Car Users Research Articles

Automatic Vehicle Fueling System using PLC Controlled Robotic Arm - A Simulation Design.

The objective of this research is to simulate an automatic fuelling system using a PLC LogixPro simulation. The system includes the "FASS" concept, which is Fast, Accurate, Safe and Simple, to allow car users to have an efficient fuel filling system. The design concept consists of three processes - identification of the vehicle, payment, and filling with the fuel. The first process identifies the presence of the car by the in-floor weight sensors. The weight sensor identifies the car, locks it in position, and activates the payment system. The second process activates the payment system. After payment is completed, the fuel cap will be opened to enable the system to start filling the fuel. If the payment doesn't go through the car will be released, manual operation will be initialized, and the entire system will be reset. A timer is included in the payment section to process the payment. In the third process, the filling arm is extended to the car, the fuel cap is opened, the fuel pump is inserted into the tank, and fuel is directed into the tank. Once the tank is full, filling is stopped, the pump is ejected, the fuel cap is closed, and the arm returned back to its position. Thus, an automatic vehicle fuelling system is created to overcome the problems of poor safety and longer waiting time during peak hours. The fuel cap is activated and deactivated by pressure and the sensor filler is stopped by a level sensor. The pump insert is activated and deactivated by a photosensor.

A Price Too High: Injury and Assault among Delivery Gig Workers in New York City

The occupational health burden and mechanisms that link gig work to health are understudied. We described injury and assault prevalence among food delivery gig workers in New York City (NYC) and assessed the effect of job dependence on injury and assault through work-related mechanisms and across transportation modes (electric bike and moped versus car). Data were collected through a 2022 survey commissioned by the NYC Department of Consumer and Worker Protection among delivery gig workers between October and December 2021 in NYC. We used modified Poisson regression models to estimate the adjusted prevalence rate ratio associations between job dependence and injury and assault. Of 1650 respondents, 66.9% reported that food delivery gig work was their main or only job (i.e., fully dependent). About 21.9% and 20.8% of respondents reported being injured and assaulted, respectively. Injury and assault were more than twice as prevalent among two-wheeled drivers, in comparison to car users. Fully dependent respondents had a 1.61 (95% confidence interval (CI) 1.20, 2.16) and a 1.36 (95% CI 1.03, 1.80) times greater prevalence of injury and assault, respectively, than partially dependent respondents after adjusting for age, sex, race and ethnicity, language, employment length, transportation mode, and weekly work hours. These findings suggest that fully dependent food delivery gig workers, especially two-wheeled riders, are highly vulnerable to the negative consequences of working conditions under algorithmic management by the platforms. Improvements to food delivery gig worker health and safety are urgently needed, and company narratives surrounding worker autonomy and flexibility need to be revisited.

THE INFLUENCE OF SERVICE QUALITY AND COMPANY IMAGE ON CONSUMER SATISFACTION AT CARRO INDONESIA.ID HARAPAN INDAH BEKASI BRANCH

The era of progress and development has made four-wheeled vehicles, or cars, a basic necessity for the middle to upper-class society. This is evident from the increasing purchase of used cars every year. The number of car users continues to rise, resulting in various complex issues. One of the main issues is the worsening traffic congestion, leading to an increase in road accidents. The automotive service industry continues to evolve, providing adequate facilities. When these services are delivered effectively, they are used to enhance customer satisfaction. A quantitative approach is employed, and it has a cause-and-effect relationship design for the specific variables. The research findings are as follows: service quality has a positive and significant impact on customer satisfaction, with low significance (0.000 < 0.05). Similarly, the company image has a positive and significant effect on customer satisfaction, with low significance (0.004 < 0.05). Furthermore, there is a positive and significant simultaneous impact of the variables on customer satisfaction, as evidenced by the high F-value (191.345 > 3.136) and low significance level (0.000 > 0.05). In conclusion, the null hypothesis (H0) is rejected, and the alternative hypothesis (Ha) is accepted, indicating that service quality and company image significantly influence customer satisfaction. Keywords: Service Quality, Corporate Image, and Customer Satisfaction

Policy dialogue: Key factors for the success of transit-oriented development infrastructure 3.0 in big cities in Indonesia

This research aims to determine the factors driving the success of four large cities in Indonesia in implementing Transit-Oriented Development (TOD) infrastructure policies beyond the eight TOD 3.0 Principles. Only a few studies like this have been conducted. The research uses qualitative methods and is supported by in-depth interviews with stakeholders, community leaders, community groups, and service users. The research findings reveal six themes: policy dialogue, organizational structure and coordination, changes in community habits, resources, dissemination and communication, and transportation and connectivity services. The characteristics of the community in the study area that prioritize deliberation are important determinants in policy dialogue and are involved in determining policy formulation. The city government has established a comprehensive organizational and coordination structure for the village and sub-district levels. The Government controls infrastructure development activities, establishes a chain of command and coordination, and encourages people to change their private car usage habits. The city government combines all this with the principle of deliberation and conveys important information to the public. The research highlights the differences in TOD implementation in Indonesia compared to other countries. Specifically, the existence of policy dialogue and the direct involvement of community members influence the level of program policy formulation and are crucial in controlling urban infrastructure development.

Examining Congestion Pricing Scheme Effectiveness Using the Travel Time Congestion Index

This study investigated the effectiveness of congestion pricing (CP) using the travel time congestion index (TTCI), a congestion assessment tool, in Hyderabad, India. Initially, a set of hypothetical mode choice scenarios under the CP scheme were designed to collect car users’ perceptions based on a stated preference (SP) experiment. Based on the SP survey data, discrete travel behavior models were developed to estimate the probable modal trade-off among cars, two-wheelers, and public buses under the generated CP scenarios. Using the existing traffic, geometric, and land-use data from the most congested corridors of the study city, TTCI values were estimated for the base and future conditions, followed by commuter volume estimation for the different conditions using vehicle occupancy factors. Further, the commuter volume derived from modal trade-off under CP scenarios was converted into traffic volume for the identified congested corridors. Finally, the TTCI values were re-estimated using the final traffic volume and compared across worst, best-worst (intermediate), and best case CP scenarios for the base and future years. An annual average growth of 5% in traffic volume was considered. The results show a significant improvement in TTCI values across all identified corridors under CP implementation, indicating its effectiveness toward congestion alleviation. Such demonstration of CP effectiveness could play a major role in making CP a successful travel demand management measure for cities burdened with congestion.

K-Nearest Neighbor Algorithm and Case Base Reasoning on Xenia Car Damage Detection Expert System

PT Astra Daihatsu Motor or commonly abbreviated as ADM is the Sole Agent Brand Holder (ATPM) of Daihatsu cars in Indonesia. Xenia car is one of the most popular cars in Indonesia. Although there are many Xenia car users, it is not uncommon for Xenia cars to experience damage caused by the ignorance of car users, where the car user only knows how to use it but does not know how to maintain the car properly and correctly. Before damage occurs to the car, the car usually experiences several symptoms of damage that the user does not realize. With that, there are often difficulties experienced by users to find out the type of damage to the car. The purpose of applying and designing applications in this study is to apply the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to Xenia cars and to design and build applications with the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to web-based Xenia cars. This research uses the Research and Development method. Based on the results of research from previous cases, the new case has similarities with 5 cases and the highest similitude value is with the highest type, namely the type of Injector Malfunction damage with a value of 0.625 or around 62.5%. This expert system application can detect and determine the results of Xenia car engine damage detection by applying a method that looks for the closest similarity value of new cases to old cases, namely the Case Based Reasoning method and the K-Nearest Neighbor Algorithm looking for the closest neighbors of the same weight value. This web-based expert system can be used by users to find the results of Xenia Car engine damage detection experienced by determining the symptoms that are available in web-based applications. This web-based application can also provide solutions from the detection results of the type of Xenia car engine damage.

Effect of copper addition on mechanical properties and microstructures of LM25 cast alloys

The use of aluminum alloys in automobiles is expanding, and the potential for additional increases is significant. Further growth will be determined by improvements in material qualities for existing applications or the discovery of new applications. Alloy A-356 (LM25) is commonly employed for high-quality alloy wheel rims in various motor vehicles, constituting 40% of global car usage. This study introduces 0.2% Cu into the Al–Si–Mg alloy system to enhance the mechanical properties. The alloy blend is cast into a metal mold, subjected to a 4-h cure at 540 °C, quenched with water, and precipitation hardened for 12 h at 1800 °C. Optical and scanning electron microscopes are utilized to analyze the alkali microstructure. The mechanical properties of alloyed and unalloyed castings, including hardness and tensile test results, are examined in untreated and heat-treated states. Fracture surfaces of tensile specimens are scrutinized. Intermetallic compounds formed during solidification are studied using scanning electron microscopy and x-ray diffraction analysis. The tensile strength under unalloyed (LM25) and alloyed (LM25 + 0.2 wt. % Cu) conditions before and after heat treatment [(72, 165.4 and 88.3, 237.1) and (78, 179.6 and 98, 252.9, respectively)] shows a significant increase.

Behaviors of pregnant women regarding travel – the case of Türkiye

Introduction and aim. With the development of transportation facilities and options, people can now travel easily. With women having a greater presence in the workforce, pregnant women can work until the eighth week before childbirth. This study was conducted to examine the behaviors of pregnant women regarding travel. Material and methods. The data for this cross-sectional and descriptive study were collected from 519 pregnant women who voluntarily participated in the research and met the research criteria. The data were analyzed using the SPSS 24 software package. Results. The average age of the participating pregnant women was 27.49±0.17, with 63.8% residing in urban areas, 74.8% be ing primiparous, and 47.6% being in the third trimester of pregnancy. A decrease in travel and car usage during pregnancy. The use of bus, train/tram/metro, taxi, bicycle/scooter, and motorcycle decreased during pregnancy, while use of car, plane, and ship/ferry increased. 81.9% of women always wore a seat belt during pregnancy. There was a statistically significant difference between the educational level of women and their car usage (p<0.005). It was found that women wore seat belts more frequently in the third trimester. As the number of pregnancies increased, the frequency of seat belt usage decreased. Conclusion. A decrease in the frequency of travel was observed among women during pregnancy. The levels of seat belt usage and correct seat belt fastening were unsatisfactory.

Telecommuting and Travel Behaviour: A Survey of White-Collar Employees in Adelaide, Australia

COVID-19 prompted a significant number of employees to shift to remote work for the first time, potentially reshaping future work patterns. This study examines the post-COVID impacts on telecommuting, commuting behaviour, travel activities, and lifestyles in the city of Adelaide, South Australia. A multivariate nominal logistic regression analysis of 305 post-restriction survey responses revealed that home distance from the CBD, industry, occupation, and income significantly influence post-COVID telecommuting trends. Individuals living over 20 kilometres from the CBD, those in professional or managerial roles, and higher-income earners (>125k) are more prone to regular telecommuting, highlighting the impact of commute lengths, job flexibility, and financial resources on the ability to work remotely. The study revealed a higher adoption of telecommuting post-COVID, with more individuals working from home and telecommuting more often each week. This led to reduced usage of private cars and public transport, indicating a decrease in overall travel frequency. Respondents also adopted flexible work schedules, resulting in fewer peak-hour commutes, which would have resulted in lower congestion and emissions and led to more sustainable travel practices. The study also investigated future telecommuting perspectives, revealing a preference for remote work 3–4 days a week. Some respondents who initially could not telecommute have since considered it feasible and want to adopt it. Notably, about 25% of respondents would even change jobs for flexible, home-based work arrangements. The study’s results suggest that remote work frequency may influence individuals’ future house location preferences. These findings offer valuable insights for sustainable transport and urban planning considerations in the post-COVID era.

Multi-objective Optimization Framework for Trade-Off Among Pedestrian Delays and Vehicular Emissions at Signal-Controlled Intersections

Traffic congestion has several adverse effects on urban traffic networks. Increased travel times of vehicles, with the addition of excessive greenhouse emissions, can be listed as harmful effects. To address these issues, transportation engineers aim to reduce private car usage, reduce travel times through different control strategies, and mitigate harmful effects on urban networks. In this study, we introduce an innovative approach to optimizing traffic signal control settings. This methodology takes into account both pedestrian delays and vehicular emissions. Non-dominated sorting genetic algorithm-II and Multi-objective Artificial Bee Colony algorithms are adopted to solve the multi-objective optimization problem. The vehicular emissions are modeled through the MOVES3 emission model and integrated into the utilized microsimulation environment. Initially, the proposed framework is tested on a hypothetical test network, followed by a real-world case study. Results indicate a significant improvement in pedestrian delays and lower emissions.

Examining the relationship between car ownership, car use, and exercise: Role of the built environment

Although owning a car allows people to access distant fitness centers and may promote exercise, car use may encourage sedentary behavior and reduce exercise. There is no empirical evidence on the relationship between car ownership, car use, and exercise, and whether improving the built environment is useful to encourage exercise by affecting car ownership and usage. Through a survey of 1049 respondents in Shanghai and subsequent path analysis, we investigate the relationship between the built environment around residences and workplaces, car ownership, car usage for work and non-work trips, and the duration of exercise weekly. While car ownership directly fosters exercise, it indirectly reduces exercise due to increased car usage for work and non-work trips, and the negative effects outweigh the positive. Moreover, the built environment around residences and workplaces affects exercise through car ownership and usage. People living in dense and downtown neighborhoods conduct more exercise because of the fewer likelihood of owning and/or using cars. More intersections and transit stops around residences and mixed land use around workplaces reduce exercise by increasing car ownership and/or car usage. We conclude that reducing car ownership and usage can promote exercise, and built environment interventions are effective in enhancing public health outcomes.

Identification and evaluation of challenges in commercial vehicle transport business in India post-implementation of BS-VI emission norms

Commercial vehicles are an indispensable part of logistics and public transport in India. It is a major source of greenhouse gas emissions too. Several countries across the world have implemented stringent statutory norms for vehicular emissions that all the automobile OEMs (original equipment manufacturers) have to adhere to while designing, producing, and after-sales the vehicle. India has also mandated BS-VI (Bharat Stage- Six) emissions norms from April 2020. Though the motive of the implementation is commendable and will prove good to society at large in the years to come, its implementation of it has created enormous challenges for OEMs and users, particularly commercial vehicles. There are several reasons attributed to it. This paper is an attempt to identify and evaluate the challenges in the commercial vehicle transport business after the implementation of BS-VI emission norms. Various challenges are identified through literature and interactions with experts and users. The challenges are then ranked according to their significance using AHP (Analytic Hierarchy Process). The challenges are then grouped into cause-and-effect categories using DEMATEL (Decision making trial and evaluation laboratory). The outcomes of the analysis would help OEMs, policymakers, and automobile users to take appropriate decisions and corrective actions for overcoming especially the maintenance and human related challenges.

Analyzing satisfaction and loyalty of car users in central Europe

ABSTRACT This study analyzes the satisfaction and loyalty levels of car commuters in Central Europe using data collected within the EU-funded project ‘Smart-Commuting.’ A Fuzzy-Hybrid TOPSIS approach is employed to measure synthetic indicators of satisfaction and loyalty among commuters. Subsequently, those expressing high satisfaction and loyalty to cars are identified through Fuzzy-Clustering Analysis. Finally, Probit estimation is utilized to investigate individual socioeconomic effects on the elevated levels of satisfaction and loyalty in car-based commuting. Results suggest that these are influenced by several socio-economic factors, including travel distance, travel time, occupation, and income. Gender and age also play a role, with males and older individuals exhibiting a higher inclination to drive. These findings can be instrumental in guiding mobility measures aimed at promoting sustainable commuting, such as incentives for public transport, improvements to cycling and walking infrastructure, and the implementation of flexible working arrangements. This is particularly relevant in Central Europe, where high car-dependency for commuting is well-documented.

How to be a winner of future vehicle maintenance services: consumer preference for vehicle self-diagnosis and fault prediction system in next-generation vehicles

ABSTRACT Alternative fuel vehicles and smart cars are rapidly changing the automobile market, affecting vehicle maintenance. Among them, vehicle self-diagnosis and prediction functions, some of the technologies to be installed in next-generation vehicles, are important technologies that can change the business model of the current vehicle maintenance market. Technical research on these technologies continues, but few studies estimate consumer preference and the future economic value of the technology. Therefore, this study used a choice experiment and mixed logit model to identify the consumer preference structure for vehicle self-diagnosis and fault prediction functions and to derive their respective economic value for drivers and non-drivers, finding a preference (in monetary terms) of 4,961 KRW (4.19 USD) per month overall, 3,525 KRW (2.98 USD) for drivers, and 7,372 KRW (6.22 USD) for non-drivers. In addition, it was found that non-drivers preferred other vehicles’ additional functions more than drivers did. The results of the analysis are expected to serve as a reference for decision-making by vehicle manufacturers, the maintenance industry, new smart car users, and governments that introduce smart cars.

Drivers of Driving: A Review

As car ownership and usage expand globally, understanding the factors that influence the propensity to drive is crucial for promoting sustainable transportation. This literature review examined the factors influencing driving decisions through a systematic search of databases, rigorous screening of over 1000 articles, and analysis of 142 studies. The findings reveal that attributes of the built environment (e.g., density, diversity, accessibility), economic factors (e.g., income, costs of car ownership, policies), and psychological aspects (e.g., attitudes, social norms, perceptions) have significant impacts on driving behaviors. By employing an integrative methodology involving targeted searches, keyword analysis, and detailed evaluation, this review offers insights into the multifactorial nature of driving decisions. The synthesis of studies across multiple domains emphasized the need for a holistic approach to understanding and addressing the factors influencing the propensity to drive, laying a foundation for informed transportation policy and practice.

Exploring Electric Car Adoption Intent: Role of Current Travel Characteristics Among Daily Car Users

Exploring Electric Car Adoption Intent: Role of Current Travel Characteristics Among Daily Car Users

Association between local amenities, travel behaviours and urban planning: A spatial analysis of a nationwide UK household panel study.

IntroductionGlobally, there has been a recent resurgence in planning policies focused on local living (such as the 20-min neighbourhood) with proposed benefits of creating sustainable and healthy places. The policies aim to provide improved spatial access to local amenities within short walkable distances of home to encourage walking and cycling and discourage car use, however these pathways have not been examined. This study aimed to quantify the density and diversity of local amenities and their association with daily/weekly travel behaviours. MethodsWe used data from Understanding Society, a national panel survey of UK adults. Spatial data were used to quantify the number and diversity of amenities that have previously been associated with active travel and focused on in 20-min neighbourhood policies within small geographical areas across the UK. These were linked to individual-level data describing daily and weekly travel behaviour for: walking (at least 10-min), cycling, car and bus use. Logistic regression models measured the association between individual amenities, their diversity and daily/weekly travel, whilst controlling for individual factors such as age, sex and employment, residing in a retail centre, as well as area-level urbanicity and deprivation. ResultsOur analysis revealed variations in active travel and car usage patterns by sex, employment status, urbanicity, and area-level deprivation. Local amenities were associated with daily travel behaviours with more amenities generally associated with more frequent walking and less regular bus and car travel. Furthermore, increased amenity diversity was associated with reduced daily car use (OR: 0.77, p < 0.001). Similar patterns were apparent for weekly travel outcomes. ConclusionsBoth access to specific local amenities as well as their diversity are both important neighbourhood factors for achieving shifts from motorised to active transport modes. Policy makers and planners need to ensure the diversity of local amenities are included in local living policies.

Studying the Impact of the COVID-19 Pandemic on Bikeshares as a Mode of Shared Micromobility in Major Cities: A Case Study of Houston

A bikeshare system offers a convenient and cost-effective transportation service, providing shared bicycles for short-term use by individuals. It promotes affordability for users while fostering a healthier environment. By offering an alternative for those without access to private vehicles, it helps mitigate the rise in private car usage. Bike sharing also provides an important first-mile/last-mile commuting option. This study focuses on investigating the effects of the COVID-19 pandemic outbreak on bikeshare ridership, with a specific case study centered around Houston, Texas. The employed methodology involves a descriptive analysis and Negative Binomial regression modeling to uncover the relationship between the dependent variable (ridership) and the independent variables. The descriptive analysis revealed an overall increase in ridership during the COVID-19 period in 2020. Notably, longer duration trips were substantially higher in 2020 compared to 2019. Furthermore, the majority of trips occurred during off-peak hours, followed by evening and morning peak periods. Through regression analysis, this study found that the COVID-19 pandemic had a statistically significant positive impact on average daily ridership, with the number of COVID-19 cases positively influencing ridership levels. Additionally, the weekend indicator had a statistically significant positive impact on the average daily ridership. On the other hand, the temperature indicator did not show any significant impact on the average daily ridership, while precipitation had a statistically significant negative impact, leading to decreased ridership levels. The study highlights the significance of various factors in influencing bikeshare usage, contributing to a better understanding of urban transportation dynamics during such unprecedented times.

Platform for Stop-based Carpooling

This paper introduces a transformative stop-based carpooling app designed to address the limitations of existing solutions. By strategically placing designated stops, such as bus stops, our innovative model restricts ride creation and participation exclusively between these stops, ensuring consistent availability, mitigating privacy concerns, and providing users with alternative transportation options. Through a comprehensive study in a representative urban setting, we examine the impact on car occupancy rates, traffic reduction, and user satisfaction, highlighting the model's ability to cater to diverse user needs. The integration with existing public transport systems extends its eco-friendly footprint, while strategically placed stops enhance coverage in areas with fewer active drivers, overcoming the limitations of conventional carpooling solutions. This paper contributes a blueprint for a sustainable and efficient shared mobility system, showcasing the potential of the stop-based approach in revolutionizing urban transportation.

A national survey on the effect of the COVID-19 pandemic on school travel in the US. – Parents perspective

The Coronavirus Disease 2019 (COVID-19) pandemic has considerably influenced school transportation in the United States (US), with conventional bus use declining and private vehicle use growing. It has increased traffic congestion, reliance on private autos, and detrimental air quality and sustainability effects. This study investigates the shift in transport mode preferences among parents during school reopening in 2021, focusing on elementary, middle, and high schools. An online questionnaire was distributed to parents in the U.S. The findings indicate a significant shift in parental transportation choices, with reduced reliance on school buses and increased automobile usage. Elementary school parents' bus percentage declined from 39.7% to 36.4% in Spring 2021, while middle and high school parents showed similar trends. School closures led to a shift to online learning platforms which affected academic achievement, with 15.9%, 15.5%, and 17.0% of students performing below average. In Spring 2021, 50.5% of students on the school bus encountered a delay of 0 to 15 min, while 32.4% suffered a wait of 15 to 30 min. In Fall 2021, 51.7% saw a 0 to 15-minute delay, while 31.2% suffered a 15-to-30-minute delay. Understanding the COVID-19 pandemic's effects on school travel patterns will allow policymakers and transportation planners to develop post-pandemic solutions prioritizing safety, justice, and environmental sustainability for similar events in the future.