2024Highlights in Science Engineering and TechnologyOpen access

The Application of Artificial Intelligence in Intelligent Transportation System

Yibo Zhao

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Abstract

Intelligent transportation systems are an important research direction in the field of transportation, offering safer, more efficient, and sustainable transportation solutions. AI, as a powerful technological tool, has demonstrated remarkable achievements in various domains. In the context of intelligent transportation, the application of AI is gaining increasing attention and expectation. Its powerful capabilities in data processing, analysis, intelligent decision-making, and autonomous control bring profound changes to the transportation system. The objective of this research is to examine the implementation of artificial intelligence (AI) in intelligent transportation and investigate its potential impact on the transportation system. This study first defines AI in the context of intelligent transportation and identifies AI sub-branches with potential applications in intelligent transportation systems. It then reviews the development of ITS and the challenges they face. Lastly, based on a literature review, an advanced overview of current and possible applications that utilize artificial intelligence in automated driving systems and transportation systems management and operations is provided. The analysis reveals that AI technologies can accurately predict traffic flow, optimize signal control in real time, and achieve highly automated driving. These results demonstrate the potential advantages and application value of AI in intelligent transportation. The application of AI in intelligent transportation systems holds immense potential for providing safer, more efficient, and sustainable transportation solutions. This research provides a new perspective and solution approach to the advancement of ITS. The application of AI in the realm of intelligent transportation can positively impact the operational efficiency, traffic safety, and environmental sustainability of transportation systems.

About this research paper

What this paper is about

Intelligent transportation systems are an important research direction in the field of transportation, offering safer, more efficient, and sustainable transportation solutions. AI, as a powerful technological tool, has demonstrated remarkable achievements in various domains. In the context of intelligent transportation, the application of AI is gaining increasing attention and expectation. Its powerful capabilities in data processing, analysis, intelligent decision-making, and autonomous control bring profound changes to the transportation system. The objective of this research is to examine the implementation of artificial intelligence (AI) in intelligent transportation and investigate its potential impact on the transportation system. This study first defines AI in the context of intelligent transportation and identifies AI sub-branches with potential applications in intelligent transportation systems. It then reviews the development of ITS and the challenges they face. Lastly, based on a literature review, an advanced overview of current and possible applications that utilize artificial intelligence in automated driving systems and transportation systems management and operations is provided. The analysis reveals that AI technologies can accurately predict traffic flow, optimize signal control in real time, and achieve highly automated driving. These results demonstrate the potential advantages and application value of AI in intelligent transportation. The application of AI in intelligent transportation systems holds immense potential for providing safer, more efficient, and sustainable transportation solutions. This research provides a new perspective and solution approach to the advancement of ITS. The application of AI in the realm of intelligent transportation can positively impact the operational efficiency, traffic safety, and environmental sustainability of transportation systems.

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Available abstract

Intelligent transportation systems are an important research direction in the field of transportation, offering safer, more efficient, and sustainable transportation solutions. AI, as a powerful technological tool, has demonstrated remarkable achievements in various domains. In the context of intelligent transportation, the application of AI is gaining increasing attention and expectation. Its powerful capabilities in data processing, analysis, intelligent decision-making, and autonomous control bring profound changes to the transportation system. The objective of this research is to examine the implementation of artificial intelligence (AI) in intelligent transportation and investigate its potential impact on the transportation system. This study first defines AI in the context of intelligent transportation and identifies AI sub-branches with potential applications in intelligent transportation systems. It then reviews the development of ITS and the challenges they face. Lastly, based on a literature review, an advanced overview of current and possible applications that utilize artificial intelligence in automated driving systems and transportation systems management and operations is provided. The analysis reveals that AI technologies can accurately predict traffic flow, optimize signal control in real time, and achieve highly automated driving. These results demonstrate the potential advantages and application value of AI in intelligent transportation. The application of AI in intelligent transportation systems holds immense potential for providing safer, more efficient, and sustainable transportation solutions. This research provides a new perspective and solution approach to the advancement of ITS. The application of AI in the realm of intelligent transportation can positively impact the operational efficiency, traffic safety, and environmental sustainability of transportation systems.

Key concepts: Intelligent transportation system, Advanced Traffic Management System, SAFER, Intelligent decision support system, Context (archaeology), Computer science, Intelligent agent, Sustainable transport

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