Skip to main content
SpringerLink
Log in

Traffic Monitoring and Estimating Speed by Side-Looking FMCW Radar

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

One of the most important problems in traffic management is evaluating the amount of traffic and the velocity of vehicles passing through transportation ways and main streets. In this study, the traffic load is measured, and the speed of cars is estimated using the 24 GHz FMCW radar. In this process, an antenna is installed to record all the targets from the side of the highway. Next, the moving vehicles are classified according to their type, based on which the traffic load is provided to the user in each highway lane. Due to the radial velocity, low Doppler frequency, and variability with time, some challenges will emerge, for which two solutions will be provided. This paper describes the speed of cars and the amount of congestion in each highway lane presented by two new methods. Finally, with the process of canceling clutters observed by radar and detecting possible errors, a highway statistic is presented as a table.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code Availability

The code is available from the corresponding author upon reasonable request.

References

  1. Jain, A., Yadav, S., Vij, S., Kumar, Y., & Tayal, D. K. (2020). A novel self-organizing approach to automatic traffic light management system for road traffic network. Wireless Personal Communications, 110(3), 1303–1321.

    Article  Google Scholar 

  2. Won, M. (2020). Intelligent traffic monitoring systems for vehicle classification: A survey. IEEE Access, 8, 73340–73358.

    Article  Google Scholar 

  3. Ustunel, E., & Masazade, E. (2019). Vision-based road slope estimation methods using road lines or local features from instant images. IET Intelligent Transport Systems, 13(10), 1590–1602.

    Article  Google Scholar 

  4. Gholamhosseinian, A., & Seitz, J. (2021). Vehicle classification in intelligent transport systems: An overview, methods and software perspective. IEEE Open Journal of Intelligent Transportation Systems, 2, 173–194.

    Article  Google Scholar 

  5. Zhu, J., Sun, K., Jia, S., Li, Q., Hou, X., Lin, W., Liu, B., & Qiu, G. (2018). Urban traffic density estimation based on ultrahigh-resolution UAV video and deep neural network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(12), 4968–4981.

    Article  Google Scholar 

  6. Zhang, Z., Zhao, T., Ao, X., & Yuan, H. (2017). A vehicle speed estimation algorithm based on dynamic time warping approach. IEEE Sensors Journal, 17(8), 2456–2463.

    Article  Google Scholar 

  7. Chaturvedi, S. K. (2019). Study of synthetic aperture radar and automatic identification system for ship target detection. Journal of Ocean Engineering and Science, 4(2), 173–182.

    Article  Google Scholar 

  8. Sumaiya, M. N., & Kumari, R. S. S. (2017). Satellite image change detection using Laplacian-Gaussian distributions. Wireless Personal Communications, 97(3), 4621–4630.

    Article  Google Scholar 

  9. Niaz, M. W., & Bhatti, R. A. (2017). High-isolation antenna system for x-band synthetic aperture radar. Wireless Personal Communications, 97(2), 2741–2750.

    Article  Google Scholar 

  10. Zhao, Y., Zhao, L., Xiong, B., & Kuang, G. (2020). Attention receptive pyramid network for ship detection in SAR images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 2738–2756.

    Article  Google Scholar 

  11. Felguera-Martín, D., González-Partida, J. T., Almorox-González, P., & Burgos-García, M. (2012). Vehicular traffic surveillance and road lane detection using radar interferometry. IEEE Transactions on Vehicular Technology, 61(3), 959–970.

    Article  Google Scholar 

  12. Lim, H. S., Lee, J. E., Park, H. M., & Lee, S. (2020). Stationary target identification in a traffic monitoring radar system. Applied Sciences, 10(17), 5838.

    Article  Google Scholar 

  13. Wei, Q., & Yang, B. (2017). Adaptable vehicle detection and speed estimation for changeable urban traffic with anisotropic magnetoresistive sensors. IEEE Sensors Journal, 17(7), 2021–2028.

    Article  Google Scholar 

  14. Ash, M., Ritchie, M., & Chetty, K. (2018). On the application of digital moving target indication techniques to short-range FMCW radar data. IEEE Sensors Journal, 18(10), 4167–4175.

    Article  Google Scholar 

  15. Munoz-Ferreras, J. M., Perez-Martinez, F., Calvo-Gallego, J., Asensio-Lopez, A., Dorta-Naranjo, B. P., & Blanco-del-Campo, A. (2008). Traffic surveillance system based on a high-resolution radar. IEEE Transactions on Geoscience and Remote Sensing, 46(6), 1624–1633.

    Article  Google Scholar 

  16. Jeng, S. L., Chieng, W. H., & Lu, H. P. (2013). Estimating speed using a side-looking single-radar vehicle detector. IEEE Transactions on Intelligent Transportation Systems, 15(2), 607–614.

    Article  Google Scholar 

  17. Nimac, P., Krpič, A., Batagelj, B., & Gams, A. (2022). Pedestrian traffic light control with crosswalk FMCW radar and group tracking algorithm. Sensors, 22(5), 1754.

    Article  Google Scholar 

  18. Arpanaei, F., Shakeri, M., & Ghalamkari, B. (2016). An improved and novel de-ramping technique for linear frequency modulated continuous wave synthetic aperture radar. Journal of Telecommunication Electronic and Computer Engineering (JTEC), 8(9), 53–60.

    Google Scholar 

  19. Kim, W., Cho, H., Kim, J., Kim, B., & Lee, S. (2020). YOLO-based simultaneous target detection and classification in automotive FMCW radar systems. Sensors, 20(10), 2897.

    Article  Google Scholar 

  20. Feng, Z., Li, M., Stolz, M., Kunert, M., & Wiesbeck, W. (2018). Lane detection with a high-resolution automotive radar by introducing a new type of road marking. IEEE Transactions on Intelligent Transportation Systems, 20(7), 2430–2447.

    Article  Google Scholar 

  21. Sk, N. M. (2015). Configurable folded IIR filter design. IEEE Transactions on Circuits and Systems II: Express Briefs, 62(12), 1144–1148.

    Google Scholar 

  22. Wang, D., & Fattouche, M. (2013). Range estimation in a time varying multipath channel. Wireless Personal Communications, 71, 887–908.

    Article  Google Scholar 

  23. Wang, P. J., Li, C. M., Wu, C. Y., & Li, H. J. (2010). A channel awareness vehicle detector. IEEE Transactions on Intelligent Transportation Systems, 11(2), 339–347.

    Article  Google Scholar 

  24. Liu, W., Cao, S., Gan, S., Chen, Y., Zu, S., & Jin, Z. (2016). One-step slope estimation for dealiased seismic data reconstruction via iterative seislet thresholding. IEEE Geoscience and Remote Sensing Letters, 13(10), 1462–1466.

    Article  Google Scholar 

  25. Islam, M. S., & Chong, U. (2015). Improvement in moving target detection based on Hough transform and wavelet. IETE Technical Review, 32(1), 46–51.

    Article  Google Scholar 

Download references

Funding

The authors received no financial support for the research work.

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Alireza Maryanaji & Behbod Ghalamkari

  2. Communication Technology Institute, Iran Telecommunication Research Center, Tehran, Iran

    Sara Efazati

Authors
  1. Alireza Maryanaji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Behbod Ghalamkari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sara Efazati
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AM and BG conceived and designed the study. AM generated the experimental data. BG and SE analysed the data with assistance from AM. SE and BG wrote the paper with input from AM SE edits the whole of the paper.

Corresponding author

Correspondence to Behbod Ghalamkari.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Maryanaji, A., Ghalamkari, B. & Efazati, S. Traffic Monitoring and Estimating Speed by Side-Looking FMCW Radar. Wireless Pers Commun 133, 851–867 (2023). https://doi.org/10.1007/s11277-023-10794-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-023-10794-6

Keywords

Search

Navigation