Dynamic pricing techniques for Intelligent Transportation System in smart cities: A systematic review

2020 ◽  
Vol 150 ◽  
pp. 603-625 ◽  
Author(s):  
Sandeep Saharan ◽  
Seema Bawa ◽  
Neeraj Kumar
Keyword(s):  
Systematic Review ◽  
Dynamic Pricing ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System

scholarly journals The key factors in transforming Birjand city to a smart city: smart mobility, smart government

2020 ◽  
Vol 19 (1) ◽  
pp. 317 ◽  
Author(s):  
Amirhossein Ghasemi ◽  
Mohsen Saberi
Keyword(s):  
Strategic Planning ◽  
Transport System ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Intelligent Transport System ◽  
Key Factors ◽  
Intelligent Transport ◽  
Smart Government

The physical development of urban communities and cities, as well as the advancement of communication and information world, increased the need for advanced technologies. Nowadays, many urban planners and managers, especially the mangers of the intelligent transport system and smart government, are concerned with the transformation of physical cities to electronic cities and finally too smart cities in the real world. Making electronic cities smart requires the full participation of urban management organizations in different sectors. In addition, the required frameworks should be designed and implemented based on the close relations of these organizations with each other. This study aimed to investigate the key factors in transforming Birjand city into a smarter city by focusing on two components of the intelligent transport system and smart government. In smart government, a structure is recommended that is appropriate for launching and preparing the policies and regulations that need to be covered by different dimensions. In smart transportation component, one of the most important and valuable solutions to the problems of transportation is the intelligent transport system (ITS).  In this context, measuring potentials and implementing strategic planning can play a key role in increasing service delivery and reducing problems. This research design is an applied study. It intends to introduce the principles and dimensions of the intelligent transportation system and explore the potentials and strategic planning opportunities in Birjand city using a descriptive-analytical method. The data were collected by the library - documentary method. Furthermore, the study was conducted as field-survey research (interviews and questionnaires). In continuation, the strengths and weaknesses, opportunities and threats (SWOT) of the intelligent transportation system were determined and analyzed using the SWOT strategic planning model. Finally, appropriate strategies were presented.

scholarly journals The Application of Virtual Reality Technology on Intelligent Traffic Construction and Decision Support in Smart Cities

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Gongxing Yan ◽  
Yanping Chen
Keyword(s):  
Big Data ◽  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
The Other ◽  
The City

The core of smart city is to build intelligent transportation system.. An intelligent transportation system can analyze the traffic data with time and space characteristics in the city and acquire rich and valuable knowledge, and it is of great significance to realize intelligent traffic scheduling and urban planning. This article specifically introduces the extensive application of urban transportation infrastructure data in the construction and development of smart cities. This article first explains the related concepts of big data and intelligent transportation systems and uses big data to illustrate the operation of intelligent transportation systems in the construction of smart cities. Based on the machine learning and deep learning method, this paper is aimed at the passenger flow and traffic flow in the smart city transportation system. This paper deeply excavates the time, space, and other hidden features. In this paper, the traffic volume of the random sections in the city is predicted by using the graph convolutional neural network (GCNN) model, and the data are compared with the other five models (VAR, FNN, GCGRU, STGCN, and DGCNN). The experimental results show that compared with the other 4 models, the GCNN model has an increase of 8% to 10% accuracy and 15% fault tolerance. In forecasting morning and evening peak traffic flow, the accuracy of the GCNN model is higher than that of other models, and its trend is basically consistent with the actual traffic volume, the predicted results can reflect the actual traffic flow data well. Aimed at the application of intelligent transportation in an intelligent city, this paper proposes a machine learning prediction model based on big data, and this is of great significance for studying the mechanical learning of such problems. Therefore, the research of this paper has a good implementation prospect and academic value.

Intelligent Transportation System in Smart Cities (ITSSC)

2018 ◽  
pp. 1157-1170
Author(s):  
Sondos Dahbour ◽  
Raghad Qutteneh ◽  
Yara Al-Shafie ◽  
Iyad Tumar ◽  
Yousef Hassouneh ◽  
...  
Keyword(s):  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System

Dynamic Pricing for Intelligent Transportation System in the 6G Unlicensed Band

2021 ◽  
pp. 1-16
Author(s):  
Rojeena Bajracharya ◽  
Rakesh Shrestha ◽  
Syed Ali Hassan ◽  
Kostromitin Konstantin ◽  
Haejoon Jung
Keyword(s):  
Dynamic Pricing ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Unlicensed Band

Cognitive Intelligent Transportation System for Smart Cities

2018 ◽  
Author(s):  
Gunasekaran Raja ◽  
Aishwarya Ganapathisubramaniyan ◽  
Madhumitha Sri Selvakumar ◽  
Thiruveni Ayyarappan ◽  
Karthikeyan Mahadevan
Keyword(s):  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System
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