Increase In Vehicle Ownership Research Articles

Research on Aerodynamic Performance Optimization and Drag Reduction of mid-sized SUV on CFD

With the increase of vehicle ownership, the environment and energy issues are highlighted, and reducing vehicle wind resistance has become the key to improving fuel economy. Based on the theory of fluid mechanics and project development experience, this paper develops a medium-sized SUV model for wind resistance reduction. Through the simulation modeling of the vehicle's external flow field, the proportion model wind tunnel test and the optimization scheme research of the exterior shape, the bottom of the vehicle and the engine room, the wind resistance is significantly reduced. Combined with the wind tunnel test results, the actual contribution of each local optimization scheme is verified, and the EGO algorithm is used for further optimization to further reduce the wind resistance coefficient. This paper summarizes the key parts and regularity experience of the aerodynamic drag reduction of the medium-sized SUV model, providing guidance for the development of high-precision vehicle performance in the future. The research methods and results of this paper are of great significance for improving the aerodynamic performance and fuel economy of vehicles.

Calculation of Motor Vehicle Insurance Premiums Through Evaluation of Claim Frequency and Amount Data

Insurance, as a risk control strategy by transferring the burden of risk from one party to another, consists of two main forms: life insurance, which covers financial losses from the risk of death of the policyholder, and general insurance, which involves the transfer of risk against property losses. Motor vehicle insurance has become a common product reflecting the high value and benefits of motor vehicles, which has resulted in an increase in vehicle ownership. Although the increase in the number of vehicles contributes to the increase in road accidents, many owners who suffer losses do not receive the compensation they deserve. In this context, the premium becomes a key factor, where the policyholder pays a certain amount of money to get protection. This research aims to apply risk premium calculation based on claim frequency and claim size data, as conducted by Ozgurel in 2005, especially for each vehicle category and region in XYZ insurance company. The main problem is to optimize the premium calculation to reflect the actual risk, providing a more accurate understanding of the influence of vehicle and regional characteristics in determining a fair and appropriate premium.

Dynamic Characteristics of Three-Body Braking System Considering Tire-Road Friction

Abstract With the significant increase in vehicle ownership in our country, urban traffic conditions have become increasingly congested. Low-speed driving has become more prevalent, leading to more frequent instances of starting and braking. Consequently, the issue of low-speed braking flutter has become increasingly prominent. While the brake is in an open environment, the dust and particles in the air and the debris generated by the brake itself will have an impact on the braking behavior. In addition, according to the theory of modal coupling, the braking stability of the vehicle is also affected by other components. In this paper, different dynamic torsional models of braking system are established according to different braking conditions. Through numerical calculation, the influence of tire parameters, road conditions, and particles on the friction dynamics characteristics of braking system pairs is explored. The results show that the instability of the brake pair system often occurs at low speed. Different tire slip ratios, tire offset factors, and road conditions will lead to different relative motions of the braking system, but the existence of particles in the brake lining-disk interface can enhance the motion stability of the system.

Forecasting the Traffic Flow by Using ARIMA and LSTM Models: Case of Muhima Junction

Traffic operation efficiency is greatly impacted by the increase in travel demand and the increase in vehicle ownership. The continued increase in traffic demand has rendered the importance of controlling traffic, especially at intersections. In general, the inefficiency of traffic scheduling leads to traffic congestion, resulting in a rise in fuel consumption, exhaust emissions, and poor quality of service. Various methods for time series forecasting have been proposed for adaptive and remote traffic control. The prediction of traffic has attracted profound attention for improving the reliability and efficiency of traffic flow scheduling while reducing congestion. Therefore, in this work, we studied the problem of the current traffic situation at Muhima Junction one of the busiest junctions in Kigali city. Future traffic rates were forecasted by employing long short-term memory (LSTM) and autoregressive integrated moving average (ARIMA) models, respectively. Both the models’ performance criteria for adequacy were the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE). The results revealed that LSTM is the best-fitting model for monthly traffic flow prediction. Within this analysis, we proposed an adaptive traffic flow prediction that builds on the features of vehicle-to-infrastructure communication and the Internet of Things (IoT) to control traffic while enhancing the quality of service at the junctions. The real-time actuation of traffic-responsive signal control can be assured when real-time traffic-based signal actuation is reliable.

Decoding Private or Commercial Vehicle Ownership Decisions for Low-Carbon Mobility Transitions: A Systematic Review of the Literature

Increase in vehicle ownership (VO) as a result of rapid economic and population growth and its negative environmental effects have gradually become a potential threat to the physical and social environment. A wide range of factors influences the propensity for VO by individuals or firms; however, the existing body of literature lacks a critical review which provides an understanding of their underlying associations and potential implications for policymaking in one holistic frame. To fill this research gap, this study presents a systematic review of factors affecting private and commercial VO using the PRISMA framework (Preferred Reporting Items for Systematic Reviews and Meta-Analysis). The factors influencing private VO decisions are extracted from the reviewed articles; subsequently, the identified factors are topologically divided into seven categories. The findings show that most studies identified the factors contributing to VO as related to socio-economic, demographic, and built environmental characteristics. A lack of research has been identified for attitudinal, technological, and parking-related variables. It is also concluded that there are gaps in the knowledge base on factors contributing to the commercial VO of a business establishment. Designing informed policy measures based on such factors that can induce a sustainable transition in the mobility sector is important to mitigate transportation-related negative externalities on the environment. The overall review findings offer actionable guidance for low-carbon mobility transition and outline a future research agenda for academic researchers and decision makers. The quantifiable factors revealed in this study are expected to assist policy makers in discouraging VO propensity among individuals or firms.

Application of a new type of lithium‑sulfur battery and reinforcement learning in plug-in hybrid electric vehicle energy management

The continuous increase in vehicle ownership has caused overall energy consumption to increase rapidly. Developing new energy vehicle technologies and improving energy utilization efficiency are significant in saving energy. Plug-in hybrid electric vehicles (PHEVs) present a practical solution to the arising energy shortage concerns. However, existing battery technologies restrict PHEV application as the most popular lithium-ion battery has a relatively high capital cost and degradation during service time. This paper studies the application of a new type of lithium‑sulfur (LiS) battery with bilateral solid electrolyte interphases in the PHEV. Compared with metals such as cobalt and nickel used in conventional lithium-ion batteries, sulfur utilized in LiS is cheaper and easier to manufacture. The high energy density of the new LiS battery also provides a longer range for PHEVs. In this paper, a PHEV propulsion system model is introduced, which includes vehicle dynamics, engine, electric motor, and LiS battery models. Dynamic programming is formulated as a benchmark energy management strategy to reduce energy consumption. Besides the offline global optimal benchmark from dynamic programming, the real-time performance of the LiS battery is evaluated by Q-learning and rule-based strategies. For a more comprehensive validation, both light-duty vehicles and heavy-duty vehicles are considered. Compared with lithium-ion batteries, the new LiS battery reduces the fuel consumption by up to 14.63 % and battery degradation by up to 82.37 %.

Kent İçi Alışveriş Merkezlerinin Mimari Özelliklerinin Kullanıcı Tercihlerine ve Davranışına Etkisi: Van Avm Örneği

Alışveriş mekânları tarihte çeşitli formlarda ticari yaşama dahil olmuşlardır. Günümüzde gündelik hayatın bir parçası haline gelen, bir buluşma ve sosyalleşme mekânı olarak hizmet veren alışveriş merkezleri daha çok kapalı mekânlardan oluşan, alışveriş harici farklı fonksiyonları içeren kamusal bir mekân niteliğindedir. Kent merkezlerinde yer alan bu yapılar zaman içinde ekonomik gelişmeler ve araç sahipliğinin de artmasıyla kent çeperlerinde konumlanmaya başlamıştır. AVM’lerin yaygınlaşması, bu alışveriş formunu bilindik-geleneksel çarşılara bir yandan alternatif haline getirirken bir yandan da sayısal olarak hızla çoğalmasıyla oluşan rekabetçi ortam, mimari özellikleri ve sunulan olanakları bakımından AVM’lerin tasarımında farklılık arayışına neden olmaktadır. Bu çalışma AVM’lerin mimari özelliklerine odaklanarak, kullanıcıların değişen tercihlerini ve AVM’nin mimari özelliklerine bağlı olarak alışveriş temelli davranışlarını tespit etmeyi hedeflemiştir. 170 kişinin katıldığı anket çalışması Van AVM’de gerçekleştirilmiş, ziyaret alışkanlıkları ve erişim yöntemleri, AVM’yi alışveriş için tercih sebebi, ziyaret sıklığı ve geçirilen süreyi etkilediği düşünülen, mekânın algısal duyusal koşulları sorgulanmıştır. Sonuçlar, AVM’lerin mimari özelliklerinin ve olanaklarının kullanıcıların alışveriş davranışlarını, ziyaret sıklığını ve tercihlerini etkilediğini göstermiştir.

Modelling of Pedals Pressing Mechanisms for Low Speed Driving in Road Traffic Delay

Road traffic delay is imminent in big cities around the world including Kuala Lumpur, due to the increase in vehicle ownership, weather condition, road blocks by authorities and ongoing infrastructure projects at particular point of the road. Previous literature shows that the average time spent by drivers in driving under road traffic delay is about 30-53 minutes per day. Within the delay, regular pressings of the brake and accelerator may lead to leg and body fatigue, hence may give detrimental effect on the driver in the long run. This paper aims to mimic the pedal pressing and releasing mechanism in replacing the leg activities during road traffic delay, such that the driver will no longer need to recurrently pressing both pedals, thus reduce the fatigue. In replicating the pressing mechanism, a linear electromechanical actuator is designed for this purpose due to its high force density as well as good response time. The mathematical model of the actuator is first developed and integrated with car dynamic model in Simscape model. All parameters used for simulation purposes were taken from an actual electromechanical actuator used for the similar application. Simulation performance evaluation was conducted on a virtual environment for the integrated models and the response of the models were investigated. As a result, the actuator model is capable to produce the desired output force that is similar with human leg during pressing activity, with about 200 N force. The model was coupled with tuned PID controller, and the actuator was also able to produce an acceptable time response, where the vehicle is brought to a complete stop within less than 1 second, which is closed to the actual driver’s leg activities during the pedal pressing in a road traffic delay.

A role for community-level socioeconomic indicators in targeting tuberculosis screening interventions

Tuberculosis screening programs commonly target areas with high case notification rates. However, this may exacerbate disparities by excluding areas that already face barriers to accessing diagnostic services. We compared historic case notification rates, demographic, and socioeconomic indicators as predictors of neighborhood-level tuberculosis screening yield during a mobile screening program in 74 neighborhoods in Lima, Peru. We used logistic regression and Classification and Regression Tree (CART) analysis to identify predictors of screening yield. During February 7, 2019–February 6, 2020, the program screened 29,619 people and diagnosed 147 tuberculosis cases. Historic case notification rate was not associated with screening yield in any analysis. In regression analysis, screening yield decreased as the percent of vehicle ownership increased (odds ratio [OR]: 0.76 per 10% increase in vehicle ownership; 95% confidence interval [CI]: 0.58–0.99). CART analysis identified the percent of blender ownership (≤ 83.1% vs > 83.1%; OR: 1.7; 95% CI: 1.2–2.6) and the percent of TB patients with a prior tuberculosis episode (> 10.6% vs ≤ 10.6%; OR: 3.6; 95% CI: 1.0–12.7) as optimal predictors of screening yield. Overall, socioeconomic indicators were better predictors of tuberculosis screening yield than historic case notification rates. Considering community-level socioeconomic characteristics could help identify high-yield locations for screening interventions.

A Review of Engine Emissions Testing Methods for Environmental Sustainability

With the increase of vehicle ownership, vehicle emission pollution has become a major source of air pollution. The control of automobile pollutant emissions is one of the effective methods to reduce air pollution. Domestic and foreign exhaust pollutant testing methods for in-use vehicles have been gradually developed from the original idling method to the double-idling method and the simple working condition method. There are many methods to test the exhaust pollutants of in-use vehicles, but the test operation cycle, gas analysis principle, cost, application occasions and the accuracy level of various testing methods are different. This paper introduces the idling method, the working condition method and the on-board emission testing method for detecting vehicle emission pollutants. Two optimized methods for detecting automotive emission pollutants (namely the double-idle method and the simple transient working condition method) are also introduced.

Distribution Analysis and Forecast of Traffic Flow of an Expressway Electronic Toll Collection Lane

AbstractWith the rapid increase of vehicle ownership in China, toll collection stations on expressways have become some of the most congested areas. Compared with a manual toll collection system (M...

Examining the long term impacts of COVID-19 using an integrated transport and land-use modelling system

ABSTRACT This paper investigates the long-term impacts of COVID-19 on transport and land-use systems through understanding changes in households’ long-term choices, such as residential location choice, travel tool ownership and type choice. For that, it first develops two possible scenarios, which are, (i) without COVID-19 pandemic, (ii) with COVID-19 pandemic. Specific behavioural attributes of households associated with each scenario are modelled and simulated up to the year 2030 within an integrated transport, land-use and energy (iTLE) model. iTLE is an agent-based microsimulation model developed for Nova Scotia, Canada. Results show that, if COVID-19 persists, most people who do not own a car will continue restraining themselves from purchasing one up to the year 2027. Most households having heads aged between 30 and 75 years and a yearly income above $100,000 will purchase new vehicles in year 2022, making the vehicle purchase rate doubled in the province. In terms of vehicle type choice decision, the use of SUVs will increase by 25% and 27% by 2025 and 2030, respectively, compared to year 2020. The pandemic will cause a 0%–74% increase in vehicle ownership in suburban areas by 2030. Additionally, the ability to ‘work from home’ and online school facilities may influence people to live further away from downtown. The results of this study will offer transport and land-use planners insights into how households’ long-term decision making may evolve in the future due to the COVID-19 crisis and help develop policies to continue focusing on the sustainability goals for communities.

Comparison of Driving Forces to Increasing Traffic Flow and Transport Emissions in Philippine Regions: A Spatial Decomposition Study

The warming of the climate system has raised a lot of concerns for decades, and this is traceable to human activities and energy use. Conspicuously, the transportation sector is a great contributor to global emissions. This is largely due to increasing dependence on private vehicles and a poorly planned public transportation system. In addition to economic impacts, this also has significant environmental and sustainability implications. This study demonstrates a novel approach using spatial logarithmic mean Divisia index (LMDI) to analyze drivers of traffic flow and its corresponding CO2 emissions in regions through an illustrative case study in the Philippines. Population growth is revealed as the main driver to traffic flow in most regions with the exception of a few regions and the national capital which are driven by economic activity. The economic activity effect shows positive trends contributing positively to traffic flow which is greatly linked to income level rise and increase in vehicle ownership. Concerning the impacts, results revealed that an increase in economic activity generally causes traffic intensity to decrease, and switching to more sustainable modes is not a guarantee to reduce carbon emissions. The authors recommend increasing equity on the appropriation of transport infrastructure projects across regions, quality improvement of public transport services and promoting mixed-use development.

Bicyclists’ behavioral and physiological responses to varying roadway conditions and bicycle infrastructure

Population growth increase of vehicle ownership, and development patterns have resulted in greater levels of congestion, pollution, and crash frequency. A proposed solution to lessen current transportation system demands is to increase the share of bicycle trips. Furthermore, as cycling is perceived by some as both a dangerous and stressful mode of transportation, understanding the factors that lead to less comfortable and stressful riding, can help drive bicycle infrastructure development. To establish a more robust understanding of the behaviors of bicyclists and how infrastructure design and operations influence them, a bicycle simulator was used to evaluate bicyclist performance measures of velocity, horizontal displacement, and physiological responses (i.e., galvanic skin response) while riding in varying roadway conditions. Results showed that bicyclists in the bike lane condition, had a GSR reading 1.77 peaks per min less than when cycling in the no bike lane condition. When bicyclists were in no bike lane condition, the GSR reading was not affected by vehicle speed but it was affected by the vehicular volume. Additionally, females felt less comfortable when riding in either bike condition, even though they reported that they were “Strong and Fearless” riders. The methodology used for this study sets forth the foundation for future research that could evaluate varying facility designs and a wider range of individuals.

Travel Time Comparison Using Google Map and OSM Tracker

In India, people’s socio-economic characteristics in society have changed over the decades which have resulted in increase of vehicle ownership at a huge rate which poses a lot of problem in both traffic control and management system. In the area where continuation is impossible, congestion can be overcome by managing and controlling the traffic. There are major developments in ITS (Intelligent Transportation System) which needs travel time as a major input. Measure the quality of any transportation network travel time is a very popular parameter. The estimation of travel time in urban network became more difficult because of the rapid change in the system and traffic. Emerging technologies such as GPS which become widely available within the last decade, can offer promising improvements in traffic monitoring technologies. Probe vehicles equipped with relatively cheap devices provide researchers with vast amounts of disaggregate traffic data that can be easily used for determining link travel speeds. This study is done in order to estimate the impact of different travel modes on travel time with different day. Data has been collected in a study stretch of 8.1 km length in Khardaha to Dunlop more, KOLKATA using mobile GPS application (OSM tracker in android Operating System) . Different private modes of transportation such as motor bike, bus and car have been used as test vehicle for the collection of data in different traffic flow scenarios in different times and also days. Latitude, longitude, speed and the travelled path at one second interval has been extracted from the GPS application. After completing a data collection, data extracted from the Osm Tracker that is GPX file to convert the value into Excel format. The travel time and average speed of different modes has been compared and the effect of vehicle composition on travel time and average speed has been analyzed.

The Implementation of the Smart City Process—Researchers’ Knowledge in Detecting Transport System Defects

Although the Republic of Moldova has experienced massive increase in vehicle ownership and use, some of the latest advances in how to approach and nurture public space are underutilized. This article summarizes the basic findings of a project aimed at transfer of knowledge and the implementation of the smart city process in Chișinău, Moldova. Chișinău presents a perfect opportunity for full-scale transformation regarding mobility in the smart city process. In its current state, where there are still enough opportunities to make significant improvements and for the region itself, the Republic of Moldova falls into the category of middle- to lower-income countries. Moreover, this article looks at the difficulties of preparing a smart mobility strategy while under the effect of the current COVID-19 pandemic in the form of social distancing by the city. The subject of study is to determine whether a long-distance strategy can be properly created and introduced, mostly based on proper communication. Key data sources were examined and chosen as the basis for determining weaknesses and as a basis for determining the main pillars. While challenging, this paper finds distanced knowledge transfer and planning to be achievable.

Collaborative Strategies and Simulation of Vehicle Group Behaviors for Off-Ramp Areas

With the increase of vehicle ownership and the rapid growth of urban traffic, the problem of congestion in the off-ramp area of the main expressway has become the main factor restricting overall section efficiency and inducing traffic accidents. This paper focuses on the problem of group collaborative lane-changing behaviors of off-ramp vehicles and through vehicles in off-ramp areas and proposes four kinds of vehicle group collaborative strategies based on different road space balance conditions. According to a three-lane expressway scene, a VISSIM-based simulation model is built and the optimization scheme is simulated and evaluated. The simulation results show that with the increase of traffic flow in off-ramp areas, a flow-balance strategy for downstream lanes where off-ramp vehicles merge with the outside lane in advance is more advantageous. When vehicles are leaving the main road, if traffic flow is heavy, the flow-balance strategy for lanes where off-ramp vehicles merge with the outside lane in advance (for example, the proportion of off-ramp vehicles in three lanes is 0 : 0 : 1) is better; otherwise, when the traffic flow on the main road is relatively small, the flow-balance strategy for lanes where off-ramp vehicles are distributed in lanes with different ratios (e.g., 1 : 3 : 6) is better. What is more, for future traffic management in connected vehicle environments, it can be concluded that collaborative vehicle lane-changing strategies with different traffic flow states can help to enhance traffic efficiency.

Air pollution in Kenya: a review

Rapid urbanization, the corresponding increase in vehicle ownership, and the continued use of solid fuels as an energy source have resulted in the deterioration of air quality in Kenya. Despite this, there is no publicly available official source of data on air pollution in the country. This article provides an overview of published studies that report the concentrations of widespread ambient pollutants, outline major themes, and identify data gaps. This review reveals that since the 1980’s particulate matter (PM) concentrations in some Nairobi locations, such as the industrial area, have been at dangerously high levels. Almost all of the studies included show that PM concentrations in Nairobi violate the World Health Organization (WHO) guidelines. Moreover, black carbon (BC) concentrations in Nairobi are among the highest in the world, indicating the need for cleaner vehicles in the city. There has been much less work done measuring the levels of gaseous pollutant concentrations in Kenya. Based on these findings, policies to reduce air pollution in Kenya and monitoring strategies to fill in the existing gaps are presented.

Alleviating Urban Traffic Congestion: Case of Gaborone City

Cities in the developing world have not been spared from the congestion problems due to economic growth and subsequent increase in vehicle ownership by both private and public owners. Traffic congestion is a major challenge in Gaborone, especially in the Western by pass road of the city resulting in massive delays, a decrease in productivity, an increase in environmental pollution, and an increase in travel time. The objective of this paper is to analyse urban transportation congestion, identify causes and proffer solutions through engaging road user perceptions, transport planning authorities and transport policy makers in Botswana. The study employed an exploratory design to sample 208 respondents through the administration of questionnaires. Quantitative data were used and analysed using SPSS v 21. The study revealed that there is massive influx of motor vehicles in the city, inadequate urban infrastructure, poor infrastructural planning, poor or no urban transport policy framework, and Road Traffic Incidents were the main causes of traffic congestion. The effects of traffic congestion are higher transport costs, massive delays, pollution, decreased productivity and stress to motorists as a result of longer travelling time. The study recommends improvement of road infrastructure especially intersections with traffic circles, implementation of mass transit system in transporting public within the city, public education on effects of congestion, implementation of smart urban transportation, mobility technologies (transport intelligence systems) and implementation of non-motorised mobility. Keywords : congestion, Gaborone, urban transport, Botswana, mass transit, Main Mall, central business district. DOI: 10.7176/JESD/11-8-06 Publication date: April 30 th 2020

Green Traffic-Oriented Heavy-Duty Vehicle Emission Characteristics of China VI Based on Portable Emission Measurement Systems

With a continuous increase in vehicle ownership, vehicle emissions have become one of the main sources of air pollution in China. Serious air pollution is a great threat to human health and life. The China VI regulations, which adopt strict particulate matter (PM) and nitrogen oxide ( ${\mathrm {NO}}_{x}$ ) limitations, have been implemented. As one of the best technologies for measuring vehicle emissions, portable emission measurement systems (PEMSs) have gained attention. In this work, the characteristics of China VI heavy-duty vehicle emissions were investigated with a PEMS. The effects of road conditions on NO x , hydrocarbon (HC), carbon monoxide (CO), PM and particle number (PN) pollutants were analyzed based on distance-based emission factors. The results show that the gaseous pollutant levels of NO x , HC and CO for China VI vehicles are much lower than those for China V vehicles. The average distance-based emission factors of NO x CO and HC decreased by 88%, 98%, and 62.7%, respectively. Based on the power-based window method, the PEMS test results for NO x , HC and CO are 460 mg $\cdot $ (kWh)−1, 192 mg $\cdot $ (kWh)−1 and 37.5 mg $\cdot $ (kWh)−1, respectively. According to the PEMS tests, approximately 88%–95% of the particles are in the 10–100 nm class based on three typical operational modes, which represent approximately 0.08%–0.13% of the total particle mass. These heavy-duty vehicles can satisfy the requirements of the PEMS China VI standards. This study emphasizes the importance of obtaining real-world measurements of heavy-duty vehicles to improve the accuracy of emission factors in the development of emission inventories in China.