Factors Influencing the Intention to Use Private Autonomous Vehicles in Indonesia's Big Cities DOI Open Access

Endang Nuriayani,

Donny Ekaputra,

Feny Fitria Afiani

et al.

Fokus Bisnis Media Pengkajian Manajemen dan Akuntansi, Journal Year: 2023, Volume and Issue: 23(1), P. 141 - 156

Published: July 3, 2023

This research explored the factors influencing intention to use Private Autonomous Vehicles (PAVs) in Indonesia's big cities. The Technology Acceptance Model (TAM) was employed as theoretical framework due its model explaining adoption of new technologies. study utilized a quantitative approach, employing Google Form questionnaire collect data from 315 respondents Jakarta, Bogor, Depok, Tangerang, and Bekasi. were analyzed using PLS-SEM analysis. While previous studies focused on AV Indonesia, particularly shared AVs public transportation, overlooked aspect familiarity concerning private adoption, this addressed these gaps. study's novelty lies including facilitating conditions variables. found that safety, familiarity, significantly impacted perceived usefulness ease AVs, while personal benefit social influence did not. In conclusion, adapting marketing strategies diverse user preferences, emphasizing safety promotional materials, strengthening educational efforts, seeking government support for road improvements, enhancing are essential fostering positive attitudes intentions toward autonomous vehicle technology.

Language: Английский

Driving forward together: The common intention of Indonesians in different residential areas to use autonomous vehicles DOI Creative Commons
Ari Widyanti,

Redifa Erlangga,

Auditya Purwandini Sutarto

et al.

Transportation Research Interdisciplinary Perspectives, Journal Year: 2024, Volume and Issue: 24, P. 101049 - 101049

Published: March 1, 2024

Despite the significant benefits of Autonomous Vehicles (AVs) for global transportation, Indonesia's diverse geographical landscape encounter unique adoption challenges due to infrastructural shortcomings and economic limitations. This study explores AVs in Indonesia, considering its potential market crucial role AV Electric Vehicle supply chains. Drawing upon Technology Acceptance Model (TAM) Unified Theory Use (UTAUT), we assessed acceptance across Metropolitan Cities, frontier regions ("3T"), New National Capital City (IKN) areas. Using a cross-sectional design, distributed an online questionnaire, focusing on demographics, perceived safety, transport mode changes, behavioral intention towards AVs, based TAM UTAUT factors. From 1,255 valid responses, found influences gender (t (1253) = 4.22), safety perceptions (F (2,1252) 52.373), frequency (4, 1250) 6.662) intentions. Both models were moderately effective explaining willingness use (R2 34% 48%, respectively). highlighted usefulness (β 0.421) ease 0.540), while emphasized effort expectancy 0.317) social influence 0.240). However, findings from multigroup analysis did not corroborate residential areas determining AVs. These offer insights developing promotion strategies, creating user-friendly designs, formulating supportive policies Indonesian regions.

Language: Английский

Citations

6
Encouraging Residents to Save Energy by Using Smart Transportation: Incorporating the Propensity to Save Energy into the UTAUT Model DOI Creative Commons
Bożena Gajdzik, Marcin Awdziej, Magdalena Jaciow

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(21), P. 5341 - 5341

Published: Oct. 27, 2024

The rapid urbanization and technological advancements of the recent decades have increased need for efficient sustainable transportation solutions. This study examines acceptance smart systems (STSs) among residents in Polish cities explores impact these on energy-saving behaviors. Using extended Unified Theory Acceptance Use Technology (UTAUT2) model, which includes propensity to save energy, this research seeks understand determinants STS adoption. primary was conducted using Computer-Assisted Web Interviewing (CAWI). sample controlled gender place residence. A 471 individuals meeting criteria living a city with over 200,000 solutions Poland were selected from panel. SmartPLS 4 software used analyze collected data. findings reveal that energy significantly influences perceived usefulness, ease use, social influence, hedonic motivation toward STSs. Perceived usefulness use found be strong predictors intention STSs, while costs had negative it. also identified moderating role personal innovativeness mitigating cost concerns. These insights underscore importance emphasizing conservation benefits user-friendly features promoting concludes aligning innovations user motivations can enhance adoption solutions, contributing smarter more urban environments.

Language: Английский

Citations

5
Negative impacts of artificial intelligence technologies on the tourism industry DOI
Anda Zvaigzne, Lienīte Litavniece, Sergejs Kodors

et al.

Worldwide Hospitality and Tourism Themes, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 2, 2025

Purpose The present research study aims to conduct a thematic literature review of the negative impacts artificial intelligence (AI) on tourism industry. Design/methodology/approach is based comprehensive prior by various authors AI and its consequences in Findings Research indicates that integrating technologies industry leads consequences. While enhances operational efficiency personalizes customer experiences, it also presents significant challenges, for example, replaces labor interaction between tourist service provider decreases. New risks are emerging areas need be managed ensure they do not have impacts. Originality/value paper provides industry, highlighting balanced approach integrates human elements with technological advancements. It offers valuable insights into potential drawbacks AI, urging stakeholders consider these challenges when implementing AI-driven solutions tourism.

Language: Английский

Citations

0
Latest breakthroughs, research results, and challenges in intelligent control of autonomous vehicles DOI
Tadele Bishaw Achenef, Solomon Nigusu Abera,

Yibeltal Antehunegn Admas

et al.

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: May 2, 2025

Major companies like Google, Tesla, and Uber have invested heavily in autonomous technology, testing them countries the US, China, Germany. Autonomous vehicle (AV) technology has advanced significantly, with deep learning algorithms, high-definition mapping systems, vehicle-to-everything (V2X) communication. Sensor lidar, radar, cameras also been developed for safe navigation. Recent advancements intelligent control improved performance capabilities, artificial intelligence (AI) machine (ML) playing a crucial role developing systems. Researchers are algorithms navigation, sensor fusion techniques, predictive modeling, planning to enhance lane changes, intersection handling. Safety AV requires rigorous testing, cybersecurity, redundancy, failsafe mechanisms. This review synthesizes wide range of methodologies, such as statistical analysis, simulation-based approaches, models, reinforcement genetic that used throughout many studies on Vehicles (AVs). These techniques greatly AVs, especially terms maximizing mixed traffic flow, strengthening integration, honing decision-making challenging situations. Research findings show significant advancements; instance, improves pedestrian recognition difficult situations, while models emphasize benefits vehicles efficiency. The optimization routing management demonstrated by successful combination learning. Despite these developments, number challenges still need be overcome, including requirement flexible scalable infrastructure well policy frameworks, susceptibilities inclement weather, security privacy concerns. necessity more reliable fixes vulnerabilities incorporation AVs into current transportation too prominent research needs. Numerous stress how important it is sophisticated governance frameworks place handle moral, legal, issues related use AVs. identifies predominantly focuses improving communication technologies, AI-enabled decision-making, integration. Future directions should explore interactions urban infrastructure, develop equitable adaptations, implement safety measures absence connectivity. Overall, this provides comprehensive insights state, challenges, future potential guiding researchers policymakers addressing critical gaps accelerate global development adoption

Language: Английский

Citations

0
Enhanced Decision-Making for Urban Climate Change Transportation Policies using q-Rung Orthopair Fuzzy Rough Fairly Information Aggregation DOI
Hafiz Muhammad Athar Farid, Muhammad Riaz, Patrick Siarry

et al.

Information Sciences, Journal Year: 2025, Volume and Issue: unknown, P. 121900 - 121900

Published: Jan. 1, 2025

Language: Английский

Citations

0
Exploring AAM Acceptance in Tourism: Environmental Consciousness’s Influence on Hedonic Motivation and Intention to Use DOI Open Access
Yining Suo, Chenglong Li, Li Tang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(8), P. 3324 - 3324

Published: April 16, 2024

Tourist destinations thrive on sustainable development. Electric vertical take-off and landing (eVTOL) aircraft, representing energy-efficient advancements in aviation that are pivotal to advanced air mobility (AAM), have garnered attention. Yet, the discourse eVTOLs’ role tourism remains scant. This study, drawing from 450 samples Mogan Mountain Scenic Area, introduces AAM-tourism acceptance model (ATAM). It integrates theory of planned behavior (TPB) technology (TAM) theoretical frameworks, incorporating environmental consciousness, perceived safety, hedonic motivation, personal innovativeness, assessing their influence tourists’ eVTOL usage intention through a structural equation (SEM). The results reveal consciousness significantly impacts motivation usefulness, driving adoption. Furthermore, innovativeness influences behavioral control. Therefore, align deeply with attributes, both positively influencing use. Thus, study validates eVTOL’s viability its potential for sectoral expansion. Moreover, it offers insights into how psychological factors shape adoption, guiding promotion sightseeing services informing research AAM across various domains.

Language: Английский

Citations

2
The Emerging Role of Artificial Intelligence in Enhancing Energy Efficiency and Reducing GHG Emissions in Transport Systems DOI Creative Commons
Tymoteusz Miller, Irmina Durlik, Ewelina Kostecka

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(24), P. 6271 - 6271

Published: Dec. 12, 2024

The global transport sector, a significant contributor to energy consumption and greenhouse gas (GHG) emissions, requires innovative solutions meet sustainability goals. Artificial intelligence (AI) has emerged as transformative technology, offering opportunities enhance efficiency reduce GHG emissions in systems. This study provides comprehensive review of AI’s role optimizing vehicle management, traffic flow, alternative fuel technologies, such hydrogen cells biofuels. It explores potential drive advancements electric autonomous vehicles, shared mobility, smart transportation economic analysis demonstrates the viability AI-enhanced transport, considering Total Cost Ownership (TCO) cost-benefit outcomes. However, challenges data quality, computational demands, system integration, ethical concerns must be addressed fully harness potential. also highlights policy implications AI adoption, underscoring need for supportive regulatory frameworks policies that promote innovation while ensuring safety fairness.

Language: Английский

Citations

2
Psychological factors shaping public acceptance of the adoption of autonomous vehicles in Indonesia DOI Open Access
Charli Sitinjak, Vladimir Šimić, Dragan Pamučar

et al.

Journal of Transport & Health, Journal Year: 2023, Volume and Issue: 34, P. 101726 - 101726

Published: Nov. 30, 2023

Language: Английский

Citations

6
Systematic Selective Limits Application Using Decision-Making Engines to Enhance Safety in Highly Automated Vehicles DOI
Divya Garikapati,

Yiting Liu,

Zhaoyuan Huo

et al.

SAE International Journal of Connected and Automated Vehicles, Journal Year: 2024, Volume and Issue: 8(1)

Published: Aug. 1, 2024

<div>The traditional approach to applying safety limits in electromechanical systems across various industries, including automated vehicles, robotics, and aerospace, involves hard-coding control into production firmware, which remains fixed throughout the product life cycle. However, with evolving needs of such as vehicles robots, this falls short addressing all use cases scenarios ensure safe operation. Particularly for data-driven machine learning applications that continuously evolve, there is a need more flexible adaptable application strategy based on different operational design domains (ODDs) scenarios. The ITSC conference paper [<span>1</span>] introduced dynamic (DCLA) strategy, supporting diverse profiles scenario parameters layers Autonomy software stack. This article extends DCLA by outlining methodology ODD elements, identification, classification using decision-making (DM) engines. It also utilizes layered architecture cloud infrastructure vehicle-to-infrastructure (V2I) technology store mapping ground truth or backup mechanism DM engine. Additionally, focuses providing subset driving case studies correspond forms baseline derive create four classes limits. Finally, real-world examples “driving-in-rain” variations have been considered apply engines classify them previously identified classes. example can be further compared future work potential offers scalable solution up Level 5 within industry.</div>

Language: Английский

Citations

1
Systematic Selective Limits Application Using Decision Making Engines to Enhance Safety in Highly Automated Vehicles DOI Open Access
Divya Garikapati, Yiting Liu,

Zhaoyuan Huo

et al.

Published: Jan. 29, 2024

Safety limits application has always been a traditional approach to ensure the safe operation of electro-mechanical systems within many industries including automated vehicles, robotics, aerospace, automotive, railways, manufacturing, etc. In all these applications, control and safety are usually hard-coded into production firmware fixed throughout entire product life cycle. Currently, due evolving needs like vehicles robots, this does not address use cases scenarios operation. Especially for data-driven machine learning applications that constantly evolve learn over time, it is important be able adjust strategy more flexible adaptable based on different Operational Design Domains (ODDs) scenarios. Our ITSC conference paper ~\cite{4} introduced concept new called Dynamic Control Limits Application (DCLA) supports diverse profiles parameters involved dynamic scenario at layers Autonomy software stack.This extends DCLA derive complete methodology ODD elements, identification classification using Decision Making Engines. It leverages layered architecture in implement (DM) algorithms. Another extension cloud infrastructure Vehicle-to-Infrastructure (V2I) technology store mapping serve as ground truth and/or backup mechanism case errors or failures associated with main Engine. There also focus providing comprehensive list custom built experimental dataset cover maximum multiple tables chosen from, which eventually helps creating profiles. These distinct perceived by system upon algorithms applied trained. This systematic can used industry any future until Level 5 Autonomy.

Language: Английский

Citations

1