Abstract
One of the major challenges on highways is to avoid an unintended departure from the lane. This paper proposes a lane departure warning system with the help of monocular vision. The efficiency of such a system is subject to clarity of lanes, weather conditions and also method of acquisition. This paper proposes a method of lane detection that is robust to stray edges within the frame. Canny edge detection is utilized on the pre-processed images to obtain maximal intensity edges, followed by lane detection using Hough transform. In this paper we try to utilize selective property of the edges obtained from canny edge detection to reduce noisy edges and improve the false positive rate. The system has been tested to be effective in fully illuminated as well as badly illuminated road conditions with satisfactory results. The average detection rate obtained is 95%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lotfy, O.G., et al.: Lane departure warning tracking system based on score mechanism. In: Midwest Symposium Circuits Systems, October, pp. 16–19 (2017)
Kortli, Y., Marzougui, M., Atri, M.: Efficient implementation of a real-time lane departure warning system. In: 2016 International Image Processing, Application System, pp. 1–6 (2016)
Son, J., Yoo, H., Kim, S., Sohn, K.: Real-time illumination invariant lane detection for lane departure warning system. Expert Syst. Appl. 42(4), 1816–1824 (2015)
Gaikwad, V., Lokhande, S.: Lane departure identification for advanced driver assistance. IEEE Trans. Intell. Transp. Syst. 16(2), 910–918 (2015)
Dai, J., Wu, L., Lin, H., Tai, W.: A driving assistance system with vision based vehicle detection techniques
Li, Q., Chen, L., Li, M., Shaw, S.L., Nüchter, A.: A sensor-fusion drivable-region and lane-detection system for autonomous vehicle navigation in challenging road scenarios. IEEE Trans. Veh. Technol. 63(2), 540–555 (2014)
Gurghian, A., Koduri, T., Bailur, S.V., Carey, K.J., Murali, V.N.: DeepLanes: end-to-end lane position estimation using deep neural networks. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 38–45 (2016)
Murugesh, R., Ramanadhan, U., Vasudevan, N., Devassy, A., Krishnaswamy, D., Ramachandran, A.: Smartphone based driver assistance system for coordinated lane change. In: 2015 International Conference on Connected Vehicles and Expo, ICCVE 2015 - Proceedings, pp. 385–386 (2016)
Jayanth Balaji, A., Harish Ram, D.S., Nair, B.B.: Machine learning approaches to electricity consumption forecasting in automated metering infrastructure (AMI) systems: an empirical study. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds.) CSOC 2017. AISC, vol. 574, pp. 254–263. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-57264-2_26
Nair, B.B., Kumar, P.K.S., Sakthivel, N.R., Vipin, U.: Clustering stock price time series data to generate stock trading recommendations: an empirical study. Expert Syst. Appl. 70, 20–36 (2017)
Singh, A.K., John, B.P., Subramanian, S.V., Kumar, A.S., Nair, B.B.: A low-cost wearable Indian sign language interpretation system. In: International Conference on Robotics & Automation for Humanitarian Applications (2016)
John, A.A., Nair, B.B., Kumar, P.N.: Application of clustering techniques for video summarization – an empirical study. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds.) CSOC 2017. AISC, vol. 573, pp. 494–506. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-57261-1_49
Wang, J.G., Lin, C.J., Chen, S.M.: Applying fuzzy method to vision-based lane detection and departure warning system. Expert Syst. Appl. 37(1), 113–126 (2010)
Duda, R.O., Hart, P.E.: Use of the Hough transform to detect lines and cures in pictures. Commun. Assoc. Comput. Mach. 15(1), 11–15 (1972)
Wu, T., Ranganathan, A.: A practical system for road marking detection and recognition. In: IEEE Intelligent Vehicles Symposium Proceedings, pp. 25–30 (2012)
Aly, M.: Real time detection of lane markers in urban streets. In: IEEE Intelligent Vehicles Symposium, pp. 7–12 (2008)
Wikipedia Contributors: Traffic Collisions in India. Wikipedia, The Free Encyclopedia, 25 July 2017. Accessed 26 Dec 2017
Times of India. Lane Cutting Speeding Big Killers on Stretch in 2016. In timesofindia.indiatimes.com, 17 December 2017
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vats, A., Nair, B.B. (2019). An Improved Driver Assistance System for Detection of Lane Departure Under Urban and Highway Driving Conditions. In: Minz, S., Karmakar, S., Kharb, L. (eds) Information, Communication and Computing Technology. ICICCT 2018. Communications in Computer and Information Science, vol 835. Springer, Singapore. https://doi.org/10.1007/978-981-13-5992-7_3
Download citation
DOI: https://doi.org/10.1007/978-981-13-5992-7_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-5991-0
Online ISBN: 978-981-13-5992-7
eBook Packages: Computer ScienceComputer Science (R0)