2011, doi: 10.3390/s110100661.
M. Kelemen et al., ‘Distance Measurement via Using of Ultrasonic Sensor’, J. Autom. Control.
Y. S. Suh, ‘Laser Sensors for Displacement, Distance and Position’, Sensors, vol. 19, no. 8, p. 1924, Apr. 2019, doi: 10.3390/s19081924.
A. Z. Khalaf and B. H. Alyasery, ‘Laser Distance Sensors Evaluation for Geomatics Researches’, Iraqi J. Sci., pp. 1831–1841, Jul. 2020, doi: 10.24996/ijs.2020.61.7.32.
G. Benet, F. Blanes, J. E. Simó, and P. Pérez, ‘Using infrared sensors for distance measurement in mobile robots’, Robot. Auton. Syst., vol. 40, no. 4, pp. 255–266, Sep. 2002, doi: 10.1016/S0921-8890(02)00271-3.
L. Alonso, V. Milanés, C. Torre-Ferrero, J. Godoy, J. P. Oria, and T. De Pedro, ‘Ultrasonic Sensors in Urban Traffic Driving-Aid Systems’, Sensors, vol. 11, no. 1, pp. 661–673, Jan. 2011, doi: 10.3390/s110100661.
S. Mohottala, S. Ono, M. Kagesawa, and K. Ikeuchi, ‘Fusion of a Camera and a Laser Range Sensor for Vehicle Recognition’, in Machine Vision Beyond Visible Spectrum, R. Hammoud, G. Fan, R. W. McMillan, and K. Ikeuchi, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 141–157. Doi: 10.1007/978-3-642-11568-4_6.
S. A. Ahmed, T. M. Hussain, and T. N. Saadawi, ‘Active and passive infrared sensors for vehicular traffic control’, in Proceedings of IEEE Vehicular Technology Conference (VTC), Stockholm, and Sweden: IEEE, 1994, pp. 1393–1397. Doi: 10.1109/VETEC.1994.345323.
Q. Gan and C. J. Harris, ‘Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion’, IEEE Trans. Aerosp. Electron. Syst., vol. 37, no. 1, pp. 273–279, Jan. 2001, doi: 10.1109/7.913685.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Highlights in Science, Engineering and Technology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
