Evaluation of Transport Events with the use of Big Data, Artificial Intelligence and Augmented Reality techniques

Díez, Fernando; Sinca, Julià Cabrerizo; Vallès, David Roche; Cacheda, Jose Magin Campos

doi:10.1016/j.trpro.2021.11.024

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…From the point of view of urban form, the road network form as a whole should match the urban spatial form. From the same circle theory, the city is also a district, and box shot axis integration is high, good economic benefits, traffic demand, should be more bearing capacity supply [ 23 ]. The middle is the area often the land price highland, the proportion of road occupation is not likely to be too high, the difficulty of building higher grade roads, and thus the need for a much higher proportion of public transport sharing than other areas, the need for road space in as much as possible to plan the rail and other public transport facilities.…”

Section: Dynamic Balance Of Urban Road Land-use Planning Based On a N...mentioning

confidence: 99%

The Big Data Model for Urban Road Land Use Planning Is Based on a Neural Network Algorithm

Zhang

2022

Computational Intelligence and Neuroscience

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The spatial differentiation of land use induces traffic demand and guides the construction of traffic supply; traffic conditions are an important influencing factor in determining the nature of land use, and there is a close interaction between the two. This study uses a neural network-based approach at the urban grid level to portray representative phenomena of urban development and analyze the interaction between transportation and land use. The results reflect the model’s effective simulation of urban laws, and the case study reveals the differences in the laws of different cities, to guide the benign development of cities and transportation. This article firstly conducts a study on the theoretical foundation; compares the development history, planning, and design methods and practical experience of road planning and resilient planning; summarizes the experience of resilient road system design; and analyzes the future development trend, based on the above basic theoretical research, to develop research ideas and methods. Secondly, the scenario analysis method is explicitly applied to analyze various scenarios that may occur in the future development process of simulated urban roads and rank the scenarios based on the probability of occurrence. For the impact of traffic on land use, the concepts of vitality and potential are introduced, and a multidimensional long and short-term memory network (MDLSTM) model is established. The model takes into account land use lags and potential transfer and has relatively higher prediction accuracy. The results show that larger cities with urban dominant industries and tertiary industries also have higher land use potential and the more significantly influenced by traffic.

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Section: Dynamic Balance Of Urban Road Land-use Planning Based On a N...mentioning

confidence: 99%

The Big Data Model for Urban Road Land Use Planning Is Based on a Neural Network Algorithm

Zhang

2022

Computational Intelligence and Neuroscience

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A sustainable smart mobility? Opportunities and challenges from a big data use perspective

D’Alberto

Giudici

2023

Sustainable Futures

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Judicial Evaluation of Data from Artificial Intelligence Systems and Other Innovative Technologies in Transport

Печегин

2022

Transportation Research Procedia

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Evaluation of Transport Events with the use of Big Data, Artificial Intelligence and Augmented Reality techniques

Cited by 3 publications

References 11 publications

The Big Data Model for Urban Road Land Use Planning Is Based on a Neural Network Algorithm

The Big Data Model for Urban Road Land Use Planning Is Based on a Neural Network Algorithm

A sustainable smart mobility? Opportunities and challenges from a big data use perspective

Judicial Evaluation of Data from Artificial Intelligence Systems and Other Innovative Technologies in Transport

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