Skip to main content
SpringerLink
Log in

The Design of an Expressway Lighting and Early Warning System Based on MCU

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

There is a design of an expressway lighting and early warning system based on MCU, and the corresponding control method is proposed in this paper. The system and its control method can realize the lighting and direction guidance of the vehicles on the expressway under different situations. The different colors of lights are used to remind the vehicle of the different driving situation. The emergent buttons and GSM module can realize help-calling for people in distress in the expressway and can also be used for road maintenance personnel to locate the worker and check on work attendance. The system and its control method can also realize the vehicle counting function and the calculation of magnitude of traffic flow.

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.

Similar content being viewed by others

REFERENCES

  1. Zhao, L., Qu, S., and Zhang, W., Design of multi-channel data collector for expressway tunnel lighting based on STM32 and Modbus protocol, Optik, 2020, vol. 213, p. 164388.  https://doi.org/10.1016/j.ijleo.2020.164388

    Article  Google Scholar 

  2. Parsa, A.B., Movahedi, A., Taghipour, H., Derrible, S., and Mohammadian, A., Toward safer expressways application of XGBoost and SHAP for real-time accident detection and feature analysis, Accid. Anal. Prev., 2020, vol. 136, p. 105405.  https://doi.org/10.1016/j.aap.2019.105405

    Article  Google Scholar 

  3. El Hatri, C. and Boumhidi, J., Fuzzy deep learning based urban traffic incident detection, Cognit. Syst. Res., 2018, vol. 50, no. 2, pp. 606–625.  https://doi.org/10.1016/j.cogsys.2017.12.002

    Article  Google Scholar 

  4. Deb, R. and Liew, A.W.-C., Noisy values detection and correction of traffic accident data, Inf. Sci., 2019, vol. 476, pp. 132–146.  https://doi.org/10.1016/j.ins.2018.10.002

    Article  Google Scholar 

  5. Jiao, P., Miao, Q., Zhang, M., and Zhao, W., A virtual reality method for digitally reconstructing traffic accidents from videos or still images, Forensic Sci. Int., 2018, vol. 292, pp. 176–180.  https://doi.org/10.1016/j.forsciint.2018.09.019

    Article  Google Scholar 

  6. Li, M., Zhen, L., Wang, S., Lv, W., and Qu, X., Unmanned aerial vehicle scheduling problem for traffic monitoring, Comput. Ind. Eng., 2018, vol. 122, pp. 15–23.  https://doi.org/10.1016/j.cie.2018.05.039

    Article  Google Scholar 

  7. Zhou, X., The research on freeway traffic accident warning management, PhD Thesis, Wuhan: Wuhan Univ. of Technology, 2013.

  8. Carrillo, J.H., Emert, S.E., Sherman, D.E., Herckes, P., Collett, J.L., Jr., An economical optical cloud/fog detector, Atmos. Res., 2007, vol. 87, nos. 3–4, pp. 259–267.  https://doi.org/10.1016/j.atmosres.2007.11.007

    Article  Google Scholar 

  9. Javadi, S., Dahl, M., and Petterson, M.I., Vehicle speed measurement model for video-based systems, Comput. Electr. Eng., 2019, vol. 76, pp. 238–248.  https://doi.org/10.1016/j.compeleceng.2019.04.001

    Article  Google Scholar 

  10. Shariff, K.K.M., Hoare, E., Daniel, L., Antoniou, M., and Cherniakov, M., Comparison of adaptive spectral estimation for vehicle speed measurement with radar sensors, Sensors, 2017, vol. 17, no. 4, p. 751.  https://doi.org/10.3390/s17040751

    Article  Google Scholar 

  11. Lou, J., GSM-based wireless expressway comprehensive management of social management system, PhD Thesis, Nanchang: East China Univ. of Technology, 2015.

Download references

Funding

This work was supported in part by Six Talent Peaks Project of Jiangsu Province (2016-XNYQC-001) and Jiangsu Provincial Department of Housing and Construction (project no. 2019ZD060).

Author information

Authors and Affiliations

  1. Faculty of Mathematics and Physics, Huaiyin Institute of Technology, 223003, Huaian, China

    Y.-Y. Fan

  2. Faculty of Electronic and Electrical Engineering, Huaiyin Institute of Technology, 223003, Huaian, China

    S. Zhang, Z.-Z. Ding, K. Peng, Y.-J. Zhang, D.-J. Cheng & Y.-J. Sang

Authors
  1. Y.-Y. Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Z.-Z. Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. K. Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Y.-J. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. D.-J. Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Y.-J. Sang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Y.-J. Sang.

Ethics declarations

The authors declare that they have no conflicts of interest.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fan, YY., Zhang, S., Ding, ZZ. et al. The Design of an Expressway Lighting and Early Warning System Based on MCU. Aut. Control Comp. Sci. 56, 38–44 (2022). https://doi.org/10.3103/S0146411622010059

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411622010059

Keywords:

Search

Navigation