Research on Vehicle AEB Control Strategy Based on Safety Time–Safety Distance Fusion Algorithm
With the increasing consumer focus on automotive safety, Autonomous Emergency Braking (AEB) systems, recognized as effective active safety technologies for collision avoidance and the mitigation of collision-related injuries, are gaining wider application in the automotive industry. To address the i...
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| Published in | Mathematics (Basel) Vol. 12; no. 12; p. 1905 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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Basel
MDPI AG
01.06.2024
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| ISSN | 2227-7390 2227-7390 |
| DOI | 10.3390/math12121905 |
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| Abstract | With the increasing consumer focus on automotive safety, Autonomous Emergency Braking (AEB) systems, recognized as effective active safety technologies for collision avoidance and the mitigation of collision-related injuries, are gaining wider application in the automotive industry. To address the issues of the insufficient working reliability of AEB systems and their unsatisfactory level of accordance with the psychological expectations of drivers, this study proposes an optimized second-order Time to Collision (TTC) safety time algorithm based on the motion state of the preceding vehicle. Additionally, the study introduces a safety distance algorithm derived from an analysis of the braking process of the main vehicle. The safety time algorithm focusing on comfort and the safety distance algorithm focusing on safety are effectively integrated in the time domain and the space domain to obtain the safety time–safety distance fusion algorithm. A MATLAB/Simulink–Carsim joint simulation platform has been established to validate the AEB control strategy in terms of safety, comfort, and system responsiveness. The simulation results show that the proposed safety time–safety distance fusion algorithm consistently achieves complete collision avoidance, indicating a higher safety level for the AEB system. Furthermore, the application of active hierarchical braking minimizes the distance error, at under 0.37 m, which meets psychological expectations of drivers and improves the comfort of the AEB system. |
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| AbstractList | With the increasing consumer focus on automotive safety, Autonomous Emergency Braking (AEB) systems, recognized as effective active safety technologies for collision avoidance and the mitigation of collision-related injuries, are gaining wider application in the automotive industry. To address the issues of the insufficient working reliability of AEB systems and their unsatisfactory level of accordance with the psychological expectations of drivers, this study proposes an optimized second-order Time to Collision (TTC) safety time algorithm based on the motion state of the preceding vehicle. Additionally, the study introduces a safety distance algorithm derived from an analysis of the braking process of the main vehicle. The safety time algorithm focusing on comfort and the safety distance algorithm focusing on safety are effectively integrated in the time domain and the space domain to obtain the safety time–safety distance fusion algorithm. A MATLAB/Simulink–Carsim joint simulation platform has been established to validate the AEB control strategy in terms of safety, comfort, and system responsiveness. The simulation results show that the proposed safety time–safety distance fusion algorithm consistently achieves complete collision avoidance, indicating a higher safety level for the AEB system. Furthermore, the application of active hierarchical braking minimizes the distance error, at under 0.37 m, which meets psychological expectations of drivers and improves the comfort of the AEB system. |
| Audience | Academic |
| Author | Fu, Xiang Ma, Wang Wan, Jiaqi Jiang, Wei Yang, Tianqi Wu, Daibing |
| Author_xml | – sequence: 1 givenname: Xiang surname: Fu fullname: Fu, Xiang – sequence: 2 givenname: Jiaqi surname: Wan fullname: Wan, Jiaqi – sequence: 3 givenname: Daibing surname: Wu fullname: Wu, Daibing – sequence: 4 givenname: Wei surname: Jiang fullname: Jiang, Wei – sequence: 5 givenname: Wang surname: Ma fullname: Ma, Wang – sequence: 6 givenname: Tianqi orcidid: 0000-0001-7755-5432 surname: Yang fullname: Yang, Tianqi |
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| Cites_doi | 10.1109/TITS.2019.2918176 10.1088/1757-899X/1275/1/012041 10.1016/j.simpat.2021.102450 10.3390/s19214671 10.1109/CoASE.2014.6899438 10.3390/electronics12163490 10.1109/TVT.2022.3222870 10.1109/SICE.2006.314777 10.1109/TITS.2023.3317095 10.1109/TITS.2023.3317361 10.1177/09544070211026191 10.3390/en15228382 10.3390/app132011352 |
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| SubjectTerms | Algorithms automotive engineering Autonomous Emergency Braking control system Braking Collision avoidance Collisions Comfort Controllers Fuzzy logic hierarchical braking control strategy Injury prevention Neural networks optimized second–order Time to Collision safety time algorithm safety distance algorithm Simulation methods System effectiveness System reliability Transportation equipment industry Travel Vehicles |
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