Abstract
Some of the critical features of Advanced Driver Assistance Systems (ADAS), including unintentional lane departure warning, and erratic driving warning have significant potential to reduce crashes. Generally, these systems use either various image processing techniques or Global Positioning System (GPS) technology with lane-level resolution maps. However, these are expensive to implement as well as have some limitations, such as harsh weather or irregular lane markings can drastically reduce their performance. Previously, we proposed a lane departure detection system where we generated road reference heading (RRH) form a vehicle’s past trajectories acquired by GPS to detect unintentional lane departure with high accuracy. Now, we propose a technique to detect erratic driving behavior of a vehicle so that the system can issue timely warnings to alert the driver. We have considered two most common erratic driving scenarios; inter lane change and intra lane change erratic driving. We have developed an algorithm to detect both of these erratic behaviors and implemented the algorithm in a prototype system. We have extensively tested the algorithm in the field for a variety of erratic driving scenarios in real-time. Our field test results show that each time an erratic driving scenario occurs; our algorithm correctly detects it and issues a warning to alert the driver.
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
Similar content being viewed by others
References
Maag, C., Muhlbacher, D., Mark, C., Kruger, H.P.: Studying effects of advanced driver assistance systems (ADAS) on individual and group level using multi-driver simulation. IEEE Intell. Transp. Syst. Mag. 4(3), 45–54 (2012)
Federal Highway Administration: FHWA Roadway Departure Strategic Plan, Washington, DC, March 2013
Salvucci, D.D.: Inferring driver intent: a case study in lane-change detection. In: Proceedings Human Factors Ergonomics Society 48th Annual Meeting, New Orleans, LA, pp. 2228–2231 (2004)
Kuge, N., Yamamura, T., Shimoyama, O.: A driver behavior recognition method based on a driver model framework. Society of Automotive Engineers, Warrendale (1998)
McCall, J., Trivedi, M.M.: Visual context capture and analysis for driver attention monitoring. In: Proceedings IEEE Conference Intelligent Transportation Systems, Washington, DC, pp. 332–337, October 2004
Heimes, F., Nagel, H.-H.: Towards active machine-vision-based driver assistance for urban areas. Int. J. Comput. Vis. 50(1), 5–34 (2002)
Sun, R., Ochieng, W.Y., Feng, S.: An integrated solution for lane level irregular driving detection. Transp. Res. Part C: Emerg. Technol. 56, 61–79 (2015)
Quintero, G.C.M., López, J.A.O., Rúa, J.M.P.: Intelligent erratic driving diagnosis based on artificial neural networks. In: 2010 IEEE ANDESCON, pp. 1–6 (2010). https://doi.org/10.1109/ANDESCON.2010.5631576
Chang, T., Hsu, C., Wang, C., Yang, L.: Onboard measurement and warning module for irregular vehicle behavior. In: IEEE Transactions on Intelligent Transportation Systems, vol. 9, no. 3, pp. 501–513, September 2008. https://doi.org/10.1109/TITS.2008.928243
Imkamon, T., Saensom, P., Tangamchit, P., Pongpaibool, P.: Detection of hazardous driving behavior using fuzzy logic. In: 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, pp. 657–660 (2008). https://doi.org/10.1109/ECTICON.2008.4600519
Saruwatari, K., Sakaue, F., Sato, J.: Detection of abnormal driving using multiple view geometry in space-time. In: 2012 IEEE Intelligent Vehicles Symposium, pp. 1102–1107 (2012). https://doi.org/10.1109/IVS.2012.6232189
Jung, C.R., Kelber, C.R.: A lane departure warning system using lateral offset with uncalibrated camera. In: Proceedings. 2005 IEEE Intelligent Transportation Systems 2005, pp. 102–107 (2005)
Jung, C.R., Kelber, C.R.: A lane departure warning system based on a linear-parabolic lane model. In: IEEE Intelligent Vehicles Symposium 2004, pp. 891–895 (2004)
Lin, Q., Han, Y., Hahn, H.: Real-time lane departure detection based on extended edge-linking algorithm. In: 2010 Second International Conference on Computer Research and Development, Kuala Lumpur, pp. 725–730 (2010)
Clanton, J.M., Bevly, D.M., Hodel, A.S.: A low-cost solution for an integrated multisensor lane departure warning system. IEEE Trans. Intell. Transp. Syst. 10(1), 47–59 (2009)
Chowdhury, S., Hossain, Md.T., Hayee, M.I.: Generation of road reference heading using GPS trajectories for accurate lane departure detection. In: VEHITS (2021)
Veness, C.: Calculate distance and bearing between two Latitude/Longitude points using Haversine formula in JavaScript. Movable Type Scripts (2011)
Faizan, M., Hussain, S., Hayee, M.I.: Design and development of in-vehicle lane departure warning system using standard GPS Receiver. Transp. Res. Rec. J. Transp. Res. Board, 1–9 (2019)
Finnegan, P., Green, P.: The time to change lanes: a literature review (1990)
Cao, X., Young, W., Sarvi, M.: Exploring duration of lane change execution. In: Australasian Transport Research Forum 2013 Proceedings, 2–4 October 2013, Brisbane, Australia (2013)
Fazio, J., Michaels, R.M., Reilly, W.R., Schoen, J., Poulis, A.: Behavioral model of freeway exiting, Transp. Res. Rec. 1281 (1990)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Hossain, M.T., Chowdhury, S., Hayee, M.I. (2022). An In-Vehicle Erratic Driving Detection and Warning System Using GPS Technology. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2021, Volume 1. FTC 2021. Lecture Notes in Networks and Systems, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-030-89906-6_29
Download citation
DOI: https://doi.org/10.1007/978-3-030-89906-6_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-89905-9
Online ISBN: 978-3-030-89906-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)