scholarly journals Individual Predictors of Autonomous Vehicle Public Acceptance and Intention to Use: A Systematic Review of the Literature

2020 ◽  
Vol 6 (4) ◽  
pp. 106 ◽  
Author(s):  
Fahimeh Golbabaei ◽  
Tan Yigitcanlar ◽  
Alexander Paz ◽  
Jonathan Bunker
Keyword(s):  
Systematic Review ◽  
Autonomous Vehicles ◽  
Public Attitudes ◽  
Autonomous Vehicle ◽  
Influential Factors ◽  
Public Acceptance ◽  
Adoption Process ◽  
Intention To Use ◽  
People’S Attitudes ◽  
The Individual

Fully autonomous vehicles (AV) would potentially be one of the most disruptive technologies of our time. The extent of the prospective benefits of AVs is strongly linked to how widely they will be accepted and adopted. Monitoring and tracking of individuals’ reactions and intentions to use AVs are critical. The current study aims to explore and classify individual predictors (i.e., influential factors or determinants) of public acceptance of, and intention to use AVs, by conducting a systematic literature review and developing a conceptual framework to map out the individual influential factors that shape public attitudes towards AVs, which influence user acceptance and adoption preferences. This framework contains the key factors identified in the systematic review—i.e., demographic, psychological, and mobility behavior characteristics. The findings of the review disclose that public perceptions and adoption intentions vary significantly among different socio-demographic cohorts. Commuters value different aspects concerning AVs, which shape their intentions on acceptance and adoption. Thus, direct experience with AVs along with education and communication would be helpful to change people’s attitudes towards AVs in a positive way. The study informs urban and transport policymakers, managers, and planners, and helps in planning for a healthy AV adoption process with minimal societal disruption.

scholarly journals The Impact of Social Influence, Technophobia, and Perceived Safety on Autonomous Vehicle Technology Adoption

2019 ◽  
Vol 48 (2) ◽  
pp. 133-142
Author(s):  
Sahil Koul ◽  
Ali Eydgahi
Keyword(s):  
Technology Adoption ◽  
Social Influence ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Negative Relationship ◽  
Future Research ◽  
Intention To Use ◽  
Perceived Safety ◽  
Vehicle Technology ◽  
The Impact

The objective of this study was to determine whether there was a relationship between social influence, technophobia, perceived safety of autonomous vehicle technology, number of automobile-related accidents and the intention to use autonomous vehicles. The methodology was a descriptive, cross-sectional, correlational study. Theory of Planned Behavior provided the underlying theoretical framework. An online survey was the primary method of data collection. Pearson’s correlation and multiple linear regression were used for data analysis. This study found that both social influence and perceived safety of autonomous vehicle technology had significant, positive relationships with the intention to use autonomous vehicles. Additionally, a significant negative relationship was found among technophobia and intention to use autonomous vehicles. However, no relationship was found between the number of automobile-related accidents and intention to use autonomous vehicles. This study presents several original and significant findings as a contribution to the literature on autonomous vehicle technology adoption and proposes new dimensions of future research within this emerging field.

Integration of GPS and Accelerometer Uncertainties to Improve the Estimation of the Pose of Autonomous Vehicles

2010 ◽  
Author(s):  
Wilson O. Achicanoy M. ◽  
Carlos F. Rodriguez H.
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Sampling Rate ◽  
System A ◽  
Accelerometer Signal ◽  
Gps Measurement ◽  
Global Positioning ◽  
The Individual ◽  
Uncertainty Models

Uncertainty fusion techniques based on Kalman filtering are commonly used to provide a better estimation of the state of a system. A comparison between three different methods to combine the sensor information in order to improve the estimation of the pose of an autonomous vehicle is presented. Two sensors and their uncertainty models are used to measure the observables states of a process: a Global Positioning System (GPS) and an accelerometer. Given that GPS has low sampling rate and the uncertainty of the position, calculated by double integration from the accelerometer signal, increases with time, first a resetting of the estimator based on accelerometer by the GPS measurement is done. Next, a second method makes the fusion of both sensor uncertainties to calculate the estimation. Finally, a double estimation is done, one for each sensor, and a estimated state is calculated joining the individual estimations. These methods are explained by a case study of a guided bomb.

scholarly journals Public attitudes towards algorithmic personalization and use of personal data online: Evidence from Germany, Great Britain, and the US

2020 ◽  
Author(s):  
Anastasia Kozyreva ◽  
Philipp Lorenz-Spreen ◽  
Ralph Hertwig ◽  
Stephan Lewandowsky ◽  
Stefan Michael Herzog
Keyword(s):  
Great Britain ◽  
Data Privacy ◽  
Large Scale ◽  
Personal Information ◽  
Public Attitudes ◽  
Personal Data ◽  
The United States ◽  
Individual Level ◽  
People’S Attitudes ◽  
The Individual

Despite their ubiquity online, personalization algorithms and the associated large-scale collection of personal data have largely escaped public scrutiny. Yet policy makers who wish to introduce regulations that respect people's attitudes towards privacy and algorithmic personalization on the Internet would greatly benefit from knowing how people perceive different aspects of personalization and data collection. To contribute to an empirical foundation for this knowledge, we surveyed public attitudes using representative online samples in Germany, Great Britain, and the United States on key aspects of algorithmic personalization and on people's data privacy concerns and behavior. Our findings show that people object to the collection and use of sensitive personal information and to the personalization of political campaigning and, in Germany and Great Britain, to the personalization of news sources. Encouragingly, attitudes are independent of political preferences: People across the political spectrum share the same concerns about their data privacy and the effects of personalization on news and politics. We also found that people are more accepting of personalized services than of the collection of personal data and information currently collected for these services. This acceptability gap---the difference between the acceptability of personalized online services and the acceptability of the collection and use of data and information---in people's attitudes can be observed at both the aggregate and the individual level. Our findings suggest a need for transparent algorithmic personalization that respects people’s data privacy, can be easily adjusted, and does not extend to political advertising.

scholarly journals Hybrid Multi-Sensor Integration for Static or Dynamic Obstacle Detection, Tracking and Classification for Autonomous Vehicle

2021 ◽  
Vol 23 (06) ◽  
pp. 1288-1293
Author(s):  
Dr. S. Rajkumar ◽  
◽  
Aklilu Teklemariam ◽  
Addisalem Mekonnen ◽  
◽  
...  
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Autonomous Vehicles ◽  
Detection System ◽  
Autonomous Vehicle ◽  
Obstacle Detection ◽  
Multiple Sensors ◽  
Environment Perception ◽  
Hybrid Sensors ◽  
The Individual

Autonomous Vehicles (AV) reduces human intervention by perceiving the vehicle’s location with respect to the environment. In this regard, utilization of multiple sensors corresponding to various features of environment perception yields not only detection but also enables tracking and classification of the object leading to high security and reliability. Therefore, we propose to deploy hybrid multi-sensors such as Radar, LiDAR, and camera sensors. However, the data acquired with these hybrid sensors overlaps with the wide viewing angles of the individual sensors, and hence convolutional neural network and Kalman Filter (KF) based data fusion framework was implemented with a goal to facilitate a robust object detection system to avoid collisions inroads. The complete system tested over 1000 road scenarios for real-time environment perception showed that our hardware and software configurations outperformed numerous other conventional systems. Hence, this system could potentially find its application in object detection, tracking, and classification in a real-time environment.

scholarly journals Maneuver-Based Objectification of User Comfort Affecting Aspects of Driving Style of Autonomous Vehicle Concepts

2020 ◽  
Vol 10 (11) ◽  
pp. 3946 ◽  
Author(s):  
Ferdinand Schockenhoff ◽  
Hannes Nehse ◽  
Markus Lienkamp
Keyword(s):  
Pilot Study ◽  
Travel Time ◽  
Autonomous Vehicles ◽  
User Study ◽  
Autonomous Vehicle ◽  
User Needs ◽  
Vehicle Concept ◽  
Driving Style ◽  
The Individual ◽  
User Comfort

Driving maneuvers try to objectify user needs regarding the driving dynamics for a vehicle concept. As autonomous vehicles will not be driven by people, the driving style that merges the individual aspects of driving dynamics, like user comfort, will be part of the vehicle concept itself. New driving maneuvers are, therefore, necessary to objectify the driving style of autonomous vehicle concepts with all its interdependencies relating to the individual aspects. This paper presents a methodology to design such driving maneuvers and includes a pilot study and a user study. As an example, the methodology was applied to the parameters of user comfort and travel time. The driven maneuvers resulted in statistical equations to objectify the interdependencies of these two aspects. Finally, this paper provides an outlook for needed maneuvers in order to tackle the entire driving style with its multidimensional facets.

A new hesitant fuzzy KEMIRA approach: An application to adoption of autonomous vehicles

2021 ◽  
pp. 1-12
Author(s):  
Sezi Çevik Onar ◽  
Cengiz Kahraman ◽  
Başar Öztayşi
Keyword(s):  
Autonomous Vehicles ◽  
Selection Process ◽  
New Technology ◽  
Autonomous Vehicle ◽  
Decision Makers ◽  
Evaluation Methodology ◽  
Adoption Process ◽  
Human Judgment ◽  
Linguistic Term ◽  
Fuzzy Linguistic

Autonomous vehicles are one of the emergent advances of the new technology era that has the prospective to redesign transportation structures. Understanding and measuring the limitations of adopting autonomous vehicles and selecting the best autonomous vehicle based on different aspects is crucial for enhancing the adoption process. Defining the criteria and the appropriate evaluation methodology is very important for selecting the best autonomous vehicles. However, this selection process is a human judgment-based process where both benefit and cost criteria with imprecise linguistic assessments should be considered. The KEmeny Median Indicator Ranks Accordance (KEMIRA) method is a method that enables ranking the benefit and cost criteria independently. In this paper, a new KEMIRA method based on hesitant fuzzy linguistic term sets is defined. Hesitant Fuzzy Linguistic Term Sets (HFLTS) are newly utilized to represent the hesitancy of the decision-makers. The proposed new KEMIRA is approach the first study that defines the alternative scores and weights of the criteria via HFLTS. The computational steps of the new model are applied to autonomous vehicle selection. A real application is employed to show the applicability of the new KEMIRA method.

The importance and significance of gene polymorphisms in preeclampsia

2016 ◽  
pp. 45-49
Author(s):  
P.N. Veropotvelyan ◽  
◽  
I.S. Tsehmistrenko ◽  
N.P. Veropotvelyan ◽  
N.S. Rusak ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Systematic Review ◽  
Early Diagnosis ◽  
Gene Polymorphisms ◽  
Individual Risk ◽  
Extended Study ◽  
Stress Genes ◽  
Detoxification System ◽  
The Individual ◽  
The Relationship

Was to conduct a systematic review of data on the relationship between polymorphisms genes of detoxification system and development of preeclampsia (РЕ). Рresents the main genes of detoxification system (GSTPI, GSTМI, GSTТI, GРХI, ЕРНХI, SOD-2, SOD-3, CYPIAL, MTHЕR, MTR) and their functions. Of interest is the possibility of calculating the individual risk of PE based on the results about the presence of a combination of different polymorphisms in the genotype of the female. Question about early diagnosis of РЕ remains controversial and not fully understood. It is necessary to conduct further in-depth, extended study of this problem. Key words: preeclampsia, oxidative stress, genes of the detoxification system.

Anti-Inflammatory Properties of Plant Derived Natural Products – A Systematic Review

2019 ◽  
Vol 26 (24) ◽  
pp. 4506-4536 ◽  
Author(s):  
Iris E. Allijn ◽  
René P. Brinkhuis ◽  
Gert Storm ◽  
Raymond M. Schiffelers
Keyword(s):  
Systematic Review ◽  
Natural Products ◽  
Positive Control ◽  
Therapeutic Effects ◽  
Reference Compound ◽  
Individual Molecular Species ◽  
The Past ◽  
Anti Inflammatory ◽  
The Individual ◽  
Natural Medicines

Traditionally, natural medicines have been administered as plant extracts, which are composed of a mixture of molecules. The individual molecular species in this mixture may or may not contribute to the overall medicinal effects and some may even oppose the beneficial activity of others. To better control therapeutic effects, studies that characterized specific molecules and describe their individual activity that have been performed over the past decades. These studies appear to underline that natural products are particularly effective as antioxidants and anti-inflammatory agents. In this systematic review we aimed to identify potent anti-inflammatory natural products and relate their efficacy to their chemical structure and physicochemical properties. To identify these compounds, we performed a comprehensive literature search to find those studies, in which a dose-response description and a positive control reference compound was used to benchmark the observed activity. Of the analyzed papers, 7% of initially selected studies met these requirements and were subjected to further analysis. This analysis revealed that most selected natural products indeed appeared to possess anti-inflammatory activities, in particular anti-oxidative properties. In addition, 14% of the natural products outperformed the remaining natural products in all tested assays and are attractive candidates as new anti-inflammatory agents.

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