Research on autonomous driving technology in intelligent transportation systems

Abstract. The convergence of scientific and technological advancement with the acceleration of urbanization has resulted in a notable intensification of the issue of traffic congestion. In this context, the development of autonomous driving technology has emerged as a pivotal area of focus for future transportation systems. Therefore, this paper presents a review of the current status of automatic driving technology in intelligent transportation systems, based on methods such as literature, data analysis and case studies. Furthermore, it delves into the evolution, applications, challenges and solutions of automated driving technologies in intelligent transport systems, and presents forward-thinking insights into the future development of intelligent transportation. As autonomous driving technology continues to evolve, the integration of deep reinforcement learning and other advanced technologies will facilitate the advancement of intelligent vehicle human-machine collaborative decision-making technology. It is imperative that the construction technology of safety-critical scenarios be reinforced in order to enhance the interpretability of algorithmic models and the real-time nature of scenario generation. All parties need to collaborate to promote the innovation and improvement of autonomous driving technology, achieve widespread application and sustainable development, and create a better travelling environment.

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Publication Details

Journal
Applied and Computational Engineering
Published
2024-11-08
DOI
https://doi.org/10.54254/2755-2721/102/20241007
Citations
2
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.53
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article

Research on autonomous driving technology in intelligent transportation systems

S. Z. Zheng
2 citations
Applied and Computational Engineering
Traffic Prediction and Management Techniques
0.53
article

Research on autonomous driving technology in intelligent transportation systems

S. Z. Zheng
article en
2 citations

Abstract

Abstract. The convergence of scientific and technological advancement with the acceleration of urbanization has resulted in a notable intensification of the issue of traffic congestion. In this context, the development of autonomous driving technology has emerged as a pivotal area of focus for future transportation systems. Therefore, this paper presents a review of the current status of automatic driving technology in intelligent transportation systems, based on methods such as literature, data analysis and case studies. Furthermore, it delves into the evolution, applications, challenges and solutions of automated driving technologies in intelligent transport systems, and presents forward-thinking insights into the future development of intelligent transportation. As autonomous driving technology continues to evolve, the integration of deep reinforcement learning and other advanced technologies will facilitate the advancement of intelligent vehicle human-machine collaborative decision-making technology. It is imperative that the construction technology of safety-critical scenarios be reinforced in order to enhance the interpretability of algorithmic models and the real-time nature of scenario generation. All parties need to collaborate to promote the innovation and improvement of autonomous driving technology, achieve widespread application and sustainable development, and create a better travelling environment.

Applied and Computational EngineeringVol. 102(1)
Nanjing University of Science and Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 33%
Traffic Prediction and Management Techniques
0.53
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