Modeling and Simulation of Intelligent Vehicle Systems Using Simulink and MATLAB Programming for Advanced Automotive Application

This article explores the design and simulation of intelligent vehicle systems using MATLAB and Simulink, focusing on applications essential for autonomous driving technologies. Key systems include DC motor speed control and collision avoidance. The study employs Simulink for system modeling and MATLAB functions for implementing control algorithms, creating an integrated framework for testing and validation. For DC motor speed control, a PI controller is used to ensure stability and precision, while the collision avoidance system utilizes sensor data and logic to prevent accidents by dynamically adjusting motor operation. These technologies highlight the role of control systems in enhancing vehicle safety, reliability, and performance, addressing challenges in intelligent transportation systems. This work demonstrates the potential of MATLAB and Simulink as effective tools for advancing autonomous vehicle technology and improving overall traffic safety and efficiency.

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Publication Details

Published
2025-03-28
DOI
https://doi.org/10.1109/iccai66501.2025.00100
Citations
1
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.68
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article

Modeling and Simulation of Intelligent Vehicle Systems Using Simulink and MATLAB Programming for Advanced Automotive Application

Xufeng Ling, Wenjun Guo, Yan He
1 citations
Autonomous Vehicle Technology and Safety
0.68
article

Modeling and Simulation of Intelligent Vehicle Systems Using Simulink and MATLAB Programming for Advanced Automotive Application

Xufeng Ling, Wenjun Guo, Yan He
article en
1 citations

Abstract

This article explores the design and simulation of intelligent vehicle systems using MATLAB and Simulink, focusing on applications essential for autonomous driving technologies. Key systems include DC motor speed control and collision avoidance. The study employs Simulink for system modeling and MATLAB functions for implementing control algorithms, creating an integrated framework for testing and validation. For DC motor speed control, a PI controller is used to ensure stability and precision, while the collision avoidance system utilizes sensor data and logic to prevent accidents by dynamically adjusting motor operation. These technologies highlight the role of control systems in enhancing vehicle safety, reliability, and performance, addressing challenges in intelligent transportation systems. This work demonstrates the potential of MATLAB and Simulink as effective tools for advancing autonomous vehicle technology and improving overall traffic safety and efficiency.

Aston University (GB), Shanghai Normal University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 27%
Autonomous Vehicle Technology and Safety
0.68
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Modeling and Simulation of Intelligent Vehicle Systems Using Simulink and MATLAB Programming for Advanced Automotive Application — Xufeng Ling, Wenjun Guo, et al. · (2025) | TGRS Research Map | TGRS