自动驾驶汽车：人工智能与学习算法的进化之旅（2024）（英文版）（13页）.pdf

1、1Autonomous Vehicles:Evolution of Artifi cialIntelligence and Learning AlgorithmsDivya Garikapati,Senior Member,IEEE,Sneha Sudhir Shetiya,Senior Member,IEEEAbstractThe advent of autonomous vehicles has heralded atransformative era in transportation,reshaping the landscape ofmobility through cutting-

2、edge technologies.Central to this evolu-tion is the integration of Artificial Intelligence(AI)and learningalgorithms,propelling vehicles into realms of unprecedentedautonomy.This paper provides a comprehensive exploration ofthe evolutionary trajectory of AI within autonomous vehicles,tracing the jou

3、rney from foundational principles to the mostrecent advancements.Commencing with a current landscape overview,the paperdelves into the fundamental role of AI in shaping the autonomousdecision-making capabilities of vehicles.It elucidates the stepsinvolved in the AI-powered development life cycle in

4、vehicles,addressing ethical considerations and bias in AI-driven softwaredevelopment for autonomous vehicles.The study presents statis-tical insights into the usage and types of AI/learning algorithmsover the years,showcasing the evolving research landscape withinthe automotive industry.Furthermore,

5、the paper highlights thepivotal role of parameters in refining algorithms for both trucksand cars,facilitating vehicles to adapt,learn,and improveperformance over time.It concludes by outlining different levelsof autonomy,elucidating the nuanced usage of AI and learningalgorithms,and automating key

6、tasks at each level.Additionally,the document discusses the variation in software package sizesacross different autonomy levels.Index TermsArtificial Intelligence(AI),Machine Learning(ML),Deep Neural Networks(DNNs),Natural Language Process-ing(NLP),Autonomous Vehicles(AVs),Safety,Security,Ethics,Eme