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Design and Deployment of the Road Safety System in Vehicular Network Based on a Distance and Speed

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Intelligent Computing and Applications

Abstract

In the age of intelligent communication technology, intelligent mobile phones play a critical role in road accidents. Their effect on driving, resulting in vehicle crashes over the last two decades, has become a significant risk. Speed was identified as an important risk factor for road traffic accidents. By monitoring vehicle speed and position, one can help prevent accidents by sending out alert messages and limiting the consequences for unprotected road users such as pedestrians and cyclists. To manage and control road accidents, the position and speed of the vehicle were communicated to nearby cars, and the excellent circle method was used to calculate the distance between the towing vehicle and the trailing vehicle. This method is based on the zero point of the earth’s equator and GPS. The application was tested in this paper using mobile devices. The experiment used various smartphone modules, such as GPS receivers, digital road maps, and communication systems. A prototype was developed and evaluated using mobile phones in highway and city scenarios with varying speeds and network sizes. As a result of the experiment, location and speed accuracy were determined, and alert messages were generated when the distance between vehicles fell below the standard or government-specified length. The investigation could be expanded further by connecting to the Internet, storing data in the cloud, performing analytics, and involving insurance agents, relatives, and nearby hospitals.

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References

  1. Ali, K., Al Yaseen, D., Ejaz, A., Javed, T., & Hassanein, H. S. (2012). CrowdITS: Crowdsourcing in intelligent transportation systems. In Wireless Communications and Networking Conference (WCNC) (pp. 3307–3311). IEEE.

    Google Scholar 

  2. Koukoumidis, E., Peh, L. S., & Martonosi, M. R. (2011). Signalguru: Leveraging mobile phones for collaborative traffic signal schedule advisory. In Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services (pp. 127–140). ACM.

    Google Scholar 

  3. Zhang, X., Gong, H., Xu, Z., Tang, J., & Liu, B. (2012). Jam eyes: A traffic jam awareness and observation system using mobile phones. International Journal of Distributed Sensor Networks.

    Google Scholar 

  4. Yang, Y., Chen, B., Su, L., & Qin, D. (2013). Research and development of hybrid electric vehicles can-bus data monitor and diagnostic system through ODB-11 and android-based smartphones. Advances in Mechanical Engineering.

    Google Scholar 

  5. Koukoumidis, E., Martonosi, M., & Peh, L. S. (2012). Leveraging smartphone cameras for collaborative road advisories. IEEE Transactions on Mobile Computing, 11(5), 707–723.

    Article  Google Scholar 

  6. White, J., Thompson, C., Turner, H., Dougherty, B., & Schmidt, D. C. (2011). WreckWatch: Automatic traffic accident detection and notification with smartphones. Mobile Networks and Applications, 16(3), 285–303.

    Article  Google Scholar 

  7. Zaldivar, J., Calafate, C. T., Cano, J. C., & Manzoni, P. (2011). Providing accident detection in vehicular networks through OBDII devices and Android-based smartphones. In 36th Conference on Local Computer Networks (LCN) (pp. 813–819). IEEE.

    Google Scholar 

  8. Magaña, V. C., & Organero, M. M. Artemisa: Using an Android device as an eco-driving assistant. Cyber Journals: Multidisciplinary Journals in Science and Technology: Journal of Selected Areas in Mechatronics (JMTC).

    Google Scholar 

  9. Castignani, G., Derrmann, T., Frank, R., & Engel, T. (2015). Driver behavior profiling using smartphones: A low-cost platform for driver monitoring. Intelligent Transportation Systems Magazine, IEEE, 7(1), 91–102. https://doi.org/10.1109/MITS.2014.2328673

    Article  Google Scholar 

  10. Verma, N. (2018). Development of native mobile application using android studio for cabs and some glimpse of cross-platform apps. International Journal of Applied Engineering Research, 13(16), 12527–12530. ISSN 0973-4562. © Research India Publications. http://www.ripublication.com

  11. Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., & Balakrishnan, H. The pothole patrol: Using a mobile sensor network for road surface monitoring. In Proceedings of the 6th International Conference on Mobile Systems, Applications, Street-Safety.

    Google Scholar 

  12. Ghose, A., Biswas, P., Bhaumik, C., Sharma, M., Pal, A., & Jha, A. (2012). Road condition monitoring and alert application: Using-vehicle smartphone as an internet-connected sensor. In 10th International Conference on Pervasive Computing and Communications Workshops (PerComWorkshops) (pp. 489–491). IEEE.

    Google Scholar 

  13. Mednis, A., Strazdins, G., Zviedris, R., Kanonirs, G., & Selavo, L. (2011). Real-time pothole detection using android smartphones with accelerometers. In International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS) (pp. 1–6). IEEE.

    Google Scholar 

  14. Mohan, P., Padmanabhan, V. N., & Ramjee, R. (2008). Nericell: Rich monitoring of road and track conditions using mobile smartphones. In Proceedings of the 6th ACM conference Embedded Network Sensor Systems (pp. 323–336). ACM.

    Google Scholar 

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Correspondence to Nagarjuna Karyemsetty .

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Syamsundararao, T., Samatha, B., Karyemsetty, N., Gogulamudi, S., Deepak, V. (2023). Design and Deployment of the Road Safety System in Vehicular Network Based on a Distance and Speed. In: Rao, B.N.K., Balasubramanian, R., Wang, SJ., Nayak, R. (eds) Intelligent Computing and Applications. Smart Innovation, Systems and Technologies, vol 315. Springer, Singapore. https://doi.org/10.1007/978-981-19-4162-7_18

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