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<p>Autonomous electric vehicles have become a focal point in the transportation sector due to their potential to revolutionize mobility. Despite significant progress, the challenge of optimizing vehicle drive control persists as a crucial barrier to unlock the full benefits of autonomous driving technology. The present research introduces a novel technique for improving autonomous vehicles’ energy economy and speed control. By considering the dynamics between a leading vehicle and a following vehicle, the main objective is to maximize both energy consumption and speed management. By adjusting its characteristics based on the following vehicle, the leading vehicle promotes safe driving practices and energy conservation. The research addresses driving behaviour and overall traffic flow, with a specific focus on speed and energy-saving control in vehicles. The proposed hybrid technique is a combination of both the variable velocity strategy osprey optimization algorithm and dynamic reinforcement remora optimization. Variable velocity strategy osprey optimization algorithm is employed to optimize energy utilization efficiency, while dynamic reinforcement remora optimization is utilized for predicting speed control on challenging terrains. The proposed technique’s implementation is carried out using PYTHON tool. Thus, the proposed strategy uses only 16.1 kWh per 100 km when compared to other conventional strategies.</p>

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Enhanced Energy Utilization Efficiency and Speed Control in Autonomous Electric Vehicles: A Velocity Reinforcement Based Hybrid Approach

  • 期刊论文

  • 发表日期：

    2025年7月14日

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  • K. B. Sri Sathya,
  • Kandasamy Sellamuthu,
  • P. Vasundradevi,
  • I. Baranilingesan,
  • N. Nandhini

摘要

Autonomous electric vehicles have become a focal point in the transportation sector due to their potential to revolutionize mobility. Despite significant progress, the challenge of optimizing vehicle drive control persists as a crucial barrier to unlock the full benefits of autonomous driving technology. The present research introduces a novel technique for improving autonomous vehicles’ energy economy and speed control. By considering the dynamics between a leading vehicle and a following vehicle, the main objective is to maximize both energy consumption and speed management. By adjusting its characteristics based on the following vehicle, the leading vehicle promotes safe driving practices and energy conservation. The research addresses driving behaviour and overall traffic flow, with a specific focus on speed and energy-saving control in vehicles. The proposed hybrid technique is a combination of both the variable velocity strategy osprey optimization algorithm and dynamic reinforcement remora optimization. Variable velocity strategy osprey optimization algorithm is employed to optimize energy utilization efficiency, while dynamic reinforcement remora optimization is utilized for predicting speed control on challenging terrains. The proposed technique’s implementation is carried out using PYTHON tool. Thus, the proposed strategy uses only 16.1 kWh per 100 km when compared to other conventional strategies.