Design of an Adaptive Cruise Control System using PID Control Method on Electric Vehicle Prototypes

• Published in: 2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA) pp. 599 - 605
• Main Authors: Saputro, Joko Slamet, Kresno Wibisono, M. Shafiy Widi, Hariyono, Joko, Anwar, Miftahul, Warindi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.11.2023
• Subjects: Adaptive Cruise Control; Cruise control; Electric Vehicle; Electric vehicles; PD control; PI control; PID; Safe Distance; Sensors; Speed Adjustment; System Response; Testing; Vehicles
• ISSN: 2832-8353
• DOI: 10.1109/ICAMIMIA60881.2023.10427856

The use of Internal Combustion Engine (ICE) vehicles is still dominant in Indonesia due to easy access to petroleum-based fuels, but it has adverse effects on the environment. Vehicles are not only used for intra-city travel but also for long distances, increasing the risk of accidents as drivers may lose focus due to fatigue. To address this issue, environmentally friendly vehicles such as electric vehicles equipped with safety features to assist drivers are required. One such feature is Adaptive Cruise Control (ACC), which helps drivers reduce speed and stop the vehicle when approaching other vehicles to avoid collisions. This research focuses on implementing LiDAR sensors to detect the distance between vehicles in the Adaptive Cruise Control system using PID control method as an additional feature in an electric vehicle prototype. The ACC system uses an algorithm that automatically performs vehicle speed adjustment based on the distance detected by the sensors. The ACC system will work based on the given input speed and adjust the safe distance as well as the minimum distance from the given input speed. The TFMini-Plus LiDAR sensor is used, and the tests show that this sensor has a high accuracy of 98.43%, with an error value of 1.57%. The performance testing of the ACC system shows that it functions according to the specified algorithm. The system is also able to respond well to new objects, with an average rise time of less than 2 seconds, overshoot less than 3%, and settling time less than 12 seconds. However, there are several faults in the encoder's readings of speed changes, leading to suboptimal analysis of the system's response.