scholarly journals Visualization Method of TOD Development Process Based on Big Data

2021 ◽  
Vol 283 ◽  
pp. 02003
Author(s):  
Wang Youke
Keyword(s):  
Land Use ◽  
Big Data ◽  
Carbon Dioxide Emissions ◽  
Development Process ◽  
Rapid Development ◽  
Noise Pollution ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Visualization Method ◽  
Low Efficiency

With the rapid development of urbanization and motorization in China, the urban problems such as low-quality land spread and low efficiency of transportation are becoming increasingly prominent. It has become an effective method to solve the traffic and environment problems by using TOD theory, while mass rail transit has become the best carrier of TOD model. TOD is a powerful means to optimize land use, traffic development and urban planning, which provides a possibility for the organic combination of land use and traffic development. This paper mainly studies the visualization method of TOD development process based on big data. In TOD model of urban development guided by public transport, this paper studies and analyzes the planning points of TOD mode, and also studies the advantages, disadvantages, opportunities and threats of urban rail transit(URT) to prove the reliability of TOD development process. This paper studies the scale algorithm of rail transit network, and also analyzes the environmental pollution caused by various traffic modes and the land use ratio of TOD types by chart analysis. The experimental results show that the most important vehicle in cities is automobiles, while the energy consumption of Metro light rail is only 0.84, carbon dioxide emissions are 1.21 and noise pollution is 0.42. The pollution caused by it is the smallest, which is worth expanding. In terms of the proportion of type land, residential land is the core of neighborhood, accounting for 62.5%, while urban TOD is mainly used for core land, accounting for 55%. In the type land, different types of land use main functions are different.

scholarly journals Visual Analytic Method for Metro Anomaly Detection and Diffusion

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yunhui Li ◽  
Yong Zhang ◽  
He Shi ◽  
Yun Wei ◽  
Baocai Yin
Keyword(s):  
Traffic Management ◽  
Rapid Development ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Analytic Method ◽  
Visual Metaphor ◽  
Transit System ◽  
Passenger Flow ◽  
Anomalous Propagation ◽  
And Diffusion

With the rapid development of urbanization in recent years, thousands of people have flooded into the city, which has brought tremendous pressure on the supervision and operation of relevant traffic management departments. In particular, the unexpected events in the urban rail transit system have caused great troubles for city managers. Aiming at the problem of abnormal passenger flow in the metro, this paper proposes a visual analytic method to support the abnormal passenger flow detection, verification, and diffusion analysis in the metro system. The method provides an intuitive visual metaphor and allows users to perform simple interactive operations to verify abnormal passenger flow. In addition, the method reveals the diffusion law of abnormal passenger flow in time and space in a two-dimensional diffusion view. The Beijing Rail Transit AFC data are used to validate the developed system, and two reliable analysis cases are presented. The system can help users quickly grasp the abnormal propagation rules and help them to develop different scheduling strategies for different anomalous propagation paths.

Design for Urban Rail Transit Energy Efficiency Management System

2013 ◽  
Vol 749 ◽  
pp. 629-633
Author(s):  
Jian Bin Ye ◽  
Zhi Yan Ding ◽  
Qi Zhu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Management System ◽  
Rapid Development ◽  
Chinese Economy ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Service Architecture ◽  
Urban Rail ◽  
Emission Reduction Strategies

With the rapid development of Chinese economy and the speeding up urbanization, urban rail transit has entered a rapid development period, which results in more and more energy consumption. Meanwhile affected by energy source and environment factors, the state has implemented energy-saving emission reduction strategies in various fields, so energy efficient management for urban rail transit becomes more important. Based on the analysis of energy consumption problems in urban rail transit, the paper designs urban rail transit energy efficiency management system from the aspects of overall architecture, service architecture and application function, and provides technical support for the realization of the software system.

scholarly journals Prediction of Passenger Flow in Urban Rail Transit Based on Big Data Analysis and Deep Learning

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 142272-142279 ◽  
Author(s):  
Kaer Zhu ◽  
Ping Xun ◽  
Wei Li ◽  
Zhen Li ◽  
Ruochong Zhou
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Passenger Flow ◽  
Urban Rail

Adaptive Spectrum Management of Cognitive Radio in Intelligent Transportation System

2015 ◽  
Vol 743 ◽  
pp. 765-773 ◽  
Author(s):  
Cheng Wu ◽  
Y.M. Wang ◽  
Xiang Qiang ◽  
Z.Y. Zhang
Keyword(s):  
Cognitive Radio ◽  
Ad Hoc ◽  
Intelligent Transportation System ◽  
Environmental Changes ◽  
Rapid Development ◽  
Spectrum Management ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Value Functions ◽  
Urban Rail

With the rapid development of urban rail transit, the demand of the public in rail transportationto take real-time, reliable and efficient wireless access services, has become the focus of mobilebroadband communications. Wireless cognitive radio (CR) over urban rail transit is a newly emergingparadigm that attempts to opportunistically transmit in licensed frequencies, without affecting the preassignedusers of these bands. To enable this functionality, such a radio must predict its operationalparameters, such as transmit power and spectrum. These tasks, collectively called spectrum management,is difficult to achieve in a dynamic distributed environment, in which CR users may only takelocal decisions, and react to the environmental changes. In this paper, we propose a reinforcementlearning based approach for spectrum management. Our approach uses value functions to evaluate thedesirability of choosing different transmission parameters, and enables efficient assignment of spectrumsand transmit powers by maximizing long-term reward. We then investigate various real-worldscenarios, and compare the communication performance using different sets of learning parameters.The results proves our reinforcement learning based spectrum management can significantly reduceinterference to licensed users, while maintaining a high probability of successful transmissions in acognitive radio ad hoc network.

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