Eco-Driving Level Evaluation Model for Electric Buses During Stop Entry and Exit

Abstract

This study presents an Eco-Driving Level Evaluation Model for Electric Buses Entering and Leaving Stops, aiming to improve energy efficiency, passenger comfort, and operational performance in urban public transportation systems. Frequent stopping and starting at bus stops significantly affect the energy consumption and battery performance of electric buses. Driving behaviors such as harsh acceleration, sudden braking, improper speed control, and inefficient stop positioning can lead to excessive power usage, reduced battery life, and lower passenger comfort. Therefore, evaluating and optimizing eco-driving behavior during bus stop operations is essential for sustainable transportation management.The proposed model analyzes key driving parameters such as acceleration, deceleration, speed variation, stopping distance, dwell time, and energy consumption during the entering and leaving phases of bus stops. Using sensor data, GPS tracking, and machine learning techniques, the system assesses driver behavior and classifies eco-driving levels based on efficiency and safety performance. The model helps transport operators identify inefficient driving patterns and provide feedback for driver improvement. The results support the development of intelligent transportation systems by promoting energy-saving driving strategies, reducing operational costs, and enhancing the overall performance of electric bus services.