Vehicle Users Research Articles

Performance Evaluation of Paid Parking at Cilebut Station

This study intends to find out the capacity of parking needs managed by PT. Kereta Api Indonesia (Persero) with the location of the Cilebut station research, this study used the SRP method of characteristics (Volume, Accumulation, Duration, Turnover, Index), in this study was the management of paid parking performance. Data collection was carried out using the survey method with a time of 12 hours and running for sixteen days, with the aspects taken being data on the hours of entry and exit of the vehicle to find out the characteristics of the parking. The results of this study show that the parking performance cannot accommodate motorcycle vehicles the area with an area of 486m2 has a parking capacity of 120 SRP, while the results of the study getting an index figure of more than 100% indicates too high parking performance and so turn over parking by 181% at peak hours. The result of the SRP needs that must be provided by the management with the results of the study is 159 slots to accommodate motorcycle vehicles, with an SRP value of 159 slots will produce good parking performance, namely parking according to the slots that have been provided so that motorcycle vehicle users feel safe when parking the vehicle.

Lived Experiences of People with and without Disabilities across the Lifespan on Autonomous Shuttles

As an emerging, alternative mode of transportation, an in-depth understanding of autonomous shuttle (AS) experiences among all age groups, with and without disabilities, may impact acceptance and adoption of the AS, shape industry guidelines, and impact public policy. Therefore, this study analyzed qualitative data from older (n = 104), younger, and middle-aged (n = 106) adults and people with disabilities (n = 42). The data were obtained by asking participants four open-ended questions from an Autonomous Vehicle User Perception Survey. The result revealed seven themes (Safety, Ease of Use, Cost, Availability, Aging, AS Information, and Experience with AS) for older, younger, and middle-aged adults and six themes (all of the previously mentioned except for Aging) for people with disabilities. Frequency counts indicated priority attention, among all groups, to Safety and Ease of Use. This study provides valuable information pertaining to the experiences, concerns, and motivations of all potential users across age groups and disabilities—and may inform policymakers and industry partners to address their needs more adequately. These findings may contribute to improving and enhancing AS programming, design, and deployment in a safer, accessible, affordable, and tailored way.

Impact of battery electric vehicle usage on air quality in three Chinese first-tier cities.

China, the world leader in automobile production and sales, confronts the challenge of transportation emissions, which account for roughly 10% of its total carbon emissions. This study, utilizing real-world vehicle data from three major Chinese cities, assesses the impact of Battery Electric Vehicles (BEVs) on air quality. Our analysis reveals that BEVs, when replacing gasoline vehicles in their operational phase, significantly reduce emissions, with reductions ranging from 8.72 to 85.71kg of CO2 per vehicle monthly. The average monthly reduction rate is 9.47%, though this effect is less pronounced during winter. Advanced BEVs, characterized by higher efficiency and newer technology, exhibit greater emission reduction benefits. While private BEVs generally contribute positively to environmental outcomes, taxi BEVs, due to their intensive usage patterns, show less environmental advantage and may sometimes worsen air quality. Looking ahead, we project substantial emission reductions from the replacement of gasoline vehicles with electric alternatives over the next decade. Policymakers are urged to adopt proactive measures, focusing on promoting medium to large electric vehicles and fostering the use of private and ride-hailing electric vehicles.

Temporal assessment of emission inventory model for Indian heavy commercial vehicle segment – A top-down approach

Heavy commercial vehicles (HCVs) are pivotal to India's economy but are also significant sources of air pollution. To address this issue, the Indian government implemented Bharat Stage VI (BS-VI) emission standards in 2020. Research gap regarding realistic inputs for annual vehicle kilometres and survival rate of heavy commercial vehicles has been identified. The HCV sector is categorized into long-haul vehicles (32 tonnes and above, with higher annual vehicle usage and survival rates) and pick-up and delivery HCV trucks (16–32 tonnes, with relatively lower annual vehicle usage and survival rates). Based on the primary research by taking into account the inputs from various stakeholders regarding annual vehicle kilometres and survival rates subject to vehicle type and emission standards, an HCV emission inventory for India has been developed for regulated pollutants (NOx, PM2.5, and CO) till 2035. We assume no additional external technological or policy interventions, except the anticipated shift to Bharat Stage VII (BS-VII) standards by 2027. Key findings reveal that the on-road HCV population is projected to marginally increase (6.5%) by 2035 compared to 2020. However, there is a notable 97% surge in goods transport tonnage by 2035, indicating more efficient commercial vehicle usage, especially in the heavier category (32 tonnes and above). Crucially, annual emissions of NOx, PM2.5, and CO from the HCV segment are expected to peak in 2020 and decline significantly by 2035. Emissions are projected to decrease by 91.5% (NOx), 96.6% (PM2.5), and 97.6% (CO) compared to 2020 levels due to the introduction of BS-VI standards in 2020 and the anticipated adoption of BS-VII standards in 2027. This study is instrumental in defining base emission inventory till 2035 for any further policy evaluation for heavy commercial vehicle segment for reducing air pollution and enhancing environmental sustainability.

Coordinated Cyber Security Enhancement for Grid-Transportation Systems With Social Engagement

Effective coordination of energy and transportation systems is fundamental and vital to smart city management. Yet, the deeply intertwined information and communication technologies have exposed smart city management to malicious cyberattacks vastly. This study develops a two-stage mitigation strategy for integrated transportation-energy systems (TESs) by coordinating energy and transportation systems to safeguard against false data injection attacks (FDIAs). Our strategy targets social engagements by electric vehicle (EV) users who can be incentivized to alter their regular EV usage patterns for supporting the energy system via vehicle-to-grid actions. We consider a TES that contains a multi-energy system comprised of power and gas systems as well as an urban transportation system. Integrated system operators can take emergency measures to coordinate important system assets (e.g., traditional generators, renewable generators, EV fleets) in a sensible and intelligent way, and thereby mitigate the consequences of FDIAs. Specifically, we take a two-stage distributionally robust approach to cope with uncertain FDIAs, with which a moment-based ambiguity set is employed to yield the worst-case uncertainty distribution. We leverage constraint generation-based relaxation to solve the problem iteratively. To demonstrate our strategy's value and practical utilities, we use a coupled urban TES to conduct case studies. According to the evaluation results, the optimized EV scheduling and energy dispatch scheme produced by the proposed strategy can contain cyberattacks’ impacts and enhance cyber resilience in smart city management more effectively.

Optimizing wireless charging infrastructure placement using genetic algorithms

Electric vehicles (EVs) play a crucial role in tackling environmental issues in the transportation industry. The incorporation of effective charging infrastructure is crucial in promoting the broad acceptance of electric vehicles (EVs). This work investigates the optimization of the location of wireless charging infrastructure in urban contexts using genetic algorithms (GAs). The location data, which includes latitude and longitude coordinates, showed a wide range of spatial distributions that are ideal for deploying charging stations. These distributions display variances that are favorable for strategically placing the infrastructure. The examination of power consumption data revealed significant variations in energy demand across different sites, ranging from 180 kWh to 300 kWh. These differences indicate that each location has its own distinct energy needs. The population density statistics exhibited a spectrum of values, ranging from 600 individuals per square unit. The population density is 1200 persons per square kilometer. The abbreviation "km" refers to kilometers, which is used to indicate different levels of prospective electric vehicle (EV) users. In addition, the distance data provided information about the lengths between prospective locations for charging stations, which varied from 400 km to 1200 km. These distances had an impact on the concerns of connection and transmission efficiency. The research highlights the intricate nature of the elements that affect the ideal location of infrastructure, underlining the need for a methodical approach to optimization. Integrating these statistics provides a foundation for developing an objective function in the GA framework to optimize the location of charging infrastructure. The study's results provide valuable understanding of the many factors that influence the location of charging infrastructure. The goal is to promote the development of efficient and easily accessible electric vehicle charging networks in metropolitan areas.

Shifting Gears: Insights into Electric Vehicle Adoption and User Satisfaction in Southern Kerala, India

This study examines how consumers in Kerala, India, think about EV adoption and satisfaction levels with conventional automobile ownership. The research indicates a significant preference for electric vehicles (EVs) among youthful, educated men, especially in the two-wheeler market controlled by companies such as Ather and Ola, based on a thorough examination of demographic characteristics and vehicle preferences. Due mostly to reduced operating costs and government incentives, long-time drivers of conventional vehicles are switching to electric vehicles (EVs). In comparison to economic issues, environmental concerns are less influential in shaping decisions, despite their importance. Particularly in terms of financial gains and operational efficiency, the results point to increased levels of satisfaction among EV users. In addition to outlining opportunities and challenges in fostering widespread EV adoption, this report highlights Kerala’s changing sustainable transportation scenario.

Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniques

This article outlines the architecture of autonomous driving and related complementary frameworks from the perspective of human comfort. The technical elements for measuring Autonomous Vehicle (AV) user comfort and psychoanalysis are listed here. At the same time, this article introduces the technology related to the structure of automatic driving and the reaction time of automatic driving. We also discuss the technical details related to the automatic driving comfort system, the response time of the AV driver, the comfort level of the AV, motion sickness, and related optimization technologies. The function of the sensor is affected by various factors. Since the sensor of automatic driving mainly senses the environment around a vehicle, including “the weather" which introduces the challenges and limitations of second-hand sensors in autonomous vehicles under different weather conditions. The comfort and safety of autonomous driving are also factors that affect the development of autonomous driving technologies. This article further analyzes the impact of autonomous driving on the user’s physical and psychological states and how the comfort factors of autonomous vehicles affect the automotive market. Also, part of our focus is on the benefits and shortcomings of autonomous driving. The goal is to present an exhaustive overview of the most relevant technical matters to help researchers and application developers comprehend the different comfort factors and systems of autonomous driving. Finally, we provide detailed automated driving comfort use cases to illustrate the comfort-related issues of autonomous driving. Then, we provide implications and insights for the future of autonomous driving.

Solar wireless electric vehicle charging system

vehicles (EVs) are increasingly prevalent on roads today. These vehicles have demonstrated their effectiveness to minimize travel costs through transitioning from traditional fuel sources to electricity, that is notably more cost-efficient, alongside the associated environmental benefits. The primary aim is to implement a charging system that accommodates extended vehicle usage by applying higher charging rates for prolonged periods. Presently, the prevailing charging infrastructure for EVs involves conductive methods where the vehicle connects to a charging station; however, this process typically takes longer. Advancements in technology are introducing wireless charging solutions. Inductive EV charging, a wireless alternative, eliminates the need for physical wires. This innovative approach proposes charging electric vehicles while they are in motion, eliminating the necessity for vehicles to stop for refueling. Notably, this charging mechanism operates on solar energy, obviating the requirement for an exterior source of power. The system-design encompasses the utilization of various components such as batteries, transformers, solar panels, copper coils, regulator circuits, ATmega328p controllers, AC to DC converters, and the LCD.

Assessing the Long-Term Impact of COVID-19 on Travel Behavior: The United Arab Emirates Perspective

The unprecedented COVID-19 pandemic has caused significant short-term travel disruptions and profound changes in daily travel routines. Yet, the long-term impact on travel behavior and mobility remains unclear. The present study examines the enduring effects of COVID-19 on travel patterns in the United Arab Emirates (UAE) through a comprehensive survey assessing long-term impacts and participants' travel behavior changes during different stages of the pandemic. The survey covered travel modes, frequency, duration, and distance, unveiling a pandemic-driven shift towards increased personal vehicle usage due to public transportation concerns. Nevertheless, as the pandemic gradually recedes, individuals are slowly reverting to their pre-pandemic travel habits. Moreover, the results indicate that travel patterns vary depending on the distance traveled. Short-distance travel has largely returned to pre-pandemic levels, while medium-distance travel continues to lag. Intriguingly, post-pandemic levels of long-distance travel have exceeded the pre-pandemic figures, indicating a potential alteration in travel behaviors. These observed changes were substantiated by a paired t-test, demonstrating a significant difference across nearly all periods examined. In summary, this research sheds light on the long-term consequences of COVID-19 on travel behavior and mobility in the UAE. The survey data uncovers a noteworthy transformation in travel patterns during the pandemic, with subsequent gradual reversion to pre-pandemic norms. Notably, the findings suggest potential shifts in travel preferences across different distances, with long-distance travel surpassing pre-pandemic levels. These insights contribute to a deeper understanding of the lasting impacts of COVID-19 on transportation and travel choices.

Hành vi chuyển đổi sử dụng phương tiện vận chuyển xanh của giao hàng chặng cuối trong thương mại điện tử: Tiếp cận từ giá trị tiêu dùng

The study aims to explain switching behavior toward green vehicle usage of last-mile delivery in e-commerce in Vietnam. A research framework is proposed based on perceived values of green vehicles and environmental concerns. The study collects data from 343 shippers who have used fossil fuel-powered vehicles from 04/2023 to 06/2023, and structural equation modeling is applied to examine proposed hypotheses. Results demonstrate that emotional, functional, and social values positively influence environmental concerns and attitude. Epistemic value motivates environmental concerns, whereas this antecedent does not affect attitude. Additionally, environmental concerns and attitude are essential catalysts for fostering switching intention toward green vehicle usage of last-mile delivery. Finally, academic and managerial implications are discussed to assist manufacturers and logistic providers to adopt communication campaigns in order to trigger switching behavior in Vietnam

Prediction of Electric Vehicle Mileage According to Optimal Energy Consumption Criterion

In the field of electric vehicle usage, an inherent challenge lies in the restricted mileage capacity prior to requiring a recharge, hindering broader acceptance of electric vehicles. To alleviate this concern, enhancing the comprehension of vehicle energy consumption and range plays a pivotal role in easing the anxieties of electric vehicle drivers. Within this context, a novel model-based predictive approach is introduced for estimating electric vehicle energy consumption. This method considers the vehicle's specific parameters, the road network's topology, and actual traffic conditions. Through the macro model of electric vehicle energy consumption, real-time summary data can be extracted using conventional map-based web services. By representing the road network as a weighted directed graph tailored to the energy consumption model, an algorithm aids in mileage optimization by determining the optimal path for immediate use. The resultant motion range from this approach offers improved precision and dependability in contrast to conventional strategies based on average consumption and distance.

Review on li-ion battery model used in electrical vehicle

In recent years, battery models have become increasingly crucial, particularly with the surge in electric vehicle usage within the transportation sector. Accurate models are essential for assessing battery performance and devising effective battery management systems. Various modeling approaches exist in literature, each carrying its own set of advantages and drawbacks. Typically, more intricate models offer precise results but demand greater computational resources and entail time-consuming, costly laboratory tests for parameter determination. Hence, for first stage assessments and battery managing system designs, models employing simpler parameter documentation procedures are the most viable and suitable options. The presence of a precise battery model within a simulation platform holds immense significance in crafting efficient battery-powered systems. Absolutely! The lithium-ion battery model is a standout option owing to its potential as an energy storage system, particularly for renewable technology applications. This is largely due to its remarkable power compactness and energy storage capabilities.

Evaluation of an Autonomous Vehicle User Interface for Sensory Impaired Users

Evaluation of an Autonomous Vehicle User Interface for Sensory Impaired Users

Assessing performance and satisfaction of micro-mobility in smart cities for sustainable clean energy transportation using novel APPRESAL method

South Korea signed the Global Methane Pledge to reduce methane emissions by 30% by 2030, updated its Nationally Determined Contribution (NDC) to target a 40% reduction in GHGs (Green House Gas) from 2018 levels by 2030. In addition, South Korea submitted its Long-Term Strategy (LTS) to achieve carbon neutrality by 2050. Nowadays, to mitigate the GHG emission every country explicitly planning to reduce non-renewable energy resource vehicles. The electric vehicle (EV) markets growing rapidly with various technologies, strategies and innovations to support decarbonization. In 2022, by the transportation CO2 (Carbon dioxide) emission report of International Energy Agency (IEA), the cars and vans contributes 48% in the over all CO2 emissions. Increasing the electric micro-mobility service would be one of the best effective approach in accordance to reduce CO2 emission. This research study support to reduce the GHG emission by increasing the clean energy vehicle. A case study conducted to analyze firm-wise e-scooter sharing service performance and its satisfaction in smart cities of South Korea. Lacking in the consistent good quality and performance affects the number of electric vehicle users. Hence, electric vehicle firm should focus into their product better performance and quality. This research supports to analyze the e-scooter based on the various criteria from the user’s perspective. This research study helps to firms to identify their lacking criteria and improve their quality and performance. We considered the performance, accessibility, tangibility, reliability and responsiveness factors which affects user’s perspective in e-scooter sharing services. A survey was conducted over sixty user’s for different e-scooter services with twenty four factors. Generally, MCDM (Multi-Criteria Decision-Making) techniques holds two phases to determine the weight of the criteria and another phase to ranking the alternatives. The existing MCDM techniques lacks to handle the user’ satisfaction index analysis and not considering the influence grade of each factors in the analysis. To overcome this draw back and analyze the micro-mobility services based over the user’s point of view, we introduced a novel fuzzy based MCDM method name as Approach for Preference, Performance and Ranking Evaluation with SAtisfaction Level (APPRESAL) approach. The findings show that Lime, a micro-mobility firm, outperformed other firms with high-quality service and user satisfaction, followed by Wind, XingXing, Alpaca, and Beam. The influences of defected factors from the accessibility, reliability, responsiveness, and assurance dimensions had an adverse effect on quality of firm’s micro-mobility service with unsatisfactory performance.

A Scientometric Analysis of electric vehicle-based text mining

The United Nations Climate Change Conference (COP 21) held in Paris on December 12, 2015, agreed on the Paris Agreement, which aims to address climate change and its negative impacts as part of the challenge of Global Warming. The transportation sector contributed 23% of CO2 emissions of a global contributor in 2018. Electric vehicles themselves have benefited from an environmental and economic perspective. The development of electric vehicles in Indonesia has increased the number of electric vehicle users as well as research related to customer awareness, opinions, preferences, and satisfaction, identification of markets and potential for technology and innovation, predictions, new policies, literature reviews and topics, keywords and fields related to electric vehicle. From the results of this study, it is expected to be able to find out customer characteristics, customer concerns, market penetration, model social impact data, predict market growth and technology developments, and formulate policies and regulations according to the needs of stakeholders Therefore, a systematic review is needed regarding the publication of electric vehicles based on text mining, then analyzes scientometric analysis Bibliographic database files from 2011 – 2023.

Toward Sustainable Cities: Where the Electric Vehicle Users Reside Matters

Toward Sustainable Cities: Where the Electric Vehicle Users Reside Matters

Optimal Scheduling of Regional Integrated Energy System Considering the Integration of Electric Vehicles and the Life Cycle Assessment Method

With the increasing scale of renewable energy and electric vehicles (EVs), the optimization scheduling of the regional integrated energy system (RIES) is facing new challenges due to the integration of EVs and new energy into the system. To realize the low-carbon economic operation of the RIES, a bi-level optimization scheduling strategy for low-carbon economic operation of the RIES is proposed, which considers EVs' participation and lifecycle carbon emissions, and integrates the electricity market and carbon trading market. Firstly, there are many factors affecting the carbon emissions of EVs and the difficulties in prediction. From the indirect carbon emissions during the use of EVs, the relationship between the carbon emissions of EVs and the charging mode and carbon emission sources is comprehensively analyzed. A carbon emission model of EVs based on the Life Cycle Assessment (LCA) is established in this paper. Secondly, the charging model of EVs based on demand response is combined with the electricity market; The carbon emission model of EVs based on the LCA is combined with the carbon trading market, and a bi-level scheduling strategy based on the flexible interaction between carbon and electricity is proposed. Then the strategy is solved to minimize system economic costs and carbon transaction costs. Finally, simulation example analysis is conducted to demonstrate that the proposed strategy can effectively reduce the total charging costs of electric vehicle users, improve the utilization rate of renewable energy, and reduce carbon dioxide emissions, with good economic and environmental benefits.

Electromobility: Safety or a Threat to Poland’s Transport?

The trend following the purchase of electric-powered vehicles is currently the biggest challenge of the Polish automotive industry. Increasing restrictions and looming deadlines for selling electric-only cars contribute to their increasing purchase numbers. It is known that electric vehicles require a stable charging infrastructure. From 2020 to 2022, infrastructure development is significant in Poland, but is it sufficient? Is this the main drawback of owning an electric vehicle? More and more users are charging their cars locally at their places of residence, but not everyone has this option. This raises the question of whether it is safe to own an electric vehicle. Is it possible to cover the route from point A to point B without much trouble? Awareness of the need to stop longer to charge an electric vehicle is not a problem among the Polish public; a bigger and more significant issue is the number of publicly available charging points. Therefore, these topics will be analyzed more extensively in this article; the possibilities of alternative charging and energy harvesting methods will be presented, as the growing interest in electric-powered vehicles and the indicated questions regarding the development of charging infrastructure and safety for electric vehicle users will be answered.

Alleviating range anxiety with ‘Enroute’: A real-time mobile solution and infrastructure innovation for electric vehicle users

Amidst the growing adoption of electric vehicles (EVs), this study addresses the prominent issue of "range anxiety" encountered by EV users when confronted with critical charging situations during their journeys. The research background emphasises the constraints of the existing charging infrastructure, primarily designed for urban areas, leaving EV drivers susceptible to unforeseen charging emergencies in remote or less-travelled regions. To tackle this challenge, an innovative mobile application that provides a real-time solution by harnessing crowd-sourced data and forging partnerships with charging infrastructure providers was developed. This app assists users in locating available charging stations. It offers the option to book a service that can bring the necessary charging equipment to a specified location (similar to a porter service), ensuring timely assistance. The research methodology involved user surveys and data analysis, specifically emphasising seamless integration with EVs’ onboard systems, making support practical and readily accessible. The results demonstrate the effectiveness of this app in alleviating range anxiety and enhancing EV users’ confidence in long-distance travel. In conclusion, this paper outlines a promising solution to a pressing issue in electric mobility. It underscores the importance of addressing the charging infrastructure gap for the widespread adoption of EVs. The future scope of this research involves further refinement of the app, expanded partnerships with charging networks and Porter service providers, and continued collaboration with EV manufacturers to ensure seamless integration and user satisfaction, ultimately advancing the cause of sustainable transportation.