The importance of public support in the implementation of green transportation in smart cities using smart vehicle bicycle communication transport

2020 ◽  
Vol 38 (5/6) ◽  
pp. 997-1011
Author(s):  
Ning Li ◽  
Parthasarathy R. ◽  
Harshila H. Padwal
Keyword(s):  
Smart Cities ◽  
Optimization Technique ◽  
Public Support ◽  
Weather Conditions ◽  
Transport Systems ◽  
Content Type ◽  
Signaling Systems ◽  
Traffic Conditions ◽  
Green Transportation ◽  
Smart Vehicle

Purpose Smart mobility is a major guideline in the development of Smart Cities’ transport systems and management. The issue of transition into green, secure and sustainable transport modes, such as using bicycles, should be implemented in this case, along with the subjectivism of management. Design/methodology/approach The proposed technology reflects the Smart Bicycle vehicle model, which tracks cyclists and weather conditions and turns to electric motors in critical circumstances. Findings This reduces the physical load and battery consumption of cyclists which affects the Smart Cities’ ecology positively. Originality/value In Smart Vehicle Bicycle Communication Transport, the vehicle movement optimization technique is used for traffic scenarios to analyze traffic signaling systems that give better results in variable and dense traffic conditions.

scholarly journals Towards an End-to-End Framework of CCTV-Based Urban Traffic Volume Detection and Prediction

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 629
Author(s):  
Maria V. Peppa ◽  
Tom Komar ◽  
Wen Xiao ◽  
Phil James ◽  
Craig Robson ◽  
...  
Keyword(s):  
Real Time ◽  
Prediction Models ◽  
Weather Conditions ◽  
Traffic Volume ◽  
Urban Traffic ◽  
Transport Systems ◽  
Traffic Conditions ◽  
Adverse Weather ◽  
Approaches To Study ◽  
End To End

Near real-time urban traffic analysis and prediction are paramount for effective intelligent transport systems. Whilst there is a plethora of research on advanced approaches to study traffic recently, only one-third of them has focused on urban arterials. A ready-to-use framework to support decision making in local traffic bureaus using largely available IoT sensors, especially CCTV, is yet to be developed. This study presents an end-to-end urban traffic volume detection and prediction framework using CCTV image series. The framework incorporates a novel Faster R-CNN to generate vehicle counts and quantify traffic conditions. Then it investigates the performance of a statistical-based model (SARIMAX), a machine learning (random forest; RF) and a deep learning (LSTM) model to predict traffic volume 30 min in the future. Tests at six locations with varying traffic conditions under different lengths of past time series are used to train the prediction models. RF and LSTM provided the most accurate predictions, with RF being faster than LSTM. The developed framework has been successfully applied to fill data gaps under adverse weather conditions when data are missing. It can be potentially implemented in near real time at any CCTV location and integrated into an online visualization platform.

Effect of type of lead vehicle on following headway behaviour in mixed traffic

2014 ◽  
Vol 11 (1) ◽  
pp. 28-43 ◽  
Author(s):  
Ravindra Kumar ◽  
Purnima Parida ◽  
Wafaa Saleh
Keyword(s):  
Transport Systems ◽  
Mixed Traffic ◽  
Driver Behaviour ◽  
Traffic Condition ◽  
Content Type ◽  
Traffic Conditions ◽  
Study Results ◽  
Strategic Study ◽  
The Impact ◽  
Lead Vehicle

Purpose – There is gap in literature on understanding of the issues of following headway behaviour of the driver and a lack of sufficient data in different traffic conditions. The purpose of this paper is to find the effects of type of lead vehicle on following headway in mixed traffic condition in India on different category of roads and flow. Design/methodology/approach – Real-world headway data were collected through video and extracted. Data were analysed using tools and statically approach was adopted to present the results in detail. Findings – Results shows the impact of type of lead vehicle on driver following time headway behaviour under different level of traffic and types of road characteristics. It was found that driver following behaviour is affected by the type of lead vehicle. It also shows that drivers are inconsistent in their choice of headway. Research limitations/implications – This research has special strategic study area of India in typical two cities Silchar and Shillong of northeast region of India. The traffic characteristic and composition is quite different as compared to other cities of India. Therefore the study results cannot be generalized for whole India. Practical implications – The result of the study has focused on impact of type of lead vehicle on following behaviour. This can be useful to safety reduction and changing the driver behaviour through education and display of information. However, the real application of this result is to be implemented by local transport and road managing authority to reduce accidents and increase safety of drivers. Originality/value – In mixed traffic conditions, the impact of type of lead vehicle on following behaviour affects the safety of drivers and the accounting for such behaviour is never been explored in mixed traffic condition. If the study is implemented, it can be useful to simulation modeller and intelligent transport systems (ITS) to design and operate many in-vehicle systems for smooth traffic processes.

Analysis of performance-based issues in green transportation management systems in smart cities

2020 ◽  
Vol 38 (5/6) ◽  
pp. 963-977
Author(s):  
Liang Chen ◽  
Prathik Anandhan ◽  
Balamurugan S.
Keyword(s):  
Smart Cities ◽  
Heavy Traffic ◽  
Main Concern ◽  
Data Reliability ◽  
Content Type ◽  
Transport Services ◽  
Learning Assistance ◽  
Green Transportation ◽  
Intelligent Information ◽  
Traffic Optimization

Purpose In this paper, an intelligent information assisted communication transportation framework (II-CTF) has been introduced to reduce congestion, data reliability in transportation and the environmental effects. Design/methodology/approach The main concern of II-CTF is to mitigate public congestion using current transport services, which helps to improve data reliability under hazardous circumstances and to avoid accidents when the driver cannot respond reasonably. The program uses machine learning assistance to predict optimal routes based on movement patterns and categorization of vehicles, which helps to minimize congestion of traffic. Findings In II-CTF, scheduling traffic optimization helps to reduce the energy and many challenges faced by traffic managers in terms of optimization of the route, average waiting time and congestion of traffic, travel, and environmental impact due to heavy traffic collision. Originality/value The II-CTF definition is supposed to attempt to overcome some of the problems of the transportation environment that pose difficulties and make the carriage simpler, safer, more efficient and green for all.

The importance of public support in the implementation of green transportation in the smart cities

2020 ◽  
Author(s):  
Jia Mao ◽  
Qi Sun ◽  
Xi Wang ◽  
BalaAnand Muthu ◽  
Sujatha Krishnamoorthy
Keyword(s):  
Smart Cities ◽  
Public Support ◽  
Green Transportation

scholarly journals Smart Cities in Turkey: Approaches, Advances and Applications with Greater Consideration for Future Urban Transport Development

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2308 ◽  
Author(s):  
Can Bıyık
Keyword(s):  
Urban Areas ◽  
Planning Process ◽  
Smart Cities ◽  
Radical Change ◽  
Urban Transport ◽  
Transport Systems ◽  
Structured Interviews ◽  
Policy Makers ◽  
Comprehensive Survey ◽  
Future Vision

The smart city transport concept is viewed as a future vision aiming to undertake investigations on the urban planning process and to construct policy-pathways for achieving future targets. Therefore, this paper sets out three visions for the year 2035 which bring about a radical change in the level of green transport systems (often called walking, cycling, and public transport) in Turkish urban areas. A participatory visioning technique was structured according to a three-stage technique: (i) Extensive online comprehensive survey, in which potential transport measures were researched for their relevance in promoting smart transport systems in future Turkish urban areas; (ii) semi-structured interviews, where transport strategy suggestions were developed in the context of the possible imaginary urban areas and their associated contextual description of the imaginary urban areas for each vision; (iii) participatory workshops, where an innovative method was developed to explore various creative future choices and alternatives. Overall, this paper indicates that the content of the future smart transport visions was reasonable, but such visions need a considerable degree of consensus and radical approaches for tackling them. The findings offer invaluable insights to researchers inquiring about the smart transport field, and policy-makers considering applying those into practice in their local urban areas.

scholarly journals Vehicular Crowdsourcing for Congestion Support in Smart Cities

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 662-685
Author(s):  
Stephan Olariu
Keyword(s):  
Smart City ◽  
Large Scale ◽  
Smart Cities ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Adaptive Traffic Signal Control ◽  
Traffic Conditions ◽  
Direct Benefits ◽  
Traffic Signal Control Systems ◽  
Computational Resources

Under present-day practices, the vehicles on our roadways and city streets are mere spectators that witness traffic-related events without being able to participate in the mitigation of their effect. This paper lays the theoretical foundations of a framework for harnessing the on-board computational resources in vehicles stuck in urban congestion in order to assist transportation agencies with preventing or dissipating congestion through large-scale signal re-timing. Our framework is called VACCS: Vehicular Crowdsourcing for Congestion Support in Smart Cities. What makes this framework unique is that we suggest that in such situations the vehicles have the potential to cooperate with various transportation authorities to solve problems that otherwise would either take an inordinate amount of time to solve or cannot be solved for lack for adequate municipal resources. VACCS offers direct benefits to both the driving public and the Smart City. By developing timing plans that respond to current traffic conditions, overall traffic flow will improve, carbon emissions will be reduced, and economic impacts of congestion on citizens and businesses will be lessened. It is expected that drivers will be willing to donate under-utilized on-board computing resources in their vehicles to develop improved signal timing plans in return for the direct benefits of time savings and reduced fuel consumption costs. VACCS allows the Smart City to dynamically respond to traffic conditions while simultaneously reducing investments in the computational resources that would be required for traditional adaptive traffic signal control systems.

scholarly journals Trk2 Potassium Transport System in Streptococcus mutans and Its Role in Potassium Homeostasis, Biofilm Formation, and Stress Tolerance

2016 ◽  
Vol 198 (7) ◽  
pp. 1087-1100 ◽  
Author(s):  
Gursonika Binepal ◽  
Kamal Gill ◽  
Paula Crowley ◽  
Martha Cordova ◽  
L. Jeannine Brady ◽  
...  
Keyword(s):  
Stress Tolerance ◽  
Streptococcus Mutans ◽  
Transport System ◽  
Biofilm Formation ◽  
Cellular Response ◽  
Pathogenic Bacteria ◽  
Transport Systems ◽  
Content Type ◽  
Growth And Survival ◽  
Dental Biofilm

ABSTRACTPotassium (K+) is the most abundant cation in the fluids of dental biofilm. The biochemical and biophysical functions of K+and a variety of K+transport systems have been studied for most pathogenic bacteria but not for oral pathogens. In this study, we establish the modes of K+acquisition inStreptococcus mutansand the importance of K+homeostasis for its virulence attributes. TheS. mutansgenome harbors four putative K+transport systems that included two Trk-like transporters (designated Trk1 and Trk2), one glutamate/K+cotransporter (GlnQHMP), and a channel-like K+transport system (Kch). Mutants lacking Trk2 had significantly impaired growth, acidogenicity, aciduricity, and biofilm formation. [K+] less than 5 mM eliminated biofilm formation inS. mutans. The functionality of the Trk2 system was confirmed by complementing anEscherichia coliTK2420 mutant strain, which resulted in significant K+accumulation, improved growth, and survival under stress. Taken together, these results suggest that Trk2 is the main facet of the K+-dependent cellular response ofS. mutansto environment stresses.IMPORTANCEBiofilm formation and stress tolerance are important virulence properties of caries-causingStreptococcus mutans. To limit these properties of this bacterium, it is imperative to understand its survival mechanisms. Potassium is the most abundant cation in dental plaque, the natural environment ofS. mutans. K+is known to function in stress tolerance, and bacteria have specialized mechanisms for its uptake. However, there are no reports to identify or characterize specific K+transporters inS. mutans. We identified the most important system for K+homeostasis and its role in the biofilm formation, stress tolerance, and growth. We also show the requirement of environmental K+for the activity of biofilm-forming enzymes, which explains why such high levels of K+would favor biofilm formation.

Beyond new roads and bridges

2018 ◽  
Vol 30 (2) ◽  
pp. 175-190
Author(s):  
Lenahan O’Connell ◽  
Juita-Elena (Wie) Yusuf ◽  
Khairul Azfi Anuar
Keyword(s):  
Factor Model ◽  
Public Support ◽  
Mass Transit ◽  
Light Rail ◽  
Urban Context ◽  
Public Preferences ◽  
Content Type ◽  
Hampton Roads ◽  
Infrastructure Investments ◽  
Three Factor

Purpose The purpose of this paper is to compare public preferences for investment and spending on non-automobile infrastructures (mass transit and bicycling) to preferences for new roads and the repair of current highways. The study explores the factors that explain preferences for non-automobile infrastructure using a three-factor model including self-interest (personal transportation benefits), concern for community-wide benefits (political beliefs), and concern for the economic impact. The study uses a case study of the urban context of the Hampton Roads region of Southeastern Virginia (USA). Design/methodology/approach The analysis uses data from a 2013 telephone survey of urban residents in the Hampton Roads area. Survey respondents were asked to identify their two investment priorities from four options: repairing existing roads, bridges, and tunnels; constructing new or expanding roads, bridges, and tunnels; expanding mass transit; and expanding bicycle routes and improving bike safety. Findings Repairing existing highway infrastructure is the most popular spending priority (66 percent of residents). There is as much support (46 percent) for investing in non-automobile infrastructure as for investing in new roads, bridges, and tunnels. Significant predictors of support for non-automobile infrastructure, using the three-factor model, are: length of commute time, self-identification as liberal, use of light rail, and a belief that light rail contributes to economic development. Originality/value The study examines public preferences for both non-traditional and traditional transportation infrastructure investments. It highlights the factors that contribute to public support for different transportation spending options.

A novel way of parameter estimation of solar photovoltaic system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rahul Bisht ◽  
Afzal Sikander
Keyword(s):  
Parameter Estimation ◽  
Mean Absolute Error ◽  
Optimization Technique ◽  
Absolute Error ◽  
Photovoltaic System ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Solar Panels ◽  
Content Type ◽  
Solar Photovoltaic System

Purpose This paper aims to achieve accurate maximum power from solar photovoltaic (PV), its five parameters need to be estimated. This study proposes a novel optimization technique for parameter estimation of solar PV. Design/methodology/approach To extract optimal parameters of solar PV new optimization technique based on the Jellyfish search optimizer (JSO). The objective function is defined based on two unknown variables and the proposed technique is used to estimate the two unknown variables and the rest three unknown variables are estimated analytically. Findings In this paper, JSO is used to estimate the parameters of a single diode PV model. In this study, eight different PV panels are considered. In addition, various performance indices, such as PV characteristics, such as power-voltage and current-voltage curves, relative error (RE), root mean square error (RMSE), mean absolute error (MAE) and normalized mean absolute error (NMAE) are determined using the proposed algorithm and existing algorithms. The results for different solar panels have been obtained under varying environmental conditions such as changing temperature and constant irradiance or changing irradiance and constant temperature. Originality/value The proposed technique is new and provides better results with minimum RE, RMSE, NMAE, MAE and converges fast, as depicted by the fitness graph presented in this paper.

Gap between France’s Macron and Le Pen is narrowing

2021 ◽  
Keyword(s):  
Public Support ◽  
Fiscal Rules ◽  
Terrorist Attacks ◽  
Law And Order ◽  
Content Type ◽  
Investment Agreement ◽  
State Investment ◽  
The Eu

Significance Nevertheless, Le Pen remains the most serious threat to President Emmanuel Macron's hopes for re-election in 2022. She stands above him in some national polls, reflecting her success in broadening RN’s appeal, widespread anti-establishment sentiment and Macron’s unpopularity and mixed record on COVID-19. Impacts To revive the economy, Macron will likely campaign for reform of EU fiscal rules to enable greater levels of state investment. Further terrorist attacks or assaults on police would increase the salience of immigration and law and order ahead of the 2022 election. Ahead of the election, Macron will be reluctant to show public support for the EU-China investment agreement.

Sign in / Sign up

Export Citation Format

Share Document