scholarly journals An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

2020 ◽  
Vol 12 (7) ◽  
pp. 2922 ◽  
Author(s):  
Muhammad Tanveer ◽  
Faizan Ahmad Kashmiri ◽  
Hassan Naeem ◽  
Huimin Yan ◽  
Xin Qi ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Age Groups ◽  
Transportation Systems ◽  
Heterogeneous Traffic ◽  
And Gender ◽  
The Impact

Traffic congestion has become increasingly prevalent in many urban areas, and researchers are continuously looking into new ways to resolve this pertinent issue. Autonomous vehicles are one of the technologies expected to revolutionize transportation systems. To this very day, there are limited studies focused on the impact of autonomous vehicles in heterogeneous traffic flow in terms of different driving modes (manual and self-driving). Autonomous vehicles in the near future will be running parallel with manual vehicles, and drivers will have different characteristics and attributes. Previous studies that have focused on the impact of autonomous vehicles in these conditions are scarce. This paper proposes a new cellular automata model to address this issue, where different autonomous vehicles (cars and buses) and manual vehicles (cars and buses) are compared in terms of fundamental traffic parameters. Manual cars are further divided into subcategories on the basis of age groups and gender. Each category has its own distinct attributes, which make it different from the others. This is done in order to obtain a simulation as close as possible to a real-world scenario. Furthermore, different lane-changing behavior patterns have been modeled for autonomous and manual vehicles. Subsequently, different scenarios with different compositions are simulated to investigate the impact of autonomous vehicles on traffic flow in heterogeneous conditions. The results suggest that autonomous vehicles can raise the flow rate of any network considerably despite the running heterogeneous traffic flow.

scholarly journals A Centralized Route-Management Solution for Autonomous Vehicles in Urban Areas

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 722 ◽  
Author(s):  
Jorge Zambrano-Martinez ◽  
Carlos Calafate ◽  
David Soler ◽  
Lenin-Guillermo Lemus-Zúñiga ◽  
Juan-Carlos Cano ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Traffic Management ◽  
Real Data ◽  
Prediction Equation ◽  
City Management ◽  
Traffic Demand ◽  
Traffic Conditions

Currently, one of the main challenges that large metropolitan areas must face is traffic congestion. To address this problem, it becomes necessary to implement an efficient solution to control traffic that generates benefits for citizens, such as reducing vehicle journey times and, consequently, environmental pollution. By properly analyzing traffic demand, it is possible to predict future traffic conditions, using this information for the optimization of the routes taken by vehicles. Such an approach becomes especially effective if applied in the context of autonomous vehicles, which have a more predictable behavior, thus enabling city management entities to mitigate the effects of traffic congestion and pollution, thereby improving the traffic flow in a city in a fully centralized manner. This paper represents a step forward towards this novel traffic management paradigm by proposing a route server capable of handling all the traffic in a city, and balancing traffic flows by accounting for present and future traffic congestion conditions. We perform a simulation study using real data of traffic congestion in the city of Valencia, Spain, to demonstrate how the traffic flow in a typical day can be improved using our proposed solution. Experimental results show that our proposed traffic prediction equation, combined with frequent updating of traffic conditions on the route server, can achieve substantial improvements in terms of average travel speeds and travel times, both indicators of lower degrees of congestion and improved traffic fluidity.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

scholarly journals An Efficiency Enhancing Methodology for Multiple Autonomous Vehicles in an Urban Network Adopting Deep Reinforcement Learning

2021 ◽  
Vol 11 (4) ◽  
pp. 1514 ◽  
Author(s):  
Quang-Duy Tran ◽  
Sang-Hoon Bae
Keyword(s):  
Reinforcement Learning ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Effective Means ◽  
Urban Network ◽  
Learning Agents ◽  
Policy Optimization ◽  
The Impact

To reduce the impact of congestion, it is necessary to improve our overall understanding of the influence of the autonomous vehicle. Recently, deep reinforcement learning has become an effective means of solving complex control tasks. Accordingly, we show an advanced deep reinforcement learning that investigates how the leading autonomous vehicles affect the urban network under a mixed-traffic environment. We also suggest a set of hyperparameters for achieving better performance. Firstly, we feed a set of hyperparameters into our deep reinforcement learning agents. Secondly, we investigate the leading autonomous vehicle experiment in the urban network with different autonomous vehicle penetration rates. Thirdly, the advantage of leading autonomous vehicles is evaluated using entire manual vehicle and leading manual vehicle experiments. Finally, the proximal policy optimization with a clipped objective is compared to the proximal policy optimization with an adaptive Kullback–Leibler penalty to verify the superiority of the proposed hyperparameter. We demonstrate that full automation traffic increased the average speed 1.27 times greater compared with the entire manual vehicle experiment. Our proposed method becomes significantly more effective at a higher autonomous vehicle penetration rate. Furthermore, the leading autonomous vehicles could help to mitigate traffic congestion.

scholarly journals “We Make Our Community”: Youth Forging Environmental Identities in Urban Landscapes

2021 ◽  
Vol 13 (14) ◽  
pp. 7736
Author(s):  
Erin Gallay ◽  
Alisa Pykett ◽  
Constance Flanagan
Keyword(s):  
High School Students ◽  
Urban Areas ◽  
Local Environment ◽  
Natural World ◽  
Urban Landscapes ◽  
Youth Of Color ◽  
School Students ◽  
Environmental Leadership ◽  
And Gender ◽  
The Impact

Insofar as race, class, and gender have profound effects on people’s environmental experiences, and consequently their activism, the environmental field needs more work on the environmental experiences and insights of groups whose voices have been missing, including youth of color who live in urban areas in the U.S. In this paper, we focus on African American and Latinx students engaged in environmental projects in their urban communities and the impact of such projects on promoting pro-environmental leadership, agency, and behavior. We draw from written reflections and focus group interviews of several hundred 4th–12th graders (majority middle- and high-school students) who participated in place-based civic science projects. Thematic analyses of student responses found that students engaged in work on local environmental issues cultivated an appreciation for the natural world and an understanding of human-nature interdependence and the ties between the local environment and their communities’ health. Through taking action with others in their communities, students viewed themselves as contributors to their communities and started to form environmental identities in ways that are not traditionally measured. Findings point to the need for forms of environmental education that are contextually grounded and centered on environmental justice in urban areas.

scholarly journals Exploring Impact of Age and Gender on Sentiment Analysis Using Machine Learning

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 374 ◽  
Author(s):  
Sudhanshu Kumar ◽  
Monika Gahalawat ◽  
Partha Pratim Roy ◽  
Debi Prosad Dogra ◽  
Byung-Gyu Kim
Keyword(s):  
Machine Learning ◽  
Sentiment Analysis ◽  
Short Term Memory ◽  
Age Groups ◽  
Modern World ◽  
Support Vector ◽  
Digital Information ◽  
Age And Gender ◽  
And Gender ◽  
The Impact

Sentiment analysis is a rapidly growing field of research due to the explosive growth in digital information. In the modern world of artificial intelligence, sentiment analysis is one of the essential tools to extract emotion information from massive data. Sentiment analysis is applied to a variety of user data from customer reviews to social network posts. To the best of our knowledge, there is less work on sentiment analysis based on the categorization of users by demographics. Demographics play an important role in deciding the marketing strategies for different products. In this study, we explore the impact of age and gender in sentiment analysis, as this can help e-commerce retailers to market their products based on specific demographics. The dataset is created by collecting reviews on books from Facebook users by asking them to answer a questionnaire containing questions about their preferences in books, along with their age groups and gender information. Next, the paper analyzes the segmented data for sentiments based on each age group and gender. Finally, sentiment analysis is done using different Machine Learning (ML) approaches including maximum entropy, support vector machine, convolutional neural network, and long short term memory to study the impact of age and gender on user reviews. Experiments have been conducted to identify new insights into the effect of age and gender for sentiment analysis.

Prediction of Vehicular Traffic Flow using Levenberg-Marquardt Artificial Neural Network Model: Italy Road Transportation System

2022 ◽  
Vol 24 (2) ◽  
pp. E74-E86
Author(s):  
Isaac Oyeyemi Olayode ◽  
Alessandro Severino ◽  
Tiziana Campisi ◽  
Lagouge Kwanda Tartibu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Time Of Day ◽  
Vehicle Speed ◽  
Road Transportation ◽  
Artificial Neural

In the last decades, the Italian road transport system has been characterized by severe and consistent traffic congestion and in particular Rome is one of the Italian cities most affected by this problem. In this study, a LevenbergMarquardt (LM) artificial neural network heuristic model was used to predict the traffic flow of non-autonomous vehicles. Traffic datasets were collected using both inductive loop detectors and video cameras as acquisition systems and selecting some parameters including vehicle speed, time of day, traffic volume and number of vehicles. The model showed a training, test and regression value (R2) of 0.99892, 0.99615 and 0.99714 respectively. The results of this research add to the growing body of literature on traffic flow modelling and help urban planners and traffic managers in terms of the traffic control and the provision of convenient travel routes for pedestrians and motorists.

Factors that affect entomophagical practices in Ghana

2017 ◽  
Vol 3 (1) ◽  
pp. 33-41 ◽  
Author(s):  
P.J. Anankware ◽  
E.A. Osekre ◽  
D. Obeng-Ofori ◽  
C.M. Khamala
Keyword(s):  
Social Factors ◽  
Urban Areas ◽  
Age Groups ◽  
Ecological Factors ◽  
Insect Species ◽  
Edible Insects ◽  
The Social ◽  
Gender Education ◽  
And Gender ◽  
Religious Reasons

This study evaluated the social and ecological factors that affect entomophagy in Ghana with a view to instigate the initiation of programmes for the use of insects for human and poultry nutrition in Africa. Two thousand questionnaires were administered to randomly selected respondents in all the ten regions of Ghana. With regards to social factors, entomophagy was found to be influenced by age, gender, education and occupation. Entomophagy is practiced across all age groups and gender in Ghana. Proportionally, 90, 78 and 74% of the aged (60+), middle aged (31-50) and the youth (18-30), respectively, were observed to consume various insect species. Ecologically, entomophagy was more pronounced in rural than urban areas. Over 87% of respondents who consume edible insects acquire them through harvesting/trapping. Four insect species were identified as feed for animals. The majority (81.6%) of the respondents consume insects as a source of protein, 9.6% for cultural reasons, 5.6% for medicinal values and 3.0 and 0.2%, respectively, for recreational and religious reasons. Gender has the least influence on entomophagy. Considering the economic, ecological and nutritional importance of edible insects in traditional Ghanaian foods, attention should be given to sustainable environmental harvesting practices.

scholarly journals Impact of Quality on Customers’ Buying Behaviour towards Point of Purchase Display with reference to Haryana

2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Sukhija Sunita ◽  
Sukhija Sunita
Keyword(s):  
Age Groups ◽  
Retail Industry ◽  
The Social ◽  
Point Of Purchase ◽  
Retail Outlets ◽  
And Gender ◽  
Buying Behaviour ◽  
Gender Groups ◽  
The Impact ◽  
One Way Anova

The present paper focuses on the impact of quality on customers’ buying behaviour towards point-of-purchase display at various retail outlets in Haryana. Point-of-Purchase Display plays an important role to increase the sale of the retailers. Today customers are rational and prefer quality products at reasonable price. Moreover, due to the emergence of the supermarkets as the dominant retail, the retail industry is experiencing vibrant changes all over the world. Retail industry in India has grown to be more complex and dynamic with an increase rate of speed from unorganized towards being organized. In this research paper data has been collected from 100 respondents and analysed with the help of Statistical Package for the Social Sciences (SPSS) using one way ANOVA and t-test with demographic factors i.e. age-wise, gender-wise, occupation-wise and income-wise. . After analysing the data it was found that, there is neutral relationship in the opinion of different age groups and gender groups over the point-of-purchase display on quality. On the other hand Occupation and income does not have any importance on customers view point regarding ‘quality’. To conclude we can say that point-of-purchase display is not directly related to the quality.

scholarly journals Einstellungen zur familialen Solidarität im Alter: Eine vergleichende Analyse mit türkischen Migranten und Deutschen

2013 ◽  
Vol 25 (1) ◽  
pp. 29-52
Author(s):  
Marie Carnein ◽  
Helen Baykara-Krumme
Keyword(s):  
Age Groups ◽  
Theoretical Background ◽  
Acculturation Gap ◽  
Immigrant Generation ◽  
Family Solidarity ◽  
Private Households ◽  
The Family ◽  
Background Data ◽  
And Gender ◽  
The Impact

The study examines the attitudes toward family solidarity and filial care obligations among Turks of the first and second immigrant generation as compared to Germans. The focilie on the impact of ethnic-cultural and socio-structural predictors, respectively, and whether patterns change across different age groups. Processes of intergenerational transmission and acculturation in migration constitute the theoretical background. Data from the Generations and Gender Survey 2005 and 2006 are used, including respondents in private households in Germany aged 18 to 79 years of the main sample, and the migrant sample, conducted on same-aged Turkish citizens in Germany. It was found that the family solidarity potential is far higher among Turkish migrants than among Germans. These differences persist in the second generation and in all age groups. Socio-structural predictors are of little relevance. The analyses indicate strong transmission processes between family generations: There ist little evidence of an “acculturation gap”.   Zusammenfassung Die Studie untersucht das familiale Solidaritätspotenzial für pflegebedürftige Eltern bei türkischen Migranten der ersten und zweiten Generation und kontrastiert es mit jenem der deutschen einheimischen Bevölkerung. Die zentralen Fragen lauten, welche Rolle ethnisch-kulturellen bzw. sozialstrukturellen Einflussgrößen zukommt und ob sich die Muster über verschiedene Altersgruppen hinweg verändern. Den theoretischen Hintergrund bilden Diskussionen um Transmissions- und Akkulturationsprozesse in der Migration. Auf Grundlage der Daten des Generations and Gender Survey 2005 und 2006, der die 18 bis 79-jährige Wohnbevölkerung in Privathaushalten Deutschlands sowie in einer Zusatzerhebung ergänzend die türkischen Staatsangehörigen berücksichtigt, kann gezeigt werden, dass das familiale Solidaritätspotenzial bei türkischen Migranten wesentlich stärker ausgeprägt ist als bei Deutschen. Die Unterschiede bleiben in der nachfolgenden Generation und über alle Altersgruppen hinweg bestehen. Sozialstrukturelle Merkmale sind von geringer Bedeutung. Die Befunde zeigen, wie stark die Transmissionsprozesse zwischen den Generationen sind: Es gibt wenig Hinweise auf einen intergenerationalen „acculturation gap“.

scholarly journals How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

2020 ◽  
Vol 10 (18) ◽  
pp. 6306 ◽  
Author(s):  
Luke Butler ◽  
Tan Yigitcanlar ◽  
Alexander Paz
Keyword(s):  
Conceptual Framework ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Technological Innovations ◽  
Potential Solution ◽  
Wide Range ◽  
Smart Mobility

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

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