Rash Driving Detection Through Data Analytics

Authors

  • Agrawal A Data Analysts, Delhi NCR, India
  • Gupta I Data Analysts, Delhi NCR, India

Keywords:

Classification, rash driving analysis, on board diagnostic, driver profiling, hierarchical clustering, principal component, analysis, support vector machine

Abstract

This paper proposes ananalytical solution for binary classification of driving behaviourinto safe or rash.A methodology is designed and developed which consists of cleaning and scrubbing of raw driving data throughidentification of best set of parameters, iterative cluster-analysis, creation of target variables by benchmarking against theoretical relations and eventually performing supervised regression using support vector machine on the prepared dataset to classify a fresh driving data point into safe or rash driving. A bad and careless driving is depicted as ‘rash driving’ while a good and efficient driving is depicted as ‘safe driving’. The proposed methodology has the potential of applying to real-world driver profiling system.

References

[1] Miyaji, M., Danno, M., Oguri, K.,“Analysis of driver behaviour based on traffic incidents for driver monitor systems”, In Intelligent Vehicles Symposium, IEEE(2008) pp. 930-935.

[2] Liang, J., Cheng, X., Chen, X.,“The research of car rear-end warning model based on mas and behavior”, In: Power Electronics and Intelligent Transportation System, IEEE (2008), pp. 305-309.

[3] Chen, S., Pan, J. and Lu, K. (2018),“Driving Behaviour Analysis Based on Vehicle OBD Information and AdaBoost Algorithms”, [online] Iaeng.org.

[4] "E/E Diagnostic Test Modes". Vehicle E E System Diagnostic Standards Committee. J1979. SAE International. 2017-02-16. doi:10.4271/J1979_201702.

[5] "Digital Annex of E/E Diagnostic Test Modes". Vehicle E E System Diagnostic Standards Committee. J1979-DA. SAE International. 2017-02-16. doi: 10.4271/J1979DA_201702.

[6] Enrique, et al. “PCA - Principal Component Analysis Essentials.” Correlation Matrix : A Quick Start Guide to Analyze, Format and Visualize a Correlation Matrix Using R Software - Easy Guides - Wiki - STHDA, 23 Sept. 2017.

[7] Barreto, Cephas. “OBD-II Datasets.” RSNA Pneumonia Detection Challenge | Kaggle, 21 Aug. 2018, www.kaggle.com/cephasax/obdii-ds3

[8] "Hierarchical Clustering", Saedsayad.com, 2018. [Online] Available:https://www.saedsayad.com/clustering_hierarchical.htm

[9] Khedkar, Sujata et al, "driver evaluation system using mobile phone and OBD-II system", In International Journal of Computer Science and Information Technologies (IJCSIT) 2018, Vol. 6 (3), 2015, 2738-2745

[10] Cortes, C., &Vapnik, V. (1995). Support-vector networks. Machine learning, Vol. 20(3), 273-297.

[11] Prabhu, M., Deorukhakar, D., Amberkar, S., & Ambre, K. (2016), “A Review on Rash Driving Detection and Alert System”, In IOSR Journal of Computer Engineering (IOSR-JCE), Conf. 16051, e-ISSN: 2278-0661, p-ISSN: 2278-8727 pp. 47-49

[12] Dixit, S., Thomas, P., & Agarwal, C. (2016).“A Cloud-based Driver Monitoring for Inefficient Driving Behavior using OBD2 Telematics”. In International Journal of Computer Applications (0975 – 8887) Vol. 153, Issue. 9, November 2016

[13] Lakhe, A., Patel, C., Raut, H., &Shinde, S. (2017),“Smart Phone based Rash Driving Detection”. In International Journal of Innovations & Advancement in Computer Science (IJIACS) ISSN 2347 – 8616, Vol. 6, Issue. 11, November 2017

[14] Patel, L., Gaurav, K., & V, D. (2018), “Detection of rash driving on highways”,In International Journal of Engineering Development and Research (IJEDR), Vol. 6, Issue. 3, ISSN: 2321-9939

[15] Juneja, P. (2019),Reinforcement Theory of Motivation, Retrieved from https://www.managementstudyguide.com/reinforcement-theory-motivation.htm

[16] Zhao, Y., Karypis, G., & Fayyad, U. (2005). Hierarchical clustering algorithms for document datasets. Data mining and knowledge discovery, 10(2), 141-168.

[17] Iwavesystems.com. (2019). OBD II Connected Car Device | iWave Systems. [online] Available at: https://www.iwavesystems.com/obd-ii-connected-car-device.html

[18] Hareendran (2017). Hands-on review: When hacking an OBD-II adapter, choose carefully. [online] Electronic Products. Available at: https://www.electronicproducts.com/Interconnections/Wire_and_Cable/Hands_on_review_When_hacking_an_OBD_II_adapter_choose_carefully.aspx [Accessed 24 Jan. 2019]

Downloads

Published

2025-11-25

How to Cite

[1]
A. Agrawal and I. Gupta, “Rash Driving Detection Through Data Analytics”, Int. J. Comp. Sci. Eng., vol. 7, no. 7, pp. 37–43, Nov. 2025.

Issue

Vol. 7 No. 7 (2019): IJCSE Special Issue Mar Edition

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.