Abstract
To improve the anti-collision warning system of road traffic, a research based on fuzzy nonlinear programming is proposed. People hope to know the accident in advance, and then take the corresponding protective measures to avoid accidents, to achieve the purpose of reducing the number of accidents. The specific content of this method is to establish a safety distance model to prevent rear-end collision. The following process can be divided into three situations: the leading vehicle is stationary, the leading vehicle is at uniform speed or accelerating speed, and the leading vehicle is decelerating. The mathematical model of the safe distance of overtaking are established respectively. The fuzzy mathematical theory is used to consider the influence of external environmental factors such as weather conditions, road condition, and vehicle speed. Determine the parameters involved in the model and the fuzzy relationship between some parameters and each influencing factor. The simulation model of vehicle anti-collision warning system is established by using fuzzy inference rules of some parameters, respectively, and the simulation test is conducted. The test results verify the rationality of the safety distance model and parameter setting. It can effectively reduce false alarm and improve the road traffic collision warning system.
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References
Bhatia V, Kaur S, Sharma K, Rattan P, Jagota V, Kemal MA (2021) Design and simulation of capacitive MEMS switch for Ka band application. Wirel Commun Mobile Comput 2021:8. https://doi.org/10.1155/2021/2021513
Bhola J, Soni S, Kakarala J (2019) A scalable and energy-efficient MAC protocol for sensor and actor networks”. Int J Commun Syst 32(13):1–16
Cao Y, Wen J, Ma L (2021) Tracking and collision avoidance of virtual coupling train control system. Futur Gener Comput Syst 120:76–90. https://doi.org/10.1016/j.future.2021.02.014
Chen L, Jagota V, Kumar A (2021) Research on optimization of scientific research performance management based on BP neural network. Int J Syst Assur Eng Manag. https://doi.org/10.1007/s13198-021-01263-z
Cheng Z, Liu X, Qiu T (2017). Vehicle target recognition system based on fuzzy control for millimeter wave radar. 2017 9th international conference on intelligent human-machine systems and cybernetics (IHMSC).In: 2017 9th international conference on intelligent human-machine systems and cybernetics (IHMSC). https://doi.org/10.1109/ihmsc.2017.46
Ding Q (2021) Risk early warning management and intelligent real-time system of financial enterprises based on fuzzy theory. J Intell Fuzzy Syst 40(4):6017–6027. https://doi.org/10.3233/JIFS-189441
Ding T, Li X, Zheng L, Hao Z (2019) Research on safety lane change warning method based on potential angle collision point. J Adv Transp 2019:1–14. https://doi.org/10.1155/2019/1281425
Jairath K, Singh N, Jagota V, Shabaz M (2021) Compact ultrawide band metamaterial-inspired split ring resonator structure loaded band notched antenna. Math Prob Eng. https://doi.org/10.1155/2021/5174455
Kishor A, Chakraborty C (2021) Early and accurate prediction of diabetics based on FCBF feature selection and SMOTE. Int J Syst Assur Eng Manag 1–9
Li R, Jin Y (2018) The early-warning system based on hybrid optimization algorithm and fuzzy synthetic evaluation model. Inf Sci 435:296–319. https://doi.org/10.1016/j.ins.2017.12.040
Li C, Zhu Z (2018) Research and application of a novel hybrid air quality early-warning system: a case study in China. Sci Total Environ 626:1421–1438. https://doi.org/10.1016/j.scitotenv.2018.01.195
Li S, Yu-Zhen S, Fan L (2015) Research on risk early-warning dynamic evaluation of logistics service supply chain based on structure entropy weight-markov analysis. J Softw Eng 9(4):858–867. https://doi.org/10.3923/jse.2015.858.867
Li L, Ma J, Zhan X (2017) The development and application of cycle economic early warning system based on fuzzy comprehensive evaluation. Int J Appl Decis Sci 10(1):36. https://doi.org/10.1504/ijads.2017.081791
Li C, Liu S, Cen X (2021) Safety and efficiency impact of pedestrian–vehicle conflicts at non signalized midblock crosswalks based on fuzzy cellular automata. Physica A 572:125871. https://doi.org/10.1016/j.physa.2021.125871
Lokhande MP, Patil DD, Patil LV, Shabaz M (2021) Machine-to-machine communication for device identification and classification in secure telerobotics surgery. Secur Commun Netw 2021:1–16. https://doi.org/10.1155/2021/5287514
Rakhra M, Singh R, Lohani TK, Shabaz M (2021) Metaheuristic and machine learning-based smart engine for renting and sharing of agriculture equipment. Math Probl Eng 2021:1–13. https://doi.org/10.1155/2021/5561065
Sanober S, Alam I, Pande S, Arslan F, Rane KP, Singh BK, Khamparia A, Shabaz M (2021) An enhanced secure deep learning algorithm for fraud detection in wireless communication. Wirel Commun Mob Comput 2021:1–14. https://doi.org/10.1155/2021/6079582
Sant A, Garg L, Xuereb P, Chakraborty C (2021) A novel green IoT-based pay-as-you-go smart parking system. CMC Comput Mater Cont 67(3):3523–3544
Sookoo A, Garg L, Chakraborty C (2021) Improvement of system performance in an IT production support environment. Int J Syst Assur Eng Manag 1–19
Takahashi A, Asanuma N (n.d.). Introduction of Honda ASV-2 (advanced safety vehicle-phase 2).In: Proceedings of the IEEE intelligent vehicles symposium 2000 (Cat. No.00TH8511). IV 2000 Intelligent Vehicles Symposium. https://doi.org/10.1109/ivs.2000.898430
Wang Q, Hui F, Wang X, Ding Q (2018) Research on early warning and monitoring algorithm of financial crisis based on fuzzy cognitive map. Clust Comput 22(S2):3689–3697. https://doi.org/10.1007/s10586-018-2219-7
Yan JM (2013) Research on driving simulator in early warning system of vehicle rear-end collisions. Appl Mech Mater 380–384:581–585
Yang W, Zhang X, Lei Q, Cheng X (2019) Research on longitudinal active collision avoidance of autonomous emergency braking pedestrian system (AEB-P). Sensors 19(21):4671. https://doi.org/10.3390/s19214671
Zhang W, Zhou N, Tang L, Qi F, Zhao L (2017) Research on the non-contact early warning of dangerous electric field by overhead transmission lines. Integr Ferroelectr 181(1):141–150. https://doi.org/10.1080/10584587.2017.1352406
Zhou Q, Xiong T, Wang M, Xiang C, Xu Q (2017) Diagnosis and early warning of wind turbine faults based on cluster analysis theory and modified ANFIS. Energies 10(7):898. https://doi.org/10.3390/en10070898
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The Project of Excellent Talents Support in Colleges and Universities, (Research on Vehicle Collision Prevention Warning Based on GIS Application in snow and ice weather), Project No: gxyqZD2020052.
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Peng, F., Wang, Y., Xuan, H. et al. Efficient road traffic anti-collision warning system based on fuzzy nonlinear programming. Int J Syst Assur Eng Manag 13 (Suppl 1), 456–461 (2022). https://doi.org/10.1007/s13198-021-01468-2
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DOI: https://doi.org/10.1007/s13198-021-01468-2