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Evaluation on New Energy Vehicle Safety Early Warning System Based on Intelligent Optimization Algorithm

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DOI: 10.23977/acss.2024.080614 | Downloads: 41 | Views: 886

Author(s)

Yongan Luo 1, Yeheng He 1, Yangyong Lan 1

Affiliation(s)

1 Changsha Yifeng Automotive Technology Co., Ltd., Changsha, Hunan, China

Corresponding Author

Yongan Luo

ABSTRACT

With the substantial increase in the inventory of vehicles, New Energy Vehicles (NEV) have received more and more attention. At the same time, the safety of NEV has received attention. When the safety problem of NEV occurs, the communication transmission of safety warning information can be processed at the first time. Communication transmission needs to use communication technology, which is mainly used for information transmission and signal processing. However, the communication speed of the traditional new energy vehicle safety early warning system is slow, and the safety performance needs to be improved. Intelligent optimization algorithms were applied to NEV safety warning systems, and the overall structure of the NEV safety early warning system was analyzed and improved. Through testing different new energy vehicles, it was found that: applying the intelligent optimization algorithm to the safety early warning system of NEV can improve the accuracy of vehicle positioning. The intelligent optimization algorithm can improve the safety performance of NEV, and can effectively improve the communication speed of early warning information of vehicles. Vehicles with improved safety warning systems are more popular with users, and user satisfaction increased by 6.67%. The intelligent optimization algorithm has improved the safety early warning system of NEV, and the communication function of NEV has also been improved.

KEYWORDS

New Energy Vehicle Safety Warning System; Intelligent Optimization Algorithm; Communication Technology; Information Transmission

CITE THIS PAPER

Yongan Luo, Yeheng He, Yangyong Lan, Evaluation on New Energy Vehicle Safety Early Warning System Based on Intelligent Optimization Algorithm. Advances in Computer, Signals and Systems (2024) Vol. 8: 94-105. DOI: http://dx.doi.org/10.23977/acss.2024.080614.

REFERENCES

[1] Visconti, Paolo. "Innovative complete solution for health safety of children unintentionally forgotten in a car: a smart Arduino‐based system with user app for remote control." IET Science, Measurement & Technology 14.6 (2020): 665-675.
[2] Lee, Sang Hyeop, Suk Lee, and Man Ho Kim. "Development of a driving behavior-based collision warning system using a neural network." International journal of automotive technology 19.5 (2018): 837-844.
[3] Song, Wenjie. "Real-time obstacles detection and status classification for collision warning in a vehicle active safety system." IEEE Transactions on intelligent transportation systems 19.3 (2017): 758-773.
[4] Sternlund, Simon. "The effectiveness of lane departure warning systems—A reduction in real-world passenger car injury crashes." Traffic injury prevention 18.2 (2017): 225-229.
[5] Outay, Fatma. "Investigation of the impact of a wireless Fog Warning System with respect to road traffic on a highway." Personal and Ubiquitous Computing 23.5 (2019): 893-899.
[6] Lim, Wonteak. "Hierarchical trajectory planning of an autonomous car based on the integration of a sampling and an optimization method." IEEE Transactions on Intelligent Transportation Systems 19.2 (2018): 613-626.
[7] Che, Gaofeng, Lijun Liu, and Zhen Yu. "An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle." Journal of Ambient Intelligence and Humanized Computing 11.8 (2020): 3349-3354.
[8] Chen, Chen. "Fuzzy adaptive control particle swarm optimization based on TS fuzzy model of maglev vehicle suspension system." Journal of Mechanical Science and Technology 34.1 (2020): 43-54.
[9] SANA, Khurram SHAHZAD, and H. U. Weiduo. "Hypersonic reentry trajectory planning by using hybrid fractional-order particle swarm optimization and gravitational search algorithm." Chinese Journal of Aeronautics 34.1 (2021): 50-67.
[10] Li, Zhe, and Ling Zheng. "Integrated design of active suspension parameters for solving negative vibration effects of switched reluctance-in-wheel motor electrical vehicles based on multi-objective particle swarm optimization." Journal of Vibration and Control 25.3 (2019): 639-654.
[11] Mulvihill, Christine. "Original road safety research: First-stage evaluation of a prototype driver distraction human-machine-interface warning system." Journal of road safety 32.4 (2021): 4-14.
[12] Gheraibia, Youcef. "An overview of the approaches for automotive safety integrity levels allocation." Journal of failure analysis and prevention 18.3 (2018): 707-720.
[13] Bello, Lucia Lo. "Recent advances and trends in on-board embedded and networked automotive systems." IEEE Transactions on Industrial Informatics 15.2 (2018): 1038-1051.
[14] Abraham, Hillary. "Case study of today’s automotive dealerships: Introduction and delivery of advanced driver assistance systems." Transportation research record 2660.1 (2017): 7-14.
[15] Takacs, Arpad. "Automotive safety in the development pipeline of highly automated vehicles: Rethinking traditional automotive product-creation methods." IEEE Systems, Man, and Cybernetics Magazine 6.1 (2020): 35-40.
[16] Mukhadis, A. "Effectiveness of professional practice work with discovery learning methods in engineering program D IV automotive safety." Advanced Science Letters 23.2 (2017): 1154-1157.
[17] Xie, Guoqi. "Reliability enhancement toward functional safety goal assurance in energy-aware automotive cyber-physical systems." IEEE Transactions on Industrial Informatics 14.12 (2018): 5447-5462.
[18] Yang, Fan, Pinjie Xie, and Bowen Xiang. "How to promote the new energy vehicles under China's "Internet plus” initiative: a review." Energy and Power Engineering 12.5 (2020): 154-181. 
[19] Jin, Xiaoye. "Factors influencing the development ability of intelligent manufacturing of new energy vehicles based on a structural equation model." Acs Omega 5.29 (2020): 18262-18272.
[20] Feng, Xiao, Bo Huang, and Yuyu Li. "R&D investment in new energy vehicles with purchase subsidy based on technology adoption life cycle and customers' choice behaviour." IET Intelligent Transport Systems 14.11 (2020): 1371-1377.
[21] Nasser Liser. New Energy Vehicle Development Strategy Integrated with Finite Volume Method. Kinetic Mechanical Engineering (2020), Vol. 1, Issue 2: 45-53. 
[22] Gachuno Eduard. New Energy Vehicle System Optimization on Hill Climbing Algorithm. Kinetic Mechanical Engineering (2020), Vol. 1, Issue 4: 29-37.

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