Automated Robotic and Network Connectivity Systems for Self-Driving Vehicle Technology.

• Author: Groener, Martin

1. Introduction

   Artificially intelligent autonomous vehicles will pave the way for breakthrough modes of transport mobility. (Joh, 2019) Using cutting-edge sensors and embedded devices, connected and self-driving cars will offer a riskless travel mode by putting an end to human driving errors, in addition to more reliable and more adequate routes for passengers, constituting an important progress with regard to sustainable development. (Chehri and Mouftah, 2019) In order for self-driving cars to become satisfactorily assimilated, the social interactions encompassing them should be thoroughly regulated. (Stromberg et al., 2018)

2. Conceptual Framework and Literature Review

   Accelerated connectivity integrated into autonomous driving functions present a significant challenge to the massive socioeconomic advantages (Balica, 2018; Grossman, 2018; Kirby et al., 2018; Lazaroiu et al., 2017; Popescu, 2017) provided by connected and autonomous vehicles. (Sheehan et al., 2019) The objects and spaces that constitute automation systems are elaborate and inconclusive. An ostensibly consonant automated object (e.g. the self-driving car) may eventually be much less stable. (Bissell, 2018) The imaginable new insecurities which autonomous vehicle driving behavior may display are designed as decisional boundaries, as artificial driving intelligence will require specific decisional capacities (De Gregorio Hurtado, 2017; Hayes and Jandric, 2017; Kral et al., 2018; Popescu et al., 2017; Popescu et al., 2018), especially in the limitation to interpret and identify the driving setting in relation to human values and moral grasp. (Cunneen et al., 2019)

3. Methodology and Empirical Analysis

   Building my argument by drawing on data collected from Abraham et al. (2017), ANSYS, Atomik Research, Capgemini Research Institute, Charles Koch Institute, CivicScience, eMarketer, Ipsos, McKinsey, Schoettle & Sivak (2014), and Statista, I performed analyses and made estimates regarding most popular activities to pursue with time saved in an autonomous car (%), attitudes toward the safety of self-driving cars (%), and the awareness of autonomous vehicles (%). Structural equation modeling was used to analyze the collected data.

4. Results and Discussion

   As autonomous vehicles can determine new standards of safety undetectable by human drivers, malware clusters may catalyze unconventional patterns of convenience, mobility, and economic and sustainable imbalance throughout urban areas. (Vassallo and Manaugh, 2018) Insofar as autonomous vehicles systems are steadily networked, the massive volume of necessitated and produced data will turn out to be too excessive and intricate for humans to handle, and cutting-edge degrees of automation suitable for processing huge quantities of data instantaneously will be required, but human supervision over such systems will decrease. (Slaughter, 2018)...