<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This article delves into the impact of intelligence (AI), on easing traffic congestion as cities strive to become more intelligent. It highlights advancements in AI technologies like networks (ANNs) and genetic algorithms (GAs), within the context of urban transportation and movement. The incorporation of intelligence, into transportation systems is motivated by the necessity to adapt to evolving circumstances while emphasizing improvements, in the effectiveness and environmental friendliness of transportation networks. Mobility as a Service (MaaS) combines options like transit, ride-sharing and bike rentals. Through the use of networks AI enhances urban traffic management by predicting congestion and optimizing traffic signal control at intersections. Genetic algorithms play a role, in optimizing vehicle routes by taking into account variables such as travel time and associated expenses. The research indicates a rise in the use of AI in the transportation industry signaling a change, in commuting patterns. This study highlights the significance of progressing AI technologies to meet changing infrastructure requirements and fluctuating traffic trends emphasizing the impact of AI on shaping the urban transportation landscape.</p>
</abstract>

This article delves into the impact of intelligence (AI), on easing traffic congestion as cities strive to become more intelligent. It highlights advancements in AI technologies like networks (ANNs) and genetic algorithms (GAs), within the context of urban transportation and movement. The incorporation of intelligence, into transportation systems is motivated by the necessity to adapt to evolving circumstances while emphasizing improvements, in the effectiveness and environmental friendliness of transportation networks. Mobility as a Service (MaaS) combines options like transit, ride-sharing and bike rentals. Through the use of networks AI enhances urban traffic management by predicting congestion and optimizing traffic signal control at intersections. Genetic algorithms play a role, in optimizing vehicle routes by taking into account variables such as travel time and associated expenses. The research indicates a rise in the use of AI in the transportation industry signaling a change, in commuting patterns. This study highlights the significance of progressing AI technologies to meet changing infrastructure requirements and fluctuating traffic trends emphasizing the impact of AI on shaping the urban transportation landscape.

Smart Urban Mobility: The Role of AI in Alleviating Traffic Congestion

Proceedings of the International Conference on Business Excellence

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Smart Urban Mobility: The Role of AI in Alleviating Traffic Congestion"}

This article delves into the impact of intelligence (AI), on easing traffic congestion as cities strive to become more intelligent. It highlights advancements...

Smart Urban Mobility: The Role of AI in Alleviating Traffic Congestion

Online veröffentlicht: 03. Juli 2024

Seitenbereich: 1441 - 1452

DOI: https://doi.org/10.2478/picbe-2024-0118

Schlüsselwörter
reducing traffic congestion, smart city solutions, artificial intelligence-based urban planning, motivating urban mobility, artificial intelligence in transport, intelligent transport systems

© 2024 Mihai Adrian Lungu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Smart Urban Mobility: The Role of AI in Alleviating Traffic Congestion

Online veröffentlicht: 03. Juli 2024

Seitenbereich: 1441 - 1452

DOI: https://doi.org/10.2478/picbe-2024-0118

Schlüsselwörterreducing traffic congestion, smart city solutions, artificial intelligence-based urban planning, motivating urban mobility, artificial intelligence in transport, intelligent transport systems

© 2024 Mihai Adrian Lungu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
reducing traffic congestion, smart city solutions, artificial intelligence-based urban planning, motivating urban mobility, artificial intelligence in transport, intelligent transport systems