Research on the Application of Artificial Intelligence Technology in the Field of Intelligent Transportation Systems

Chenyu Yu

doi:10.54097/vq5x9568

Authors

Chenyu Yu

DOI:

https://doi.org/10.54097/vq5x9568

Keywords:

Artificial intelligence, vehicle-to-everything, intelligent transportation systems.

Abstract

This research report provides a comprehensive investigation into the application of artificial intelligence (AI) in the context of autonomous driving technology within Intelligent Transportation Systems (ITS). Firstly, it offers an analysis of the technical aspects of autonomous driving technology. It then focuses on the development and research status of Intelligent Transportation Systems (ITS), with a particular emphasis on vehicle-to-vehicle (V2X) communication as a major AI application in connecting vehicles. The goal is to explore and evaluate the current application of AI technology in connected vehicles. The research investigates existing literature, research directions, methodologies, and case studies to assess the progress, challenges, and potential future developments in this field. Through this study, one can gain a comprehensive understanding of the research progress and practical applications of AI in various domains within the ITS context. This helps uncover the strengths, challenges, and future directions of AI technology in the ITS field, providing valuable insights and guidance for further research and advancements.

Downloads

Download data is not yet available.

References

H.T. (Noblis), E.S. (Noblis), K.W. (Noblis), C.B. (Noblis), B.H. (Kimley-H.D.G. (Kimley-H.K.O. (Cognium) Meenakshy Vasudevan (Noblis), Identifying Real-World Transportation Applications Using Artificial Intelligence (AI) Real-World AI Scenarios in Transportation for Possible Deployment (2020).

Smith et al., 2018. "In the context of traffic-related applications, ML has been successfully applied in areas like traffic prediction, intelligent traffic signal control, and driving assistance systems."

Chen et al., 2017. "ANNs have found extensive use in traffic flow prediction, vehicle detection and tracking, and traffic accident prediction."

LeCun et al., 2015. "DL hierarchically extracts high-level features and has proven to be highly effective in object and face recognition applications."

Liu et al., 2020. "NLP can extract information about road conditions and support real-time traffic navigation."

Zou et al., 2019. "Computer vision techniques enable object detection, scene understanding, and action recognition, while image analysis performs tasks like object tracking and segmentation."

Russell et al., 2022. "The advancements in AI have enabled systems to possess a wide range of functions. They can now sense and perceive the environment, reason and analyze information, learn from experience, adapt to new situations, make decisions, and communicate and take actions."

Li, X., & Zhang, Y. (2020). Application of artificial intelligence technology in intelligent transportation system. Journal of Advanced Transportation, 2020, 1 - 13.

Y.; Ahn, T.; Lee, C.; Kim, S.; Park, K. A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication. Sensors 2020, 20, 7022.

https://img1.baidu.com/it/u=3121842074,3159308431&fm=253&fmt=auto&app=138&f=JPEG?w=667&h=500.

https://developer.aliyun.com/article/64981?scm=20140722.184.2.173.