INTELLECTUAL SAFETY OF ELECTRIC SCOOTERS WITH SMARTSTOP TECHNOLOGY

  • Tetiana Korobeynikova PhD (Engineering), Associate Professor, Lviv Polytechnic National University, Ukraine https://orcid.org/0000-0003-2487-8742
  • Oleksandr Reminnyi PhD (Engineering), Assistant, Lviv Polytechnic National University, Ukraine https://orcid.org/0009-0005-5119-3695
  • Daniel Gada student of the Department of Computerised Automation Systems, Lviv Polytechnic National University, Ukraine
  • Artem Gada student of the Department of Computerised Automation Systems, Lviv Polytechnic National University, Ukraine
  • Nazariy Dmytriv student of the Department of Computerised Automation Systems, Lviv Polytechnic National University, Ukraine
Keywords: electric scooter, traffic safety, adaptive speed control, automatic braking, SMARTSTOP

Abstract

 The article considers the problem of improving the safety of electric scooters in the urban environment through the development and implementation of the SMARTSTOP intelligent system. The proposed system is based on adaptive speed control and automated braking using sensor technologies and real-time algorithms. The key components of the system are ultrasonic sensors, an Arduino Nano microcontroller, a potentiometer, a servo drive, an electric motor, an LCD display, and a piezoelectric speaker. SMARTSTOP allows you to effectively detect static and dynamic obstacles within 5-6 m. with a viewing angle of 150 degrees, determine the level of threat and respond accordingly by slowing down or initiating automatic braking. The system was tested using the Hardware-in-the-Loop (HiL) methodology on the MATLAB/Simulink platform, which allowed us to simulate various road scenarios. The test results confirmed the high efficiency and accuracy of the system, which ensures timely response to potential hazards. Further development areas include improving algorithms for difficult operating conditions and integrating SMARTSTOP with smart city technologies.

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References

Wanganoo, L., Shukla, V., & Mohan, V. (2022). Intelligent micro‐mobility e‐scooter: revolutionizing urban transport. Trust‐based communication systems for internet of things applications, 267-290. DOI: https://doi.org/10.1002/9781119896746.ch11

D'Addato, M. (2021). Design of a smart sensor for obstacles detection on electric scooters or bicycles (Doctoral dissertation, Politecnico di Torino), URL: http://webthesis.biblio.polito.it/id/eprint/18054

Vinayaga-Sureshkanth, N., Wijewickrama, R., Maiti, A., & Jadliwala, M. (2020). Security and privacy challenges in upcoming intelligent urban micromobility transportation systems. In Proceedings of the Second ACM Workshop on Automotive and Aerial Vehicle Security, pp. 31-35, DOI: https://doi.org/10.1145/3507657.3528551

Jang, W. J., Kim, D. H., & Lim, S. H. (2023). An AI safety monitoring system for electric scooters based on the number of riders and road types. Sensors, 23(22), 9181, DOI: https://doi.org/10.3390/s23229181

Alai, H., Jeon, W., Alexander, L., & Rajamani, R. (2025). A smart e-scooter with embedded estimation of rear vehicle trajectories for rider protection. Mechanical Systems and Signal Processing, 222, 111786, DOI: https://doi.org/10.1016/j.ymssp.2024.111786

Ma, Q., Yang, H., Mayhue, A., Sun, Y., Huang, Z., & Ma, Y. (2021). E-Scooter safety: The riding risk analysis based on mobile sensing data. Accident Analysis & Prevention, 151, 105954, DOI: https://doi.org/10.1016/j.aap.2020.105954

Babiy, M. V., Babiy, V. A., & Martynchuk, A. O. (2023). Intelligent traffic safety systems. Materials of the V International Scientific and Practical Conference ‘Improving the reliability and efficiency of machines, processes and systems’. Kropyvnytskyi: TSNTU, 156 [in Ukrainian]

Yakovenko, T. K. (2024). Motion sensors based on the Arduino microcontroller in intelligent security systems [in Ukrainian]

Published
2024-12-30
Cited
How to Cite
Korobeynikova, T., Reminnyi, O., Gada, D., Gada, A., & Dmytriv, N. (2024). INTELLECTUAL SAFETY OF ELECTRIC SCOOTERS WITH SMARTSTOP TECHNOLOGY. Computer Science and Cybersecurity, (2), 25-40. https://doi.org/10.26565/2519-2310-2024-2-03
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Статті