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.

scholarly journals Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6309
Author(s):  
Mohammad Peyman ◽  
Pedro J. Copado ◽  
Rafael D. Tordecilla ◽  
Leandro do C. Martins ◽  
Fatos Xhafa ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Edge Computing ◽  
Analytical Models ◽  
Current Status ◽  
Ride Sharing ◽  
The City

With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens’ mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours, and to make decisions that increase the efficiency of the transportation system. It involves many challenges such as how to deal and manage real and huge amounts of data, and improving security, privacy, scalability, reliability, and quality of services in the cloud and vehicular network. In this paper, we review the state of the art of IoT in intelligent transportation systems (ITS), identify challenges posed by cloud, fog, and edge computing in ITS, and develop a methodology based on agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing.These algorithms allow us to process, in real time, the data gathered from IoT systems in order to optimize automatic decisions in the city transportation system, including: optimizing the vehicle routing, recommending customized transportation modes to the citizens, generating efficient ride-sharing and car-sharing strategies, create optimal charging station for electric vehicles and different services within urban and interurban areas. A numerical example considering a DRSP is provided, in which the potential of employing edge/fog computing, open data, and agile algorithms is illustrated.

scholarly journals Traffic Big Data in the Development of Intelligent Transportation System

2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Qiang Shi ◽  
Lei Wang ◽  
Taojie Wang
Keyword(s):  
Big Data ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Paper Briefly ◽  
System A ◽  
Basic Characteristics

With the continuous development and advancement of computer technology, big data guarantees the establishment of an urban intelligent transportation system, a solid environmental basis to reform its application, and the construction of a deeply integrated data mechanism for big data-driven traffic management. This review paper briefly elaborates on the basic characteristics and sources of traffic big data as well as expound on the problems and application mechanisms of big data in intelligent transportation systems.

Study on Path Optimization Method of Traffic Guidance System under the Condition of the Car Networking

2014 ◽  
Vol 624 ◽  
pp. 567-570
Author(s):  
Dan Ping Wang ◽  
Kun Yuan Hu
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
System Integration ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Guidance System ◽  
Wide Range ◽  
Computer Communication Network

Intelligent Transportation System is the primary means of solving the city traffic problem. The information technology, the communication, the electronic control technology and the system integration technology and so on applies effectively in the transportation system by researching rationale model, thus establishes real-time, accurate, the highly effective traffic management system plays the role in the wide range. Traffic flow guidance system is one of cores of Intelligent Transportation Systems. It is based on modern technologies, such as computer, communication network, and so on. Supplying the most superior travel way and the real-time transportation information according to the beginning and ending point of the journey. The journey can promptly understand in the transportation status of road network according to the guidance system, then choosing the best route to reach destination.

scholarly journals Deep Intelligent Prediction Network: A Novel Deep Learning Based Prediction Model on Spatiotemporal Characteristics and Location Based Services for Big Data Driven Intelligent Transportation System

2019 ◽  
Vol 8 (11) ◽  
pp. 845-849
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Recommendation System ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Location Based Services ◽  
Traffic Data ◽  
Spatiotemporal Characteristics

The concept of big Data for intelligent transportation system has been employed for traffic management on dealing with dynamic traffic environments. Big data analytics helps to cope with large amount of storage and computing resources required to use mass traffic data effectively. However these traditional solutions brings us unprecedented opportunities to manage transportation data but it is inefficient for building the next-generation intelligent transportation systems as Traffic data exploring in velocity and volume on various characteristics. In this article, a new deep intelligent prediction network has been introduced that is hierarchical and operates with spatiotemporal characteristics and location based service on utilizing the Sensor and GPS data of the vehicle in the real time. The proposed model employs deep learning architecture to predict potential road clusters for passengers. It is injected as recommendation system to passenger in terms of mobile apps and hardware equipment employment on the vehicle incorporating location based services models to seek available parking slots, traffic free roads and shortest path for reach destination and other services in the specified path etc. The underlying the traffic data is classified into clusters with extracting set of features on it. The deep behavioural network processes the traffic data in terms of spatiotemporal characteristics to generate the traffic forecasting information, vehicle detection, autonomous driving and driving behaviours. In addition, markov model is embedded to discover the hidden features .The experimental results demonstrates that proposed approaches achieves better results against state of art approaches on the performance measures named as precision, execution time, feasibility and efficiency.

Design and implementation of microstrip array antenna for intelligent transportation systems application

Frequenz ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Arun Kumar Singh ◽  
Arun Kumar ◽  
Samarendra Nath Sur ◽  
Rabindranath Bera ◽  
Bansibadan Maji
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Impedance Matching ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Array Antenna ◽  
Design And Implementation ◽  
Microstrip Patch ◽  
Microstrip Array Antenna

Abstract This article proposes a design and implementation of array Microstrip Patch antenna of configuration 2 × 2 at an operating frequency of 3.5 GHz. The proposed design takes a dimension of 80 mm × 92 mm × 1.6 mm with four radiating elements arranged in rectangular form with an optimized separation between the patches. All the radiating elements were connected through a corporate series network with an inset feed to have better impedance matching. The model gives an efficiency of 90.99% with a bandwidth of 510 MHz and with fractal configuration, the bandwidth further enhances to 1.12 GHz. The maximum gain measured was found as 11.01 dBi at θ = 10° and ɸ = 360° and 10.45 dBi with fractal configuration. The designed antenna is proposed to be used in RADAR which will be used in the intelligent transportation system for the detection of nearby (short-range) vehicles in the blind zone. This kind of Radar also finds its application in collision avoidance and activating airbags/break boosting and thus helping mankind by saving lives. The article gives an idea of the use of an array antenna in intelligent transportation system for better gain and efficient results.

scholarly journals Vision Based Automatic Steering Control Using A Pid Controller

2012 ◽  
Author(s):  
Ahmad Saifizul Abdullah ◽  
Kim Hai Loo ◽  
Noor Azuan Abu Osman ◽  
Mohd Zamri Zainon
Keyword(s):  
Control System ◽  
Intelligent Transportation Systems ◽  
Pid Controller ◽  
Intelligent Transportation System ◽  
Vision System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Steering Control ◽  
Automatic Steering

Kawalan stereng automatik adalah satu komponen penting dalam pengautomatan lebuhraya, yang kini diselidik di seluruh dunia di bawah beberapa program Intelligent Transportation System (ITS). ITS berpotensi meningkatkan kapasiti lebuhraya yang sedia ada dengan penggunaan yang lebih selamat dan lebih efisien terhadap ruang yang sedia ada. Sistem ini akan terdiri daripada konsep pemanduan “hands–off” secara menyeluruh yang mana kenderaan akan dikawal secara automatik apabila ia memasuki sistem itu. Untuk mencapai objektif di atas, pengawal PID dan konsep dasar penglihatan ke atas sistem kawalan stereng automatik digunakan untuk membolehkan kenderaan menjejak rujukan di dalam pelbagai keadaan. Keputusan simulasi menunjukkan bahawa sistem kawalan yang dicadangkan mencapai objektifnya meskipun ia kurang lasak untuk mengekalkan prestasinya di dalam pelbagai keadaan. Kata kunci: Kawalan stereng automatik, dinamik kenderaan, sistem penglihatan, kawalan PID Automatic steering control is a vital component of highway automation, currently investigated worldwide in several Intelligent Transportation Systems (ITS) programs. The promise of Intelligent Transportation System lies in the possibility of increasing the capacity of existing highways by safer and more efficient use of available space. This system will include completely “hands–off” driving in which vehicles are fully automatically controlled once they enter the system. In order to achieve the above objective, the Proportional–Integral–Derivative (PID) controller and vision based concept to an automatic steering control system is used to cause the vehicle to track the reference under various conditions. Simulation results show that the proposed control system achieved its objective even though it is less robust in maintaining its performance under various conditions. Key words: Automatic steering control, vehicle dynamics, vision system, PID controller

scholarly journals Analytic architecture to overcome real time traffic control as an intelligent transportation system using big data

2018 ◽  
Vol 7 (2.18) ◽  
pp. 7 ◽  
Author(s):  
Venkata Ramana N ◽  
Seravana Kumar P. V. M ◽  
Puvvada Nagesh
Keyword(s):  
Big Data ◽  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Control Logic ◽  
Systematic Analysis ◽  
Real Time Traffic

Big data is a term that describes the large volume of data – both structured and unstructuredthat includes a business on a day-to-day basis including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation. 

Intelligent transportation system for sustainable environment in smart cities

2021 ◽  
pp. 002072092098350
Author(s):  
Liang Zhao ◽  
Yuanhua Jia
Keyword(s):  
Environmental Sustainability ◽  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Advanced Technology ◽  
Toxic Substances ◽  
Sustainable Environment

Advanced technology has ushered in the urge to enhance the travel experience. Besides the consistent desire to travel faster and more comfortably, the need to ensure transportation sustainability has remained constant. Smart cities employ top-grade technological applications to facilitate operations. Intelligent transportation systems involve the use of advanced transportation technologies. Through the integration of the Internet of Vehicles, cars in traffic can send and receive data between themselves and other vehicles and the environment. This data is processed to ensure efficient transportation by controlling traffic flows and preventing accidents. In this study, a literature review is conducted on how intelligent transportation systems contribute to environmental sustainability in smart cities. With technologies such as electricity-driven cars and autonomous vehicles, the systems minimize the emission of toxic substances to the environment while enhancing the interaction of the car with its surroundings to avoid accidents.

scholarly journals Implementasi Fasilitas Intelligent Transportation System (ITS) Di Kota Palangka Raya

2020 ◽  
Vol 8 (2) ◽  
pp. 72-78
Author(s):  
Devia Devia ◽  
Prihanika Prihanika
Keyword(s):  
Control System ◽  
Traffic Safety ◽  
Traffic Control ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Travel Speed ◽  
Transportation System ◽  
Transportation Systems ◽  
Traffic Control System ◽  
The City

The movement of people and goods is increasing in line with economic growth in society. This causes the potential for increased transportation activities in the City of Palangka Raya so it needs efforts to improve adequate transportation facilities and infrastructure. The application of technology-based Intelligent Transportation System (ITS) in Palangka Raya City is needed so that the management of the transportation system becomes more effective and efficient. This paper provides an overview of the application of ITS facilities and types in Palangka Raya City and provides recommendations for the use of new ITS facilities or optimizing existing technology so that ITS facilities can be utilized by stakeholders in traffic management and transportation systems in Palangka Raya City. Based on observations of the application of ITS in the City of Palangka Raya is applied to improve the performance of intersections and road services. The type of ITS facility is the Area Traffic Control System (ATCS), which is a vehicle traffic control system at the signal intersection to increase travel speed and travel time so that delays in travel can be minimized. It is also expected that the implementation of ITS in Palangkaraya City can also optimize the performance of public transport and traffic safety as well as the collaboration between stakeholders so that the improvement of the integrated transportation system can be well integrated.

Creating Smart Cities with Intelligent Transportation Solutions

2011 ◽  
pp. 174-190 ◽  
Author(s):  
Leo Tan Wee Hin ◽  
R. Subramaniam
Keyword(s):  
Public Transportation ◽  
Intelligent Transportation Systems ◽  
Electronic Monitoring ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Signaling Systems ◽  
Public Transportation System ◽  
City State

Transportation is often the bane of urban societies. Traffic gridlocks and inadequate availability of a comprehensive and affordable public transportation system further accentuate the problem. This chapter focuses on the Singapore experience with intelligent transportation solutions to alleviate a range of problems, thus contributing to its positioning as a smart city. We focus on seven issues: public transportation using modern mass rapid transit trains; congestion control using electronic road pricing; electronic monitoring advisory systems to guide road users on adverse conditions or incidents on roads; computerized traffic signaling systems to streamline the throughput of vehicles in roadways; intelligent dispatch of taxis, which helps to minimize idle cruising time; parking guidance systems to alert motorists of the nearest car park, in the process decreasing the level of floating traffic on roads; and integrated ticketing systems to promote inter-modal transfer. A unique funding mechanism that has led to the evolution of a modern and efficient public transportation system is also elaborated. Being a city state and a living laboratory of intelligent transportation systems that have attracted international attention, it is suggested that there are some lessons to be drawn from the Singapore experience in managing transportation problems in smart cities.

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