Analysis and Prediction of Urban Traffic Congestion Based on Big Data

Wang, Zhenhua; Yu, Yangsen; Ju, Dangchen

doi:10.11648/j.ijdst.20180403.14

Cited by 10 publications

(5 citation statements)

References 9 publications

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“…Based on the collection of previous big data, the application of blockchain technology, the correlation between products, the reorganization of visual system, and the mining of product form, product AI can realize visualization, thinking, and automation, and generate product veins of different sources and structures independently by intelligent system [16]. The production process and marketing path to achieve automatic, recyclable, sustainable, green product production, before, during and after the use of products to adapt to product functions and solve the corresponding problems.…”

Section: Product Artificial Intelligence Visual Design Systemmentioning

confidence: 99%

Multiple Roles of Big Data Platform and Artificial Intelligence Architecture

Zhang

2023

Advances in Transdisciplinary Engineering

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Multi-role and artificial intelligence have gradually pushed the industry to a new stage of “human-machine integration” and “role intelligence”. Methods: Based on the big data platform, the feasibility of artificial intelligence and multiple roles of products was studied, and artificial intelligence and multiple roles provided intelligent interaction opportunities for the social production and visual dissemination of product knowledge system. Content: The construction of products by big data platform can realize the collaborative production of intelligent machines and professional designers, and multi-role interaction can realize the new dynamic level of knowledge of copywriting planning, visual design, structure generation and function reconstruction. As the artificial intelligence matching users and designers, the product big data platform has dynamic connection and interaction, which can further promote the hierarchical transformation of the knowledge system of users and designers from independent thinking to diversified vision, and from broad connection to multi-dimensional connection. The multi-role and artificial intelligence architecture can aggregate the multi-dynamic and interactive freedom of the product’s main content economy, assets and culture in the upstream and downstream, as well as the traceable flow information of the big data platform, thus bringing the increment of the product’s internal and external stock content and the value increment of the asset. Results: The product big data platform further proposed to build a “human-machine integration” and “role intelligence” data system with multi-role communication foreground, artificial intelligence knowledge center and blockchain technology background as the core.

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Section: Product Artificial Intelligence Visual Design Systemmentioning

confidence: 99%

Multiple Roles of Big Data Platform and Artificial Intelligence Architecture

Zhang

2023

Advances in Transdisciplinary Engineering

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“…The use of technologies, such as cloud computing and edge computing, could be considered. Using Big Data technology to gather traffic data of an entire city, practical data can be provided for guiding traffic and urban planning, which could solve problems related to traffic congestion analysis, traffic flow prediction, and wise planning of transportation infrastructure (Wang et al, 2018).…”

Section:  Managing Huge Amounts Of Datamentioning

confidence: 99%

Intelligent Traffic Management: A Review of Challenges, Solutions, and Future Perspectives

Ravish

Swamy²

2021

Transport and Telecommunication Journal

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Recent years have witnessed a colossal increase of vehicles on the roads; unfortunately, the infrastructure of roads and traffic systems has not kept pace with this growth, resulting in inefficient traffic management. Owing to this imbalance, traffic jams on roads, congestions, and pollution have shown a marked increase. The management of growing traffic is a major issue across the world. Intelligent Transportation Systems (ITS) have a great potential in offering solutions to such issues by using novel technologies. In this review, the ITS-based solutions for traffic management and control have been categorized as traffic data collection solutions, traffic management solutions, congestion avoidance solutions, and travel time prediction solutions. The solutions have been presented along with their underlying technologies, advantages, and drawbacks. First, important solutions for collecting traffic-related data and road conditions are discussed. Next, ITS solutions for the effective management of traffic are presented. Third, key strategies based on machine learning and computational intelligence for avoiding congestion are outlined. Fourth, important solutions for accurately predicting travel time are presented. Finally, avenues for future work in these areas are discussed.

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“…[10] By analyzing data collected from simulation tools, the project seeks to identify bottlenecks and propose data-driven suggestions to improve traffic flow on specific routes. [11] The integration of LLMs offers a novel approach to understanding and managing urban traffic, providing a sophisticated analysis that can dynamically adapt to changing traffic patterns and predict potential congestion points before they become critical.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Urban Mobility through Adaptive Traffic Analysis: A Case Study in Singapore

Mohor,

Somasundaram,

Ronak

et al. 2024

Preprint

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Traffic congestion is a significant issue in most urban landscapes, causing delays and affecting the daily commutes of thousands. This study, "Adaptive Traffic Learning and Analysis System" seeks to leverage the capabilities of Large Language Models (LLMs) to analyze data from urban traffic systems and provide detailed insights into congestion points. By using the Simulation of Urban MObility (SUMO) software, we replicate street layouts and traffic signals for specific locations in Singapore, facilitating real-time traffic simulations. The project employs SUMO’s APIs to extract vehicle positioning information, which is then used to compute traffic flow statistics. These insights enable LLMs to propose informed optimizations for traffic management, aiding urban planners and traffic managers in decision-making. The recommendations can be further evaluated and refined using SUMO, aiming to mitigate traffic congestion and improve urban mobility in Singapore.

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Analysis and Prediction of Urban Traffic Congestion Based on Big Data

Cited by 10 publications

References 9 publications

Multiple Roles of Big Data Platform and Artificial Intelligence Architecture

Multiple Roles of Big Data Platform and Artificial Intelligence Architecture

Intelligent Traffic Management: A Review of Challenges, Solutions, and Future Perspectives

Enhancing Urban Mobility through Adaptive Traffic Analysis: A Case Study in Singapore

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