SafeRouteGuard : Accident-Aware Navigation System

Authors

  • Prof. Anuja Garande Artificial Intelligence & Data Science Engineering, Zeal College of Engineering and Research, Pune, India Author
  • Omkar Kondhalkar Artificial Intelligence & Data Science Engineering, Zeal College of Engineering and Research, Pune, India Author
  • Ayush Sherigar Artificial Intelligence & Data Science Engineering, Zeal College of Engineering and Research, Pune, India Author
  • Pranav Rathod Artificial Intelligence & Data Science Engineering, Zeal College of Engineering and Research, Pune, India Author
  • Manish Gadhave Artificial Intelligence & Data Science Engineering, Zeal College of Engineering and Research, Pune, India Author

DOI:

https://doi.org/10.32628/IJSRSET2411210

Keywords:

Security Issues, Mapbox Security, Openstreetmap Architecture, Challenges, Automation of Road Safety Industry, Security Zone Threats, Security Measurement Frameworks

Abstract

SaferRouteGuard is a novel web application designed to enhance road safety by providing real-time notifications of accident- prone zones, or "black spots," along user-input routes. This system aims to reduce the likelihood of accidents and enhance overall road safety. The research paper discusses the development, methodology, data sources, and future scope of SaferRouteGuard. In a world where transportation is a vital part of our daily lives, road safety remains a paramount concern. The alarming frequency of road accidents, their devastating consequences, and the associated economic burden demand innovative solutions that can proactively address this issue. We are proud to present a groundbreaking project that brings together technology, data analysis, and real-world impact in the form of the "Road Accident Navigation System and Minimal Accident Route Recommendation.”

Downloads

Download data is not yet available.

References

M. Divyaprabha, M. Thangavel and P. Varalakshmi, "A Comparative Study on Road M. H. A. Hussein, T. Sayed, K. Ismail, and A. V. Espen, “Calibrating road design guides using riskbased reliability analysis,” Journal of Transportation Engineering, vol. 140, no. 9, Article ID 04014041, 2013.Safety Problems," 2018 IEEE International Conference on Computational Intelligence And Computing Research (ICCIC), Madurai, India, 2018, pp. 1-7, Doi: 10.1109/ ICCIC.2018.8782353.

Road Accidents Statistics and Reasoning ((IJITR) INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND RESEARCH). Volume No.4,Issue No.6, October - November 2016, 49794984

T. Beshah, D. Ejigu, A. Abraham, V. Snasel and P. Kromer, "Pattern recognition and knowledge discovery from road traffic accident data in Ethiopia: Implications for Improving road safety," 2011 World Congress on Information and Communication Technologies, Mumbai, India, 2011, pp. 1241•1246, Doi: 10.1109/WICT.2011.6141426. DOI: https://doi.org/10.1109/WICT.2011.6141426

Maharashtra Road Crash Report 2021 HIGHWAY POLICE, MAHARASHTRA STATE Published on October 2022

J.K.Poua/Wah/Black Spot/ /2023 Additional Police Commissioner Bahtuk Office Pune City, Dated 18/09/2023 20-9-23 References •1) Jak Appons (WA)/45/Planning/Black Spot (Ran 2020•2022)/2970/2023 Mumbai dated 23/08/2023

M. H. A. Hussein, T. Sayed, K. Ismail, and A. V. Espen, “Calibrating road design guides using risk-based reliability analysis,” Journal of Transportation Engineering, vol. 140, no. 9, Article ID 04014041, 2013. DOI: https://doi.org/10.1061/(ASCE)TE.1943-5436.0000694

P. T. Savolainen, F. L. Mannering, D. Lord, and M. A. Quddus, “The statistical analysis of highway crashinjury severities: a review and assessment of methodological alternatives,” Accident Analysis & Prevention, vol. 43, no. 5, pp. 1666-1676, 2011 DOI: https://doi.org/10.1016/j.aap.2011.03.025

E. T. Donnell and J. M. Mason Jr., “Predicting the frequency of median barrier crashes on Pennsylvania interstate highways,” Accident Analysis & Prevention, vol. 38, no. 3, pp. 590-599, 2006. DOI: https://doi.org/10.1016/j.aap.2005.12.011

K. K. W. Yau, “Risk factors affecting the severity of single vehicle traffic accidents in Hong Kong,” Accident Analysis & Prevention, vol. 36, no. 3, pp. 333-340, 2004. DOI: https://doi.org/10.1016/S0001-4575(03)00012-5

J. Lee and F. Mannering, “Impact of roadside features on the frequency and severity of run-off-roadway accidents: an empirical analysis,” Accident Analysis & Prevention, vol. 34, no. 2, pp. 149-161, 2002. DOI: https://doi.org/10.1016/S0001-4575(01)00009-4

X. Jiang, X. Yan, B. Huang, and S. H. Richards, “Influence of curbs on traffic crash frequency on highspeed roadways,” Traffic Injury Prevention, vol. 12, no. 4, pp. 412-421, 2011. DOI: https://doi.org/10.1080/15389588.2011.578285

C. R. Sax, T. H. Maze, R. R. Souleyrette, N. Hawkins, and L. Carriquiry, “Optimum urban clear zone distance,” Transportation Research Record: Journal of the Transportation Research Board, vol. 2195, no. 1, pp. 27-35, 2010. DOI: https://doi.org/10.3141/2195-04

M. El Esawey and T. Sayed, “Evaluating safety risk of locating above ground utility structures in the highway right-of-way,” Accident Analysis & Prevention, vol. 49, no. 11, pp. 419-428, 2012. DOI: https://doi.org/10.1016/j.aap.2012.03.008

T. Koisaari, T. Tervo, and N. Sihvola, “185 lethal single vehicle accidents of ESC fitted passenger cars,” Injury Prevention, vol. 22, no. 2, 2016. DOI: https://doi.org/10.1136/injuryprev-2016-042156.185

A. Lyckegaard, T. Hels, and I. M. Bernhoft, “Effectiveness of electronic stability control on single vehicle accidents,” Traffic Injury Prevention, vol. 16, no. 4, pp. 380-386, 2015. DOI: https://doi.org/10.1080/15389588.2014.948618

H. L. Shauna, T. Samantha, O. Nicole, C. Cher, and M. Dan, “Evaluation of driving behavior on rural 2-lane curves using the SHRP 2 naturalistic driving study data,” Journal of Safety Research, vol. 54, no. 9, pp. 11-17, 2015. DOI: https://doi.org/10.1016/j.jsr.2015.06.017

M. Hosseinpour, A. S. Yahaya, A. F. Sadullah, N. Ismail, and S. M. R. Ghadiri, “Evaluating the effects of road geometry, environment, and traffic volume on rollover crashes,” Transport, vol. 31, no. 2, pp. 221- 232, 2016. DOI: https://doi.org/10.3846/16484142.2016.1193046

V. N. Shankar, S. Chayanan, S. Sittikariya, M.-B. Shyu, N. K. Juvva, and J. C. Milton, “Marginal impacts of design, traffic, weather, and related interactions on roadside crashes,” Transportation Research Record: Journal of the Transportation Research Board, vol. 1897, no. 1, pp. 156-163, 2004. DOI: https://doi.org/10.3141/1897-20

R. Rusli, M. M. Haque, M. King, and W. S. Voon, “Singlevehicle crashes along rural mountainous highways in Malaysia: an application of random parameters negative binomial model,” Accident Analysis & Prevention, vol. 102, no. 5, pp. 153-164, 2017. DOI: https://doi.org/10.1016/j.aap.2017.03.002

E. K. Adanu, A. Hainen, and S. Jones, “Latent class analysis of factors that influence weekday and weekend single-vehicle crash severities,” Accident Analysis & Prevention, vol. 113, no. 4, pp. 187-192, 2018. DOI: https://doi.org/10.1016/j.aap.2018.01.035

Patil, P., Kataria, B., Redkar, V., Banait, A., Shilpa, C., Patil, & Khetani, V. (08 2024). Automated Detection of Tuberculosis Using Deep Learning Algorithms on Chest X-rays. Frontiers in Health Informatics, 13, 218–229.

Kataria, B., Jethva, H.B., Shinde, P.V., Banait, S.S., Shaikh, F., Ajani, S. (2023). SLDEB: Design of a secure and lightweight dynamic encryption bio-inspired model for IoT networks. International Journal of Safety and Security Engineering, Vol. 13, No. 2, pp. 325-331. https://doi.org/10.18280/ijsse.130214 DOI: https://doi.org/10.18280/ijsse.130214

Shivadekar, S., Kataria, B., Limkar, S. et al. Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process. Soft Comput (2023). https://doi.org/10.1007/s00500-023-08709-5 DOI: https://doi.org/10.1007/s00500-023-08709-5

Shivadekar, S., Kataria, B., Hundekari, S. ., Kirti Wanjale, Balpande, V. P., & Suryawanshi, R. . (2023). Deep Learning Based Image Classification of Lungs Radiography for Detecting COVID-19 using a Deep CNN and ResNet 50. International Journal of Intelligent Systems and Applications in Engineering, 11(1s), 241–250. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2499.

Bhavesh Kataria, Dr. Harikrishna B. Jethva (2021). Optical Character Recognition of Sanskrit Manuscripts Using Convolution Neural Networks, Webology, ISSN: 1735-188X, Volume 18 Issue 5, October-2021, pp. 403-424.

Downloads

Published

30-03-2024

Issue

Section

Research Articles

How to Cite

[1]
A. G. Garande, O. Kondhalkar, A. Sherigar, P. Rathod, and M. Gadhave, “SafeRouteGuard : Accident-Aware Navigation System”, Int J Sci Res Sci Eng Technol, vol. 11, no. 2, pp. 122–132, Mar. 2024, doi: 10.32628/IJSRSET2411210.

Similar Articles

1-10 of 103

You may also start an advanced similarity search for this article.