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Advancements in Integrated Driver Behavior Analysis and Smart Routing Optimization for Enhanced Urban Mobility

by R. Geetha Ramani, Keerthi Kumar E.N., Joseph Samuel M., Kishor S.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 13
Year of Publication: 2024
Authors: R. Geetha Ramani, Keerthi Kumar E.N., Joseph Samuel M., Kishor S.
10.5120/ijca2024923499

R. Geetha Ramani, Keerthi Kumar E.N., Joseph Samuel M., Kishor S. . Advancements in Integrated Driver Behavior Analysis and Smart Routing Optimization for Enhanced Urban Mobility. International Journal of Computer Applications. 186, 13 ( Mar 2024), 19-28. DOI=10.5120/ijca2024923499

@article{ 10.5120/ijca2024923499,
author = { R. Geetha Ramani, Keerthi Kumar E.N., Joseph Samuel M., Kishor S. },
title = { Advancements in Integrated Driver Behavior Analysis and Smart Routing Optimization for Enhanced Urban Mobility },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2024 },
volume = { 186 },
number = { 13 },
month = { Mar },
year = { 2024 },
issn = { 0975-8887 },
pages = { 19-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number13/advancements-in-integrated-driver-behavior-analysis-and-smart-routing-optimization-for-enhanced-urban-mobility/ },
doi = { 10.5120/ijca2024923499 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-03-27T00:44:38.430190+05:30
%A R. Geetha Ramani
%A Keerthi Kumar E.N.
%A Joseph Samuel M.
%A Kishor S.
%T Advancements in Integrated Driver Behavior Analysis and Smart Routing Optimization for Enhanced Urban Mobility
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 13
%P 19-28
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The integration of various methodologies to analyze driver behavior and smart routing algorithms represents a significant advancement in enhancing transportation safety and efficiency. These approaches leverage data-driven insights and sophisticated algorithms to tailor driving assistance systems and navigation experiences to individual users' needs. By utilizing techniques such as LSTM neural networks for driver behavior analysis and intelligent algorithms for smart routing, these advancements contribute to the development of more advanced driver-assistance technologies and dynamic navigation systems. Driver behavior analysis, which aims to understand and predict driving actions, is crucial for enhancing safety through smarter assistance systems. By matching driving patterns with suitable analytical methods, advancements like LSTM neural networks decode intricate driving actions, contributing to the development of advanced driver-assistance technologies for safer driving experiences. Similarly, smart routing employs intelligent algorithms to compute optimal routes in real-time, prioritizing efficiency and precision in navigating diverse urban landscapes. Leveraging sophisticated algorithms and graph theory, smart routing aims to craft dynamic navigation systems that adapt routes in real-time, optimizing efficiency and user-friendliness within specific road networks. This approach offers customized navigation experiences tailored to individual user needs, further enhancing the overall efficiency and safety of urban transportation systems.

References
  1. Othman, W.; Hamoud, B.; Kashevnik, A.; Shilov, N.; Ali, A. Correlation Analysis between Driver Behaviour and Vital Signs: Machine Learning Based Approach and Case Study. Sensors 2023, 23, 7387. https://doi.org/10.3390/s23177387
  2. Li, J., Guo, F., Li, W., Tian, B., Chen, Z.a, Qu, S.a Research on driving behavior characteristics of older drivers based on drivers' behavior graphs analysis (2023) Heliyon, 9 (8), art. no. e18756,.
  3. T. L. L. Mon and T. L. L. Thein, "Analysis of GPS Data Interpolation Methods for Driver's Behavior Detection," 2023 IEEE Conference on Computer Applications (ICCA), Yangon, Myanmar, 2023, pp. 288-293, doi: 10.1109/ICCA51723.2023.10181662.
  4. Zhang, H., Ni, D., Ding, N., Sun, Y., Zhang, Q., Li, X.Structural analysis of driver fatigue behavior: A systematic review(2023) Transportation Research Interdisciplinary Perspectives, 21, art. no. 100865,DOI: 10.1016/j.trip.2023.100865
  5. Wei, H., Li, L., Xu, Y., Lei, S., Wang, Y.Dynamic shimmy behavior and bifurcation analysis of driver-vehicle-road system (2023) Meccanica, 58
  6. Mehdi Cina, Ahmad B. Rad ,Categorized review of drive simulators and driver behavior analysis focusing on ACT-R architecture in autonomous vehicles, Doi:10.1016/j.seta.2023.103044
  7. Heddar Yamina , Djebabra Mébarek , Belkhiri Mohammed , Saaddi Saadia , Contribution to the analysis of driver behavioral deviations leading to road crashes at work, doi:10.1016/j.iatssr.2023.03.003 0386-1112
  8. Tarek Ghoul , Tarek Sayed , Chuanyun Fu, Real-time safest route identification: Examining the trade-off between safest and fastest routes,https://doi.org/10.1016/j.amar.2023.100277
  9. Yi He , Changxin Sun , Fangrong Chang , The road safety and risky behavior analysis of delivery vehicle drivers in China, https://doi.org/10.1016/j.aap.2023.107013
  10. M. Nasr Azadani and A. Boukerche, "Siamese Temporal Convolutional Networks for Driver Identification Using Driver Steering Behavior Analysis," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 10, pp. 18076-18087, Oct. 2022, doi: 10.1109/TITS.2022.3151264.
  11. A. R. Anil and A. J, "Driver behavior analysis using K-means algorithm," 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT), Kannur, India, 2022, pp. 1555-1559, doi: 10.1109/ICICICT54557.2022.9917899.
  12. P. K. K R and S. A M, "Driver Behavior Analysis Using Deep Learning," 2022 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 2022, pp. 1-3, doi: 10.1109/ICCCI54379.2022.9740778.
  13. Smita Jangale, Rutuja Rajhans, Anuja Shetye, Ritik Wadhwani , Location Tracking and Smooth Path Providing System, International Research Journal of Engineering and Technology (IRJET), 9(3). Retrieved from https://www.irjet.net/archives/V9/i3/IRJET-V9I3157.pdf
  14. Lesch, Veronika & König, Maximilian & Kounev, Samuel & Stein, Anthony & Krupitzer, Christian. (2021). A Case Study of Vehicle Route Optimization.
  15. J. Tomić, N. Gazivoda, M. Kušljević, P. Sovilj and M. Šaš, "Travel Route Planning in Smart Cities," 2023 Zooming Innovation in Consumer Technologies Conference (ZINC), Novi Sad, Serbia, 2023, pp. 88-92, doi: 10.1109/ZINC58345.2023.10174121.
  16. S. Hayes, S. Wang and S. Djahel, "Personalized Road Networks Routing with Road Safety Consideration: A Case Study in Manchester," 2020 IEEE International Smart Cities Conference (ISC2), Piscataway, NJ, USA, 2020, pp. 1-6, doi: 10.1109/ISC251055.2020.9239085.
  17. Pradhan, R., Agarwal, A. & De, T. A Multi-Criteria Route Selection Method for Vehicles Using Genetic Algorithms Based on Driver’s Preference. Wireless Pers Commun 125, 2477–2496 (2022). https://doi.org/10.1007/s11277-022-09670-6
  18. N. Sun, H. Shi, G. Han, B. Wang and L. Shu, "Dynamic Path Planning Algorithms With Load Balancing Based on Data Prediction for Smart Transportation Systems," in IEEE Access, vol. 8, pp. 15907-15922, 2020, doi: 10.1109/ACCESS.2020.2966995.
  19. Dimitris Bertsimas, Patrick Jaillet, S´ebastien Martin, Online Vehicle Routing: The Edge of Optimization in Large-Scale Applications, Massachusetts Institute of Technology. Retrieved from https://web.mit.edu/jaillet/www/general/online-routing-18.pdf
  20. Jian Dai, Bin Yang , Chenjuan Guo , Zhiming Ding, Personalized Route Recommendation using Big Trajectory Data, Retrieved from https://coolgiserz.github.io/publication/personalized-routerecommendation-using-big-trajectory-data/personalized-routerecommendation-using-big-trajectory-data.pdf
  21. Yu, Qian & Wang, Yuanguo & Jiang, Xiaogang & Zhao, Bailu & Zhang, Xiuling & Wang, Xiaobei & Liu, Qingqing. (2021). Optimization of Vehicle Transportation Route Based on IoT. Mathematical Problems in Engineering. 2021. 1-10. 10.1155/2021/1312058.
  22. H. Raeesi and A. Hosseinpour, "Routing of vehicles by intelligent algorithms in the matter of transporting goods," 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA), Changchun, China, 2022, pp. 297-302, doi: 10.1109/EEBDA53927.2022.9744800.
  23. S. Jiang, M. Jafari, M. Kharbeche, M. Jalayer and K. N. Al-Khalifa, "Safe Route Mapping of Roadways Using Multiple Sourced Data," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 4, pp. 3169-3179, April 2022, doi: 10.1109/TITS.2020.3032643.
Index Terms

Computer Science
Information Sciences
Driver Behavior
Smart Routing

Keywords

Internet of Things Long Short Term Memory Recurrent Neural Network Global Positioning System Radio Frequency Identification Application Program Interface

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