Sustainable Energy Management in Intelligent Transportation

2022 ◽  
Author(s):  
Ying Gao ◽  
Tong Ren ◽  
Xia Zhao ◽  
Wentao Li
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Data Storage ◽  
Intelligent Transportation Systems ◽  
Field Tests ◽  
Intelligent Transportation ◽  
Analysis Data ◽  
Primary Energy ◽  
Transportation Systems ◽  
Intelligent Transport System

Intelligent transportation systems (ITS) are a collection of technologies that can enhance transport networks and public transit and individual decision-making about various elements of travel. ITS technologies comprise cutting-edge wireless, electronic and automated technology intending to improve safety, efficiency and convenience in surface transit. In certain cases, reducing energy usage has proven to be an ITS advantage. In this report, the primary energy advantages of a range of ITS systems established through models, pilot projects/field tests and extensive use are examined and summarized. In worldwide driving, the Internet of Things (IoT) solutions play a vital role. A new age of communication leading to ITS will be the communication between cars via IoT. IoT is a mixture of data and data analysis data storage and processing to manage the traffic system efficiently.Energy management, which is seen as an efficient, innovative approach to highly efficient energy generation plants. It simultaneously takes care of optimizing traditional sources of the IoT based intelligent transport system, helps to automate railways, roads, airways and shipways, which improve customer experience in the process. Following an evaluation of the situation, a proposal named energy management in intelligent transportation (EMIT) improves energy efficiency and economic efficiency in transportation. It improves energy management to reduce economic and ecological waste by decreasing global transport energy consumption. The sustainable development ratio is 85.7%, accidents detection ratio is 85.3%, electric vehicle infrastructure ratio is 83.6%, intelligent vehicle parking system acceptance ratio is 82.15%, and reduction ratio of energy consumption is 91.4%.

scholarly journals Privacy Preserving Data Transmission in Malicious Vehicular Adhoc Networks

2021 ◽  
Vol 12 (3) ◽  
pp. 5757-5761
Author(s):  
Mrs.R.M.Rajeshwari Et. al.
Keyword(s):  
Data Storage ◽  
Data Transmission ◽  
Intelligent Transportation Systems ◽  
Privacy Preservation ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Third Party ◽  
Mobile Nodes ◽  
Legitimate User ◽  
On The Road

Vehicle Adhoc Network is deployed on the road, where vehicles constitute mobile nodes in which active security and intelligent transportation are important applications of VANET. VANETs are a key part of the intelligent transportation systems (ITS) framework. Sometimes, VANETs are referred as Intelligent Transportation Networks. However, authentication and privacy of users are still two vital issues in VANETs.  In the traditional mode, the transactional data storage provides no distributed and decentralized security, so that the third party initiates the dishonest behaviors possibly. VANET has  temporary participants , communication between vehicles are short-lived messages. Possible situation might happens , adversary may play as an legitimate user and able to perform malicious activity .To address these challenges this paper proposes timestamp based message between users to  perform secure data transmission and give the negligible probability of the attacker. With the help of Certificate Authority (CA) and the RoadSide Units (RSUs), our proposal attains the confidentiality and  trace the identity of the unauthenticated vehicle in the anonymous announcements as well. Finally, through the theoretical analysis and simulations, our scheme is able to implement a secure VANET framework with accountability and privacy preservation

scholarly journals Smart Green Applications: From Renewable Energy Management to Intelligent Transportation Systems

Energies ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 1317 ◽  
Author(s):  
Mario Collotta ◽  
Yunchuan Sun ◽  
Luca Persio ◽  
Emad Ebeid ◽  
Riccardo Muradore
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems

Experience Implementing a User Service for Archived Intelligent Transportation Systems Data

2005 ◽  
Vol 1917 (1) ◽  
pp. 90-99 ◽  
Author(s):  
Robert L. Bertini ◽  
Steve Hansen ◽  
Andrew Byrd ◽  
Thareth Yin
Keyword(s):  
Data Storage ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Travel Demand ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Successful Implementation ◽  
Data Archive ◽  
Data Archiving ◽  
Advanced Traffic Management System

In cooperation with the Oregon Department of Transportation (ODOT) and other regional partners, the Portland regional intelligent transportation systems (ITSs) data archive was recently inaugurated via a direct fiber-optic connection between ODOT and Portland State University (PSU). In July 2004, the Portland Regional Transportation Archive Listing was activated; it received 20-s data from the 436 inductive loop detectors composing the Portland area's advanced traffic management system. PSU is designated as the region's official data archiving entity, consistent with the ITS architecture being developed. This paper discusses the steps taken for successful implementation of the Portland region's functional ITS data archive and plans for development and expansion. Included is a discussion of the archive structure, data storage, data processing, and user interface. An experiment involving Metro, the Portland region's metropolitan planning organization, demonstrates that archived loop detector data can be used to improve travel demand forecasts for the Portland region. The data archive will expand to include transit data, freeway incident data, city traffic signal data, and truck weigh-in-motion data.

A Comprehensive Study on Intelligent Transportation Systems

2018 ◽  
Vol 4 (10) ◽  
pp. 10
Author(s):  
Ankur Mishra ◽  
Aayushi Priya
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Transportation Systems ◽  
Environmental Conservation ◽  
Integrated System ◽  
Transport Systems ◽  
Transport Sector ◽  
Intelligent Transport System ◽  
Intelligent Transport ◽  
Transportation Sector

Transportation or transport sector is a legal source to take or carry things from one place to another. With the passage of time, transportation faces many issues like high accidents rate, traffic congestion, traffic & carbon emissions air pollution, etc. In some cases, transportation sector faced alleviating the brutality of crash related injuries in accident. Due to such complexity, researchers integrate virtual technologies with transportation which known as Intelligent Transport System. Intelligent Transport Systems (ITS) provide transport solutions by utilizing state-of-the-art information and telecommunications technologies. It is an integrated system of people, roads and vehicles, designed to significantly contribute to improve road safety, efficiency and comfort, as well as environmental conservation through realization of smoother traffic by relieving traffic congestion. This paper aims to elucidate various aspects of ITS - it's need, the various user applications, technologies utilized and concludes by emphasizing the case study of IBM ITS.

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.

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