Number Of Cars Research Articles

Development and Assessment of a Carpooling Applied System: Perspective of Users from Public-Education Sector

The heavy reliance on private cars is linked not only to harmful environmental impacts, such as gas emissions and global warming, but also to other issues like traffic congestion, road infrastructure maintenance, and the limited availability of parking spaces—significant concerns in many cities. To address these challenges, carpooling has been shown to be an effective solution, as it directly reduces emissions, alleviates congestion, and mitigates the environmental effects of transportation.The aim of this research is to enhance the understanding of carpooling in our society. To achieve this, a carpooling initiative among teachers for their commuting journeys was developed and implemented, followed by an evaluation of the system by a panel of experts. The results showed a 31.9% reduction in the number of cars on the road among participants, with a total of 109,080 km saved based on the reduced number of vehicles.The primary motivation for participants to adopt carpooling was fuel savings, while the reduction of physical fatigue from driving was identified as the second most important factor. Although some barriers to participation were identified, their impact was generally lower than that of the perceived benefits. These findings suggest that carpooling programs should focus on optimizing matching conditions and addressing individual concerns to promote wider adoption.

Exploring the travel behavior of household-owned electric bikes with the consideration of nonlinear effects of factors with the aid of the generalized additive mixed model

Electric bikes (E-bikes) reduce traffic burden in developing countries and provide a lightweight travel option for households. Few studies examined nonlinear effects of factors on e-bike travel behavior. This study adopts the generalized additive mixed model to explore the travel behavior of household-owned e-bikes with the consideration of nonlinear effects of factors based on data from Zhoukou, China. The study confirms that there is a significant nonlinear effect of many factors on the travel behavior of household-owned e-bikes, with the nonlinear effects varying by factors. The lower the number of household bicycles, the higher the travel frequency of household-owned e-bikes. An increase in the number of household cars leads to a decrease in the travel frequency of household-owned e-bikes, and this effect becomes larger as the number of cars increases. The number of household-owned e-bikes is positively correlated with travel frequency, but the correlation weakens after more than 3 e-bikes. There is a negative correlation between the travel frequency of household-owned e-bikes and the number of persons older than 6 when it exceeds 4. The effect of the number of persons older than 6 on the travel frequency of household-owned e-bikes gradually increases when the number of persons older than 6 exceeds 3. Finally, this study puts forward policy suggestions regarding enhancing the attractiveness and competitiveness of household-owned e-bikes. These findings could advance the understanding of the role of e-bikes in households and serve as references for policymakers and planners.

Research on traffic flow prediction method based on LSTM model and PSO-LSTM model

Abstract. With the acceleration of urbanization, the number of cars owned by residents has also significantly increased. The contradiction between the number of cars and the road carrying capacity has become increasingly severe, resulting in very serious congestion. This paper selects road data from 0:00 to 10:00 every morning in Beijing from April 2nd to April 12th, 2016, and uses the average speed of vehicles as a variable to measure road congestion. Based on these data, this article uses LSTM models to predict the speed of vehicles on two roads representing main and non main roads. Research has found that LSTM model has good predictive performance for the speed of vehicles on two roads and is very accurate in predicting the data trend. However, the accuracy of LSTM model in predicting non periodic and highly discrete data is not ideal. This article also uses the PSO-LSTM model to predict one of the roads, and the results show that the model is more accurate than the LSTM model in predicting non periodic data. The prediction of short-term traffic flow will greatly help the transportation department coordinate and manage resources, alleviate traffic congestion, and facilitate residents' travel.

Optimization and energy management strategies, challenges, advances, and prospects in electric vehicles and their charging infrastructures: A comprehensive review

Electric vehicles (EVs) are at the forefront of global efforts to reduce greenhouse gas emissions and transition to sustainable energy systems. This review comprehensively examines the optimization and energy management strategies for EVs and their charging infrastructure, focusing on technological advancements, persistent challenges, and future prospects. By the end of 2023, the number of electric cars on the road globally reached 40 million, with 14 million new registrations recorded in 2023 alone—95% of which were in China, Europe, and the United States. Governments across the globe have introduced incentives and policies to promote EV adoption, and by 2030, EVs are expected to comprise a significant portion of light-duty vehicles in major regions. Despite these encouraging developments, challenges such as range anxiety, the relatively low energy density of 200–300 Wh/kg in Li-ion batteries (compared to 13,000 Wh/kg for petroleum), and insufficient public charging infrastructure remain key barriers to widespread EV adoption. This review also explores the critical role of smart grid technologies, vehicle-to-grid (V2G) systems, and renewable energy integration in supporting the growing EV market. V2G technologies are projected to enhance grid stability by 20–30% and reduce operational costs by 10–15% through load balancing and real-time energy price forecasting. By thoroughly analyzing optimization techniques such as load balancing, dynamic scheduling, and real-time energy management, this paper offers a roadmap for researchers, policymakers, and industry stakeholders to accelerate the integration of EVs into global energy systems and enhance sustainability in urban transportation networks.

Constructing red-black spanners for mixed-charging vehicular networks

Motivated by the recent trend of increasing number of e-cars and hybrid cars, we investigate the problem of building a red-black spanner for a mixed-charging vehicular network. In such a network, we have two kinds of gas/charging stations: electric (black) and the traditional gas (red) stations. Our requirement is that one cannot connect two gas stations directly in the spanner (i.e., no red-red edge), and the goal is to build a linear-size spanner with a bounded stretch factor under this requirement. (In 2-d, it can be shown that a spanner with an optimal stretch factor could have a quadratic size and if one is constrained to build the spanner purely from a given road network then it is impossible to obtain a bounded stretch factor.) Our main results are summarized as follows.1.In 1-d, a linear-size red-black spanner is built to satisfy the ‘no red-red edge’ requirement which achieves the optimal stretch factor.2.In 2-d and under the L2 metric, we build a linear-size red-black spanner satisfying the ‘no red-red edge’ requirement which achieves a stretch factor of 1.998.3.In 2-d and under the L1 metric, a linear-size red-black spanner is built to satisfy the ‘no red-red edge’ requirement which achieves a stretch factor of 3.613.

The impact of COVID-19 restrictions on road traffic and noise pollution of the urban street, a case study from Krakow, Poland

The study determined the impact of restrictions introduced by the Ministry of Health in connection with the COVID-19 pandemic on traffic and sound pressure levels in the university building and its immediate vicinity. Mickiewicza Street was selected for the study. It is one of the city’s busiest streets, located relatively close to the old historic center, and is the main artery connecting the north and south of the city. There are residential buildings on this street, but primarily offices and institutions, as well as schools and universities. Noise near the street and in buildings located relatively close to the road can be a serious problem in places where peace is required (e.g., libraries, reading rooms, university halls). Therefore, the acoustic comfort needed in these places may be disturbed, and the perception of knowledge acquisition may be limited. The aim of the work was achieved through measurements and analysis of street traffic intensity and sound pressure levels, taking into account pandemic restrictions. Then, statistical analyses were performed, which showed significant variability in traffic intensity and sound pressure values in individual periods of the pandemic. The pandemic’s beginning was mainly characterized by a significant decrease in the above data, deviating from the norm. In the pre-pandemic period, an average of 47,733 vehicles passed through the street daily, and the median sound pressure was Leq.OUT = 62.0 dBA outside the building and Leq.INS = 44.0 dBA inside. During the greatest restrictions, a period called “lockdown,” the number of cars driving decreased a little to an average of 44,153 per day, but there were days with 10,000–20,000 cars passing. In turn, noise decreased to 59.9 dBA for Leq.OUT and 43.2 dBA for Leq.INS. Between the first and second waves of infections, traffic was comparable to the post-pandemic period (an average of 69,027 cars per day), and noise also increased to Leq.OUT = 64–65 dBA and close to Leq.INS = 47.5 dBA. Studies have shown that noise on Mickiewicza Street is mainly caused by traffic (correlation coefficient: r = 0.92 for Leq.OUT and r = 0.86 for Leq.INS). The sound pressure level is high outside (Leq.OUT = 63.9 dBA) but relatively low inside the building (Leq.INS = 47.0 dBA) and should not negatively affect university staff and students (Leq.WH < LWH.acc). Based on the analyses, three stages show society’s approach to the COVID-19 pandemic: (1) fear of the COVID-19 pandemic; (2) relaxation after restrictions; (3) getting used to the COVID-19 pandemic. These periods did not correlate with the development of the pandemic or the number of people infected and dead.

PROBLEMY ZRÓWNOWAŻONEJ MOBILNOŚCI W POLSKICH MIASTACH

Sustainable mobility in Polish cities faces numerous challenges arising from dynamic urbanization, demographic changes, and the growing transportation needs of residents. The increase in the number of cars on urban roads leads to congestion, air pollution, and a decrease in quality of life. Transport policies must focus on reducing individual car traffic in favour of public transport, micromobility, and eco-friendly solutions. Key initiatives include creating bike paths, promoting electric scooters, and developing zero-emission vehicles. Financial support, infrastructure modernization, and changing social attitudes toward transport are essential to achieve sustainable mobility. These actions must be supported by local and governmental strategies such as the "European Green Deal" and the "Sustainable and Smart Mobility Strategy." Furthermore, educating the public and engaging residents in transport planning will contribute to improving the quality of urban life and the environment.

Analysis of factors influencing family support for child safety seat legislation based on Probit-Adversarial Interpretive Structure model

Objectives In recent years, China’s motorization process has accelerated, urban road traffic has become increasingly complex, and the safety of children has become increasingly prominent. China aims to encourage the use of child safety seats (CSSs) and stipulates in the Law on the Protection of Minors that “Parents or other guardians of minors shall take measures, such as equipping child safety seats.” However, the utilization rate of such seats in China is still low (<5%, 2021), an important reason is the lack of mandatory legislation. This study focuses on developing cities in China that do not have mandatory legislation on the use of CSS, explores the factors that families support child seat legislation, and explores the impact of children’s feedback on the transmission of values within families and the use of CSS in family decisions. Methods Four hundred and eighty-two subjects in several neighborhoods in Changsha City participated in this survey through an online questionnaire. We use the data to do a Probit analysis to find the influencing factors of parental support for child safety seat legislation, and the Adversarial Interpretive Structure model is used to assess the hierarchy of the influencing factors and the relationship between the influence of internal factors. Results The results showed that educational level and children’s feedback are root cause factors; monthly family income, number of children, confidence level in CSS, number of cars, and others’ behavior are intermediate factors; gender, penalty support, and subjective perception expenditure are surface factors. Conclusion Finally, the results have focused recommendations for the direction of child safety seat legislation, focused recommendations for law enforcement, advocacy, and educational interventions, and recommendations for installation training before the use of CSS.

Development and analysis of a traffic model in the AnyLogic environment

The Federal Work Program on Informatics for the 11th grade (advanced level) indicates the need to consider the issues of constructing simulation models, provides the practical works on motion modeling and processing of experimental results. Development and analysis of simulation models related to road traffic management is interesting and understandable for schoolchildren. These models can be implemented in the AnyLogic environment, for which it is advisable to offer schoolchildren to create a model of an intersection they are familiar with and analyze at what traffic intensity there is no need to install a traffic light, when a traffic light is necessary, what time phases of the traffic light provide the highest capacity of the intersection. The article describes algorithms for creating models of unregulated and regulated intersections; presents tasks for analyzing the capacity of the intersection for different values of the number of cars in each direction of traffic per hour; describes tasks for optimizing the phases of the traffic light to increase the capacity of the intersection; provides examples of project topics for organizing independent work of students.

CAR T-cell therapy for gliomas.

To review the landscape of chimeric antigen receptor T-cell (CAR T) therapy for gliomas as seen in recently published trials and discuss on-going challenges with new cancer immunotherapy treatments. Given how CAR T therapy has revolutionized the treatment of several hematologic malignancies, there has been increasing interest in using immunotherapy, and particularly CAR T therapy for gliomas. Within the past decade, several first in human trials have published early patient experiences showing treatment is generally well tolerated but with limited efficacy, which may be improving with newer evolutions in CAR T design to overcome known resistance mechanisms in glioma treatment. CAR T therapy is a promising avenue of treatment for high-grade gliomas, which have a universally poor prognosis as well as limited therapeutics. There are a growing number of CAR T clinical trials for CNS tumors and thus, an understanding of their treatment strategies, toxicity management, and overcoming resistance mechanisms will be important for both clinical practice and to identify areas for future research.

Predictive Artificial Intelligence Models for Energy Efficiency in Hybrid and Electric Vehicles: Analysis for Enna, Sicily

Developments in artificial intelligence techniques allow for an improvement in sustainable mobility strategies with particular reference to energy consumption estimates of electric vehicles (EVs). This research proposes a vehicle energy model developed on the basis of deep neural network (DNN) technology. This study also explores the potential application of the model developed for the movement data of new vehicles in the province of Enna, Sicily, Italy, which are characterized by numerous attractors and the increasing number of hybrid and electric cars circulating. The energy model for electric vehicles shows high accuracy and versatility, requiring vehicle velocity and acceleration as input data to predict energy consumption. This research article also provides recommendations for the energy modeling of electric vehicles and outlines additional steps for model development. The implemented methodological approach and its results can be used by transport decision-makers to plan new transport policies in Italian cities aimed at optimizing vehicle charging infrastructure. They can also help vehicle users accurately estimate energy consumption, generate maps, and identify locations with the highest energy consumption.

Smart Transportation Systems: IOT-enabled Traffic Management &amp; Vehicle-to-infrastructure Communication

Recently, there has been a substantial increase in the number of cars on the road. Escalating traffic congestion is a widespread problem that folks face on a daily basis. The manual control of traffic-by-traffic police has shown to be ineffective. “Furthermore, the signal's set duration has failed to effectively address this issue, regardless of the level of traffic congestion. This research presents a communication system called Vehicle-to-Blockchain (V2B), which utilizes blockchain technology to enable transparent and decentralized communications. The aim is to optimize the incorporation of blockchain technology into V2X (Vehicle-to-Everything) and IoT (Internet of Things) systems, therefore enhancing the efficiency and effectiveness of future transportation systems. We present a range of advanced applications for blockchain technology, such as a car ownership system that utilizes the multi-token standard, a vehicle grading system, the integration of blockchain with the Internet of Things (IoT), and a decentralized ticket administration system for transportation services. The design places a high emphasis on essential elements such as the seamless integration of data, precise precision, and the establishment of secure connections. Furthermore, it includes a decentralized payment system and marketplace for transportation inside smart cities. Our main focus is on the technical execution of smart contracts in these particular scenarios, highlighting their importance in guaranteeing strong and dependable interactions. Our decentralized approach creates a transportation ecosystem that has the ability to adjust and fulfill the evolving requirements of intelligent urban areas. It is groundbreaking, durable, and capable

Bird metacommunities of urban parks in the pampean region, Argentina

Metacommunities are the set of local communities that are linked by the dispersion of potentially interacting species. The study of metacommunities is important to elucidate the relationship between processes that occur at different spatial scales. However, bird metacommunities in urban parks have been little studied. The objectives of this study were: 1) to analyze the relative role of species dispersal, environmental selection, and stochastic processes shaping urban bird metacommunities; and 2) to analyze the structure of the metacommunities of birds in urban parks. Bird surveys were made in 51 parks of six cities in Buenos Aires province, Argentina. To obtain the metacommunity structure, three elements were analyzed: coherence, turnover, and boundary clumping. We found that the metacommunity conforms to a clementsian structure, in which groups of species respond in a similar way to environmental gradients. The environmental and connectivity variables explained a greater proportion of the variance than the spatial variable. The composition of species was related to the location of the cities, the distance to the rural area, the distance to the urban center, the number of cars passing near parks, and habitat diversity. Due to the clementsian structure of metacommunities, they probably were structured under a species sorting and mass effect process. The number of cars and habitat diversity in the parks would be acting as environmental filters for bird species, while the distance to rural areas and the distance to the urban center would affect species dispersal to the parks. These findings emphasize the importance of maintaining and improving park connectivity and habitat diversity for bird species, managing them as cities grow.

Райдшеринг: проблемы правовой регламентации в России

Ridesharing is the joint movement of several individuals in a single vehicle along a route defined by the vehicle owner. From a legal point of view, this agreement can be regarded as an unnamed joint travel contract. The development of ridesharing is facilitated by the widespread use of smartphones and platforms providing digital services. The main purpose of ridesharing is to save financial resources and to improve the environment by reducing the number of cars on the road. The transport legislation of a number of countries has introduced norms on the legal regulation of shared travel. In the Russian Federation it is necessary to clarify the regulatory framework in this area, as the lack of legal regulation leads to abuse of the right. The purpose of this study is to assess the possibility of legitimisation of ridesharing, to analyse the draft law developed by the Ministry of Transport of the Russian Federation on amendments to the Statute of Road Transport concerning the legal regulation of joint travel, to propose legal measures. The author has developed proposals on the definition of joint travel and ridesharing agreement, defined the legal nature of the agreement, reflected the positive and negative sides of the use of joint travel, analysed foreign experience of their legal regulation.

RESEARCH OF THE COMBUSTION PARAMETERS OF GASOLINE WITH ADDITIONAL HYDROGEN IN A SPARK-IGNITION ENGINE IN EXTERNAL SPEED CHARACTERISTIC MODES

The directions of development and improvement of road transport around the world are inextricably linked to the desire to reduce the use of cars “on traditional fuels” due to limited oil and environmental safety of mankind. Since the modes of external speed characteristic are the most typical for the operation of cars in cities, the study of environmental performance of engines in these modes is an urgent task. Therefore, finding ways to reduce carbon dioxide emissions from automobile engines at high-speed modes is an urgent task. The rapid growth in the number of cars with internal combustion engines and the inevitable decline in world oil reserves necessitate the development and implementation of energy-saving technologies and the use of alternative fuels. Research aimed at finding ways to improve the fuel efficiency and environmental performance of automotive engines is relevant. One of the promising areas is the influence on the combustion process in gasoline engines by using additives of alternative fuels, which include hydrogen. The presented study of the parameters of combustion of gasoline with hydrogen additive in a spark ignition engine at external speed characteristics is a comprehensive analysis of the combustion process of a gasoline-hydrogen mixture and determination of its effect on the concentration of carbon dioxide in exhaust gases by developing a mathematical model that takes into account the composition of the mixture components and features of the combustion process, allows for sufficiently accurate calculation of the operating process of an engine with hydrogen additive at ψ ≤ 10%, its identification by the results of experiments. In the course of the study, dependencies were developed to determine the combustion parameters of the Wiebe model, taking into account the addition of hydrogen to gasoline in the modes of external speed characteristics, and the effect of hydrogen addition on the concentration of CO2 in exhaust gases was analyzed. It is shown that with an increase in the hydrogen additive to 10% by mass fraction to gasoline, there is a decrease in CO2 emissions to almost 30% in the external speed characteristic modes, which corresponds to modern environmental standards for gasoline internal combustion engines.

Overview on potential, opportunities and trends for internal combustion engines

Abstract As one of the most influential markets on the planet, the automotive industry is expanding and, despite the increase in the number of electric cars, its internal combustion engine sector is no exception. Thus, it needs to regularly adapt to the latest trends and changes imposed by the technological innovations that are constantly appearing. Also, in addition to the technical aspect, environmental trends must be taken into account, because they directly influence the evolution of the automotive field, leading it towards a greener future, with an emphasis on ecological and sustainable solutions for current problems. This article aims to offer an overview on the most relevant trends at European level, manifested in the field of sustainability, urbanization, individualization and digitalization, which make possible the restructuring process of the automotive industry, successfully integrating it in the sustainable sectors of the industrial economy. Also, the current situation regarding the European and Romanian automotive sector is presented and there are exemplified a number of ways in which internal combustion engines can be optimized for sustainability, in order to improve the performance of vehicles and their integration into the ecological trends of the moment.

Company cars and household car choices

Tax systems that favour company cars for personal use could cause households to have more cars. It could also affect the choice of fuel type. We investigate the relationship between household car choices and access to a company car through a difference-in-differences design using Norwegian microdata. We find that access to a company car is associated with an increase in the total number of cars and the number of combustion-engine cars. For electric cars, the results are inconclusive. However, wage growth and access to company cars are also positively correlated. Therefore, we cannot interpret the difference in the number of cars between the treatment and control groups as a causal effect of the company car scheme, but as a correlation. Still, existing evidence on the income elasticity of car demand suggests that the increase in the number of cars is unlikely to be driven by wage growth alone.

Driving Towards Sustainable Transportation Systems: A bottom-up Traffic Modal Choices Analysis Using Responsible Management for Future Development Planning

The transportation sector wields substantial influence on society, encompassing economic, social and environmental dimensions of sustainability. Recognising environmentally conscious actions initiated by individuals, particularly at grassroots levels, fosters the development of a pro-environmental social identity. The article aims to analyse the transportation systems from a bottom-up perspective within a municipality. Consequently, three objectives are proposed for this research paper: investigate citizen behaviour regarding transportation, assess the strengths and weaknesses of communities based on citizen perspectives and generate ideas for improving transit through responsible management principles using a bottom-up approach. It has been determined that private car is the most commonly used mode of transportation. The number of cars is the only variable that influences the choice of transportation. A significant positive relationship has been identified between the number of cars and car travels, while a negative relationship has been observed between the number of cars and travels by transit, pedestrian or bicycle. In addition to this, other significant relationships were determined. Regarding the second objective, the majority of the interviewees perceive that the commune lacks any significant strengths. In terms of enhancement opportunities, respondents express a desire for improvements in pedestrian and cyclist infrastructure, transit facilities and the addition of more lanes and roads.

Exploring parental decision-making in school commutes: A structural equation model of public transport utilization and child safety in Thailand

Concern is growing regarding the increasing use of private car in many developing countries, including Thailand. Car usage is rising in Thailand in part because the public transit system is inadequate and unreliable, especially in rural and suburban communities. Often, children’s route to school is unsafe due to the increasing number of cars around the school. This prompts parents to worry about their child’s safety when in transit. The model of travel by public transportation is an alternative for reducing road congestion and improving children’s safety. This study seeks to better understand the factors that influencing parents’ decisions regarding the use of public transportation for their children’s school commutes. Data were gathered through a questionnaire from a sample of 750 parents with children between the ages of 6 and 18 years in Nakhon Ratchasima Province, Thailand. The findings of the structural equation model analysis showed a relationship between service users’ loyalty and the components of satisfaction, trust, expectation, and perception of service quality. The outcomes derived in this study can serve as practical guidelines for public and private transportation system operators to improve service efficiency, meet consumer demand, and foster positive interactions between service users and operators. In this way, this study can lead to important internal and external benefits for the continued development of the public transportation system and motivate more service users to transition to the use of public transportation.

Alternate green and carsharing mobility options: A strategy to fight climate change in oil producing countries

In Kuwait, the number of private cars is significantly high. Hence, reducing private car ownership is one of the main necessary approaches to minimize greenhouse gas emissions. Globally, cities are countering the increase in private car ownership by providing a reliable public transportation system. In Kuwait, public transport consists of a bus system, which is not widely accepted by users since it does not provide connectivity to desired locations. However, providing carsharing services and ride-sourcing can be an alternative mode. In 2019, a service called Careem was launched in Kuwait which is considered a leading ride-sourcing company in the region. Meanwhile, carsharing is not introduced yet to Kuwait. This study aims to evaluate people acceptance of carsharing and evaluate the available transport modes in Kuwait which are Careem, Taxi, Private car and Bus. 373 people participated in this study through an online questionnaire, 40% of them were willing to use carsharing when it is introduced. Additionally, Chi-square test verified that males are more likely to use taxi and Careem services. Moreover, car availability had the biggest influence on not using public transport modes. To evaluate the current transport modes and the accessibility of transport modes, 5 trips with 5 different origins and destinations were selected. The results indicated that private car is the quickest mode followed by Careem. However, public transport showed bad results with no access in Al-Jahra area, with walking time exceeding 30 min from and to the station. The required carsharing vehicles was estimated using the questionnaire data, referring to the number of carsharing in Dubai. It was concluded that there should be at least a single car sharing in 785,398 m2. In order to increase the acceptance of public transport modes, it is highly recommended to extend its tours to cover more regions and reallocate bus stations to reduce walking time for users.