Development of Advanced Rider Assistance System (ARAS) for Electric Motorcycles: A Level-1 Collision Avoidance and Emergency Braking Prototype Using Ultrasonic Sensors

This paper presents the design, development, and validation of an Advanced Rider Assistance System (ARAS) for electric motorcycles, focused on a Level-1 collision avoidance and emergency braking prototype using ultrasonic sensors. The motivation stems from the disproportionate risk faced by two-wheeler riders and the current lack of widespread ARAS deployment compared to Advanced Driver Assistance Systems (ADAS) in cars. The proposed system addresses this gap by integrating front and rear ultrasonic sensors (operating at 40 kHz, with a detection range of 2 cm to 4 m and ±1% accuracy) to continuously monitor the proximity of obstacles in real time, even when the motorcycle is inclined up to 30°. Sensor data is processed by an embedded microcontroller (STM32 series), which executes a collision risk assessment algorithm based on measured distance and relative speed. When the distance to an obstacle falls below a configurable safety threshold (typically 3 m), the system initiates a multi-stage warning protocol: visual alerts (LED indicators), auditory signals (buzzer), and haptic feedback to the rider. If the rider fails to respond within 300 ms, the system automatically engages emergency braking via a solenoid actuator, modulating deceleration to a maximum of 0.6g to maintain stability and prevent wheel lock. The ARAS prototype was developed following a rigorous methodology: simulation of accident scenarios using IPG Motorcycle Maker, component selection and integration, and iterative hardware prototyping. Simulated and real-world tests under varied speeds (10–40 km/h) and lean angles demonstrated reliable object detection, timely warnings, and effective emergency braking intervention. Results indicated a 92% reduction in simulated rear-end collisions and an average system response time of 180 ms. The modular design also enables future integration of additional sensors and connectivity features for higher-level automation. This research demonstrates the feasibility and impact of low-cost, sensor-based ARAS solutions in enhancing electric motorcycle safety, paving the way for broader adoption and further innovation in rider protection technologies