Abstract
This research explores the integration of lane and vehicle detection in autonomous vehicles using Model Predictive Control (MPC) with radar and camera sensors. The focus is on the concept of driving scene understanding, particularly object distance detection, crucial for safe decision-making. MPC, as an effective controller, utilizes lateral and longitudinal movements to keep the vehicle on the designated path. The goal is to create a responsive and reliable autonomous vehicle. Testing involves various environmental conditions, and the lane detection system proves effective but faces challenges when lane angles are undetected. Vehicle detection is fairly accurate, yet influenced by the brightness of the virtual environment and the limited accuracy of the ACF model. MPC can respond to detection results, although test outcomes differ from previous studies, showing increased error in X-axis position RMSE and improved performance in Y-axis position RMSE. Thus, this research presents an integrated solution to enhance the capabilities of autonomous vehicles in understanding and responding to their surrounding environment.
Original language | English |
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Title of host publication | 2024 International Seminar on Intelligent Technology and Its Applications |
Subtitle of host publication | Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 577-582 |
Number of pages | 6 |
Edition | 2024 |
ISBN (Electronic) | 9798350378573 |
DOIs | |
Publication status | Published - 2024 |
Event | 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 - Hybrid, Mataram, Indonesia Duration: 10 Jul 2024 → 12 Jul 2024 |
Conference
Conference | 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 |
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Country/Territory | Indonesia |
City | Hybrid, Mataram |
Period | 10/07/24 → 12/07/24 |
Keywords
- Autonomous Vehicles
- Detection Integration
- Driving Scene Understanding
- Model Predictive Control (MPC)
- Transportation Technology