Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
Reseach Article

A Smart Vehicular Forward Collision Alert System using Neural Network

by Felix Larbi Aryeh, Emmanuel Kweku Eshun, Abdul-Harisu Inusah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 21
Year of Publication: 2021
Authors: Felix Larbi Aryeh, Emmanuel Kweku Eshun, Abdul-Harisu Inusah
10.5120/ijca2021921575

Felix Larbi Aryeh, Emmanuel Kweku Eshun, Abdul-Harisu Inusah . A Smart Vehicular Forward Collision Alert System using Neural Network. International Journal of Computer Applications. 183, 21 ( Aug 2021), 8-17. DOI=10.5120/ijca2021921575

@article{ 10.5120/ijca2021921575,
author = { Felix Larbi Aryeh, Emmanuel Kweku Eshun, Abdul-Harisu Inusah },
title = { A Smart Vehicular Forward Collision Alert System using Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2021 },
volume = { 183 },
number = { 21 },
month = { Aug },
year = { 2021 },
issn = { 0975-8887 },
pages = { 8-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number21/32047-2021921575/ },
doi = { 10.5120/ijca2021921575 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:17:24.437363+05:30
%A Felix Larbi Aryeh
%A Emmanuel Kweku Eshun
%A Abdul-Harisu Inusah
%T A Smart Vehicular Forward Collision Alert System using Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 21
%P 8-17
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Road accidents over the years have led to an increased mortality rate in Ghana. Most accidents are caused by stress, tiredness, and loss of concentration of drivers while driving. This paper sought to design and build an automatic detection forward collision alert system for already existing vehicles in Ghana. Specifically, a deep learning model was built using a convolutional neural network for detection of stationary/moving objects (person, cars, bicycle, truck, bus and others). The object's relative speed to that of the subject vehicle is used to determine the probability of a collision. A buzzing alarm sound occurs when the possibility of collision is higher. The proposed system is an economical technique of alerting drivers of any impending danger on our roads.

References
  1. Alom, M. Z., Taha, T. M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., Hasan, M., Van Essen, B. C., Awwal, A. A. and Asari, V. K. (2019), “A State-of-the-Art Survey on Deep Learning Theory and Architectures”. Electronics, Vol. 8, Issue 3, p. 292.
  2. Anon. (2009), “Transport: Bedrock for Economic Development”, https://www.natcomreport. com/ghana/livre/transport.pdf. Accessed: January 25, 2019.
  3. Anon. (2012), “Neuron”, https://www.simple.wikipedia/wiki/Neuron. Accessed: February 2, 2019.
  4. Anon. (2015), “Piezo Buzzer (Through Hole)”, https://www.inventelectronics.com/product/piezo-buzzer-through-hole. Accessed: February 8, 2019.
  5. Anon. (2016), “Raspberry Pi 3 Model B+”, http://www.raspberrypi.org/products/raspberry-pi-3-model-b+. Accessed: February 3, 2019.
  6. Anon. (2017a), “2017 State Ownership Report”, http://www.mofep.gov.gh/sites/default/files/reports/economic/2017-State-Ownership-Report.pdf. Accessed: February 3, 2019.
  7. Anon. (2017b), “Getting Started with Picamera Module Your Raspberry Pi”, https://www.electrone.com/getting-started-picamera-module. Accessed: February 24, 2019.
  8. Anon. (2018a), “Statistics: Road Safety Overview”, http://www.nrsc.gov.gh/index.php/statistics. Accessed: February 8, 2019.
  9. Anon. (2018b), “Global Status Report on Road Safety 2018”, https://www.who. int/violence_injury_prevention/road_safety_status/2018/en/. Accessed: January 5, 2019.
  10. Arik, S. Ö., Chrzanowski, M., Coates, A., Diamos, G., Gibiansky, A., Kang, Y., Li, X., Miller, J., Ng, A., Raiman, J. and Sengupta, S. (2017), “Deep voice: Real-Time Neural Text-to-Speech”, Proceedings of the 34th International Conference on Machine Learning, Vol. 70, pp. 195 - 204.
  11. Du, K. L. and Swamy, M. N. S. (2014), “Multilayer Perceptrons: Architecture and Error Backpropagation”, Neural Networks and Statistical Learning, pp. 83 - 126.
  12. Everingham, M. and Winn, J. (2011), “The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Development Kit”, Pattern Analysis, Statistical Modelling and Computational Learning, Tech. Rep, pp. 1 – 32.
  13. Girshick, R. (2015), “Fast R-CNN”, IEEE International Conference on Computer Vision, pp. 1440 - 1448.
  14. Girshick, R., Donahue, J., Darrell, T. and Malik, J. (2014), “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation”, IEEE Conference on Computer Vision and Pattern Recognition, pp. 580 - 587.
  15. Horberry, T., Anderson, J., Regan, M. A., Triggs, T. J. and Brown, J. (2006), “Driver Distraction: The Effects of Concurrent in-Vehicle Tasks, Road Environment Complexity and Age on Driving Performance”, Accident Analysis & Prevention, Vol. 38, Issue 1, pp. 185 - 191.
  16. Hulstaert, L. (2019), “A Beginner’s Guide to Object Detection”, Datacamp, p. 1.
  17. Jung, H., Choi, M. K., Soon, K. and Jung, W. Y. (2018), “End-to-End Pedestrian Collision Warning System Based on a Convolutional Neural Network with Semantic Segmentation”, International Conference on Consumer Electronics (ICCE), pp. 1 - 3.
  18. Kusano, K. D. and Gabler, H. C. (2012), “Safety Benefits of Forward Collision Warning, Brake Assist, and Autonomous Braking Systems in Rear-End Collisions”, IEEE Transactions on Intelligent Transportation Systems, Vol. 13, Issue 4, pp.1546 – 1555.
  19. Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C. Y. and Berg, A. C. (2016), “SSD: Single Shot Multibox Detector”, European Conference on Computer Vision, pp. 21 - 37.
  20. O'Shea, K. and Nash, R. (2015), “An Introduction to Convolutional Neural Networks”, pp. 1 – 11.
  21. Park, K. Y. and Hwang, S. Y. (2014), “Robust Range Estimation with a Monocular Camera for Vision-based Forward Collision Warning System”, The Scientific World Journal, pp. 1 – 9.
  22. Raphael, E., Kiefer, R., Reisman, P. and Hayon, G. (2011), “Development of a Camera-Based Forward Collision Alert System, SAE International Journal of Passenger Cars-Mechanical Systems, Vol. 4, pp. 467 - 478.
  23. Redmon, J., Divvala, S., Girshick, R. and Farhadi, A. (2016), “You Only look Once: Unified, Real-Time Object Detection”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779 - 788.
  24. Ren, S., He, K., Girshick, R. and Sun, J. (2015), “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, Advances in Neural Information Processing Systems, pp. 91 - 99.
  25. Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A. and Chen, Y. (2017), “Mastering the Game of Go without Human Knowledge”. Nature, Vol. 550, Issue 7676, p. 354.
  26. Stein, G. P., Ferencz, A. D. and Avni, O. (2012). “Estimating Distance to an Object using a Sequence of Images Recorded by a Monocular Camera”, United States Patent, pp. 1 – 15.
  27. Strayer, D. L., Watson, J. M. and Drews, F. A. (2011), “Cognitive Distraction while Multitasking in the Automobile”, Psychology of Learning and Motivation, Vol. 54, pp. 29 - 58.
  28. Tuohy, S., O'Cualain, D., Jones, E. and Glavin, M. (2010), “Distance Determination for an automobile Environment using Inverse Perspective Mapping in OpenCV”, Irish Signals and Systems Conference, Galway – Ireland, pp. 1 - 8.
  29. Viola, P. and Jones, M. (2001), “Rapid Object Detection using a Boosted Cascade of Simple Features”, Accepted Conference on Computer Vision and Pattern Recognition, Vol. 1, Issue 1, pp. 511 - 518.
Index Terms

Computer Science
Information Sciences

Keywords

You Only Look Once (YOLO) Visual Geometry Group (VGG) Single Shot Multibox Detector (SSD) Advanced Driver Assistance System (ADAS).