Cameraless sensor fusion: developing a cost-effective driver assistance system using radar and ultrasonic sensor

Purpose This paper aims to develop a cost-effective, camera-less advanced driver assistance system (ADAS) for electric vehicles. It will use sensor fusion of ultrasonic and radar sensors to implement adaptive cruise control (ACC), blind spot detection (BSD) and reverse parking (RP). Design/methodology/approach The system was tested on an electric vehicle test bench, using strategically placed ultrasonic and radar sensors. Sensor fusion enabled accurate object detection and distance measurement. The system’s performance was evaluated through simulated obstacle scenarios, with responses monitored via a graphical user interface. Sensor and GPS data were transmitted to the cloud for potential vehicle-to-vehicle communication. Findings The sensor fusion approach effectively supported ACC, BSD and RP functions, demonstrating accuracy in obstacle detection, speed adjustment and emergency braking. The real-time system visualization confirmed reliability across various scenarios and cloud integration showed promise for future communication enhancements. Research limitations/implications Ultrasonic and radar sensors have limited range and accuracy compared to cameras. Ultrasonic sensors are less effective at longer distances and in adverse weather conditions, whereas radar can face challenges in detecting small or stationary objects. Sensor performance can be affected by environmental factors such as rain, fog or snow, which may reduce the effectiveness of both ultrasonic and radar sensors. Sensor performance can be affected by environmental factors such as rain, fog or snow, which may reduce the effectiveness of both ultrasonic and radar sensors. Practical implications Improved obstacle detection and collision avoidance contribute to overall vehicle safety. Drivers benefit from advanced features like ACC, BSD and RP without the high cost of traditional camera-based systems. The use of ultrasonic and radar sensors makes advanced driver assistance features more affordable, allowing broader adoption across various vehicle segments, including budget-friendly and mid-range models. The system’s responsiveness and obstacle detection capabilities can lead to more efficient driving, reducing the likelihood of accidents and improving traffic flow. Social implications Enhanced safety features such as ACC, BSD and RP contribute to reducing traffic accidents and injuries. By making advanced driver assistance features more affordable, the system improves vehicle safety for a broader range of drivers, including those in lower-income brackets. The introduction of such systems can raise public awareness about the benefits of ADAS technologies and their role in enhancing road safety. Originality/value This study introduces a novel ADAS system that eliminates the need for cameras by leveraging the strengths of radar and ultrasonic sensors. The approach offers a practical and innovative solution for enhancing vehicle safety at a reduced cost.