Shortcomings of Ultrasonic Obstacle Detection for Vehicle Driver Assistance and Profiling

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Author(s)

James I. Obuhuma 1,* Henry O. Okoyo 2 Sylvester O. McOyowo 2

1. Department of Computer & Information Technology, Africa Nazarene University, Nairobi, Kenya

2. School of Computing and Informatics, Maseno University, Private Bag, Maseno, Kenya

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2019.06.04

Received: 9 Jan. 2019 / Revised: 27 Mar. 2019 / Accepted: 19 May 2019 / Published: 8 Jun. 2019

Index Terms

Obstacle Detection, Driver Profiling, Ultrasound, Ultrasonic Sensors, Bayesian Network, 2TBN, Sensor Fusion, Driver Assistance

Abstract

Obstacle detection is a challenging problem that has attracted much attention recently, especially in the context of research in self-driving car technologies. A number of obstacle detection technologies exist. Ultrasound is among the commonly used technologies due to its low cost compared to other technologies. This paper presents some findings on the research that has been carried out by the authors with regard to vehicle driver assistance and profiling. It discusses an experiment for detection of obstacles in a vehicle driver’s operational environment using ultrasound technology. Experiment results clearly depict the capabilities and limitations of ultrasound technology in detection of obstacles under motion and obstacles with varied surfaces. Ultrasound’s wavelength, beam width, directionality among others are put into consideration. Pros and cons of other technologies that could replace ultrasound, for instance RADAR and LIDAR technologies are also discussed. The study recommends sensor fusion where several types of sensor technologies are combined to complement one another. The study was a technical test of configurable technology that could guide future studies on obstacle detection intending to use infrared, sound, radio or laser technologies particularly when both the sensor and obstacle are in motion and when obstacles have differing unpredictable surface properties.

Cite This Paper

James I. Obuhuma, Henry O. Okoyo, Sylvester O. McOyowo, "Shortcomings of Ultrasonic Obstacle Detection for Vehicle Driver Assistance and Profiling", International Journal of Information Technology and Computer Science(IJITCS), Vol.11, No.6, pp.28-36, 2019. DOI:10.5815/ijitcs.2019.06.04

Reference

[1]J. I. Obuhuma, H. O. Okoyo, and S. O. Mcoyowo, “Real-time Driver Advisory Model: Intelligent Transportation Systems,” in IST-Africa 2018 Conference Proceedings, IEEE Xplore, 2018.

[2]J. I. Obuhuma, H. O. Okoyo, and S. O. Mcoyowo, “Driver Behaviour Profiling Using Dynamic Bayesian Network,” MECSJ. Mod. Educ. Comput. Sci., vol. 7, pp. 50–59, 2018.

[3]J. Borenstein and Y. Koren, “Real-time obstacle avoidance for fast mobile robots,” IEEE Trans. Syst. Man. Cybern., vol. 19, no. 5, pp. 1179–1187, Sep. 1989.

[4]S. Walter, “The sonar ring: Obstacle detection for a mobile robot,” in Proceedings. 1987 IEEE International Conference on Robotics and Automation, vol. 4, pp. 1574–1579.

[5]J. Borenstein and Y. Koren, “Obstacle avoidance with ultrasonic sensors,” IEEE J. Robot. Autom., vol. 4, no. 2, pp. 213–218, Apr. 1988.

[6]N. Gageik, P. Benz, and S. Montenegro, “Obstacle Detection and Collision Avoidance for a UAV With Complementary Low-Cost Sensors,” IEEE Access, vol. 3, pp. 599–609, 2015.

[7]M. Upton and M. Upton, “Techniques for Distance Measurement,” vol. 104, no. 1995, pp. 2023–2029, 2018.

[8]B. Mustapha, A. Zayegh, and R. K. Begg, “Ultrasonic and Infrared Sensors Performance in a Wireless Obstacle Detection System,” in 2013 1st International Conference on Artificial Intelligence, Modelling and Simulation, 2013, pp. 487–492.

[9]D. Holz, M. Nieuwenhuisen, … D. D.-I. A. P., and U. 2013, “Towards multimodal omnidirectional obstacle detection for autonomous unmanned aerial vehicles,” academia.edu.

[10]L. Scalise et al., “Experimental Investigation of Electromagnetic Obstacle Detection for Visually Impaired Users: A Comparison With Ultrasonic Sensing,” IEEE Trans. Instrum. Meas., vol. 61, no. 11, pp. 3047–3057, Nov. 2012.

[11]M. Bousbia-Salah, A. Redjati, M. Fezari, and M. Bettayeb, “An Ultrasonic Navigation System for Blind People,” in 2007 IEEE International Conference on Signal Processing and Communications, 2007, pp. 1003–1006.

[12]D. Dakopoulos and N. G. Bourbakis, “Wearable Obstacle Avoidance Electronic Travel Aids for Blind: A Survey,” IEEE Trans. Syst. Man, Cybern. Part C (Applications Rev., vol. 40, no. 1, pp. 25–35, Jan. 2010.

[13]W. C. S. S. Simoes and V. F. de Lucena, “Blind user wearable audio assistance for indoor navigation based on visual markers and ultrasonic obstacle detection,” in 2016 IEEE International Conference on Consumer Electronics (ICCE), 2016, pp. 60–63.

[14]M. R. Strakowski, B. B. Kosmowski, R. Kowalik, and P. Wierzba, “An ultrasonic obstacle detector based on phase beamforming principles,” IEEE Sens. J., vol. 6, no. 1, pp. 179–186, Feb. 2006.

[15]X. Zheng, S. Wang, and Y. Zhang, “The Obstacle Detection and Measurement Based on Machine Vision,” MECSJ. Intell. Syst. Appl., vol. 2, pp. 17–24, 2010.

[16]V. R. Shah, S. V Maru, and R. H. Jhaveri, “An Obstacle Detection Scheme for Vehicles in an Intelligent Transportation System,” MECSJ. Comput. Netw. Inf. Secur., vol. 10, pp. 23–28, 2016.

[17]Y. Singh and L. Kaur, “Obstacle Detection Techniques in Outdoor Envi-ronment: Process, Study and Analysis,” MECSJ. Image, Graph. Signal Process., vol. 5, pp. 35–53, 2017.

[18]M. Bansode, S. Jadhav, and A. Kashyap, “Voice Recognition and Voice Navigation for Blind using GPS,” Int. J. Innov., 2015.

[19]J. Sarik and I. Kymissis, “Lab kits using the Arduino prototyping platform,” 2010 IEEE Front. Educ., 2010.

[20]S. Tarapiah, S. Atalla, and B. Alsayid, “Smart on-board transportation management system Geo-Casting featured,” Comput. Appl., 2014.

[21]C. Galeriu, “An Arduino-controlled photogate,” Phys. Teach., 2013.

[22]M. Ulaganathan and C. Saravanan, “Cost-effective Perturb and Observe MPPT Method using Arduino Microcontroller for a Standalone Photo Voltaic System,” Int. J., 2014.

[23]J. Obuhuma and C. Moturi, “Use of GPS with road mapping for traffic analysis,” Int. J. Sci. Technol., 2012.

[24]W. Ulke, R. Adomat, K. Butscher, and W. Lauer, “Radar Based Automotive Obstacle Detection System,” 1994.