مقاله انگلیسی رایگان در مورد اعتماد به خودرو های بدون سرنشین – الزویر ۲۰۱۸

elsevier

 

مشخصات مقاله
ترجمه عنوان مقاله اعتماد به خودرو های بدون سرنشین: بررسی عوامل کلیدی تاثیرگذار در پذیرش خودرو های بدون سرنشین
عنوان انگلیسی مقاله Trust in driverless cars: Investigating key factors influencing the adoption of driverless cars
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۱۰ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه الزویر
نوع نگارش مقاله مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس میباشد
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی برق، مهندسی کامپیوتر، مهندسی مکانیک
گرایش های مرتبط هوش ماشین و رباتیک، هوش مصنوعی، مکاترونیک
مجله مجله مدیریت مهندسی و فناوری – Journal of Engineering and Technology Management
دانشگاه College of Science and Engineering – Flinders University – Australia
کلمات کلیدی اتومبیل های بدون راننده، تحقیق و توسعه، پذیرش فناوری، اعتماد به فن آوری، توسعه محصول جدید
کلمات کلیدی انگلیسی Driverless cars, R&D, Technology adoption, Trust in technology, New product development
شناسه دیجیتال – doi
https://doi.org/10.1016/j.jengtecman.2018.04.006
کد محصول E9218
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Introduction

The World Health Organization has indicated that 1.2 million people die in accidents each year (WHO, 2015). Driverless cars have been deemed an important technology in reducing a portion of those deaths due to human error (Kyriakidis et al., 2015). A driverless car, otherwise termed a self-driving car or an autonomous car, broadly refers to a robotic vehicle that works without a human operator (Benenson et al., 2008; Paden et al., 2016). More specifically, it can be defined as ‘those in which at least some aspects of a safety-critical control function (e.g. steering, throttle or braking) occur without direct driver input’ (NHTSA, 2013, p. 7). There are various levels of automation of driverless cars and various classification systems exist (the widely adopted SAE standard, the National Highway Traffic Safety Administration (NHTSA) standard and the German Federal Highway Research Institute (BASt) standard). These systems generally encompass five levels of automation from no automation to various levels of partial automation to fully automated (Kyriakidis et al., 2015). Since the Internet and smart phone revolutions, driverless cars have now been deemed as one of the key disruptors in the next technology revolution along with drones and the internet of things and have been recognized as a key area for future research (NHTSA, 2013). Google’s self-driving car has become a hot topic in the media and governments around the world have begun to develop strategies to address the challenges that may result from self-driving vehicles (Schoettle and Sivak, 2014). While driverless cars promise to provide many benefits, a key barrier to its adoption is the public trust in driverless cars (Bansal et al., 2016; Kyriakidis et al., 2015). As automobiles are becoming unsustainable, there has been many consequences such as the emission of carbon, high traffic and accidents (Paden et al., 2016). To control these, driverless cars have been proposed as a suitable alterative. Although this may potentially provide safety and efficiency benefits, there are major concerns around the public’s willingness to adopt the technology. These concerns relate to security, trust, privacy, reliability and liability (Fagnant and Kockelman, 2015). Additionally, there are certain situations in which users may be more willing to adopt driverless cars, compared to others. Further research in understanding the scenarios when users are most willing to adopt driverless cars will assist in early implementation programs among adopting target groups and settings. Consequently, this study will attempt to answer the following research question: ‘What are the key factors influencing trust in driverless cars’? It will investigate perceptions of benefits, concerns, trust and importantly, situations when users are more willing to adopt driverless cars. It is widely accepted that driverless cars will not become mainstream on the majority of roads globally in the immediate future (Benenson et al., 2008; Godoy et al., 2015). The most likely adoption settings may be in closed environments such as university campuses, airports, golf courses, holiday parks and retirement villages (Miralles-Guasch and Domene, 2010). However, the majority of existing studies have collected data in broad brushed random approaches internationally or nationally rather than focus on closed environments. For instance, a study by Kyriakidis et al. (2015) obtained 5,000 broad responses from 109 countries with only 40 countries having at least 25 responses. Similarly, a study by Schoettle and Sivak (2014) collected 1533 responses from the US, UK and Australia. However, as the mass consumer market would not be the first ones to adopt the technology, research is needed that is more nuanced in terms of the groups and situations when people will most likely adopt the technology. For instance, prior studies did not indicate who may be willing to use driverless vehicles for public transportation. In fact, prior research makes little mention of public transport, although government transport departments and those providing transport services in certain closed precincts will be interested in attitudes towards driverless cars (Lam et al., 2016).

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