Jing Niu, Chuanyan Shen, Jiapei Wei, Shifeng Liu, Cheng Lin
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引用次数: 0
Abstract
INTRODUCTION: To solve the problems of low quality and weak global optimization of the DWA algorithm, especially the problems of unreasonable path planning and the inability to give consideration to speed and driving safety in the process of vehicles passing through dense obstacles, this paper proposed an improved DWA algorithm based on ant colony algorithm.
OBJECTIVES: The traffic capacity and computing efficiency of Self-driving Vehicles in complex dense obstacles can be greatly improved.
METHODS: Through the obstacle density and distance information obtained by high-precision sensors on the vehicle, the speed objective function is updating in real time by using ant colony algorithm. And the maneuverability and safety performance of vehicles passing through are considering by the way.
RESULTS: The experimental results show that this method can obviously improve the vehicle's traveling ability and uneven path planning in the case of dense obstacles, and the number of iterations of the algorithm is reduced by more than 16%.
CONCLUSION: The improved DWA algorithm integrated with the ant colony algorithm can effectively improve the operating efficiency of the algorithm, reduce the distance the car must go around outside the obstacles, and improve Car driving safety. The effectiveness and universality of the improved DWA algorithm were verified through experiments.
简介：为解决DWA算法质量不高、全局优化能力弱的问题，特别是车辆通过密集障碍物过程中路径规划不合理、无法兼顾速度和行车安全等问题，本文提出了一种基于蚁群算法的改进DWA算法。目标：大幅提高自动驾驶汽车在复杂密集障碍物中的通行能力和计算效率。方法：通过车辆上高精度传感器获取的障碍物密度和距离信息，利用蚁群算法实时更新速度目标函数。同时考虑车辆通过时的机动性和安全性能。结果：实验结果表明，该方法能明显改善车辆的行驶能力和密集障碍物情况下的不均匀路径规划，算法迭代次数减少了 16% 以上。结论：与蚁群算法相结合的改进型 DWA 算法能有效提高算法的运行效率，减少汽车在障碍物外的绕行距离，提高汽车行驶的安全性。通过实验验证了改进的 DWA 算法的有效性和通用性。
期刊介绍：
With ICT pervading everyday objects and infrastructures, the ‘Future Internet’ is envisioned to undergo a radical transformation from how we know it today (a mere communication highway) into a vast hybrid network seamlessly integrating knowledge, people and machines into techno-social ecosystems whose behaviour transcends the boundaries of today’s engineering science. As the internet of things continues to grow, billions and trillions of data bytes need to be moved, stored and shared. The energy thus consumed and the climate impact of data centers are increasing dramatically, thereby becoming significant contributors to global warming and climate change. As reported recently, the combined electricity consumption of the world’s data centers has already exceeded that of some of the world''s top ten economies. In the ensuing process of integrating traditional and renewable energy, monitoring and managing various energy sources, and processing and transferring technological information through various channels, IT will undoubtedly play an ever-increasing and central role. Several technologies are currently racing to production to meet this challenge, from ‘smart dust’ to hybrid networks capable of controlling the emergence of dependable and reliable green and energy-efficient ecosystems – which we generically term the ‘energy web’ – calling for major paradigm shifts highly disruptive of the ways the energy sector functions today. The EAI Transactions on Energy Web are positioned at the forefront of these efforts and provide a forum for the most forward-looking, state-of-the-art research bringing together the cross section of IT and Energy communities. The journal will publish original works reporting on prominent advances that challenge traditional thinking.
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