Regulating Autonomous Vehicles in a Smart Urban Transport System: Safety, Security, and Privacy Issues.

• Author: Ljungholm, Doina Popescu
• Position: Report

1. Introduction

   To ensure a comfortable assimilation of self-driving cars to road traffic, trust must be considered carefully. (Korber et al., 2018) As vehicles become more self-governing, their capacity for moral accountability will increase. (Bigman et al., 2019) Perceived risk does not directly shape individuals' attitudes as regards self-driving cars but influences it indirectly by affecting their level of trust. (Zhang et al., 2019) Heterogeneous elaborate subsystems incorporated into autonomous vehicle technology carrying out instantaneous tasks may result in failures. (Gohar and Lee, 2020) Decreasing traffic jam, energy utilization and emissions, while expanding access require a prevailing business pattern in which connected and autonomous vehicles are mainly shared, and not privately owned. (Cohena and Hopkins, 2019)

2. Conceptual Framework and Literature Review

   Self-driving cars may revolutionize the transportation industry only via broad acceptance and adoption. (Dixon et al., 2020) As their operations become more incomprehensible, autonomous vehicles will be seen as possessing more free will, and more moral responsibility will be ascribed to them. (Bigman et al., 2019) Pedestrians may display escalated stress and cautious crossing behavior when the autonomous vehicle driver does not eye gaze and completes a non-driving task or infer that a self-driving car would yield without fail. (Palmeiro et al., 2018) Shared autonomous vehicles may cut down greenhouse gas emissions by steering more coherently, circumventing traffic jams, intensifying implementation of alternative fuel cars, and charging according to renewable electricity generation, while bringing about more vehicle miles operated by decreasing the time expense of cruising and enabling non-drivers to ride more by car. (Jones and Leibowicz, 2019)

3. Methodology and Empirical Analysis

   Using and replicating data from CARiD, CBS Interactive, Deloitte, GHSA, Kennedys, MRCagney, TechRepublic, and ZDNet, I performed analyses and made estimates regarding safety, security, and privacy issues. The results of a study based on data collected from 4,600 respondents provide support for my research model. Using the structural equation modeling, I gathered and analyzed data through a self-administrated questionnaire.

4. Results and Discussion

   Data-driven connected and autonomous vehicles may refashion mobilities, making movement of people thoroughly accessible. (Wigley and Rose, 2020) Values of travel time decreases will result from subjective well-being enhancements (Andrei et al., 2016; Cera et al., 2019; Kliestik et al., 2020; Lazaroiu et al., 2018; Lazaroiu et al., 2020a, b; Nica, 2015; Popescu et al., 2017) via diminished stresses of driving or the capacity to unwind and mentally transition. (Singleton, 2019) Broad acceptance and adoption of autonomous vehicle technology necessitates cost competitiveness with conventional cars. (Nunes and Hernandez, 2020) Ridesharing may curb both required autonomous vehicle fleet proportion and vehicle driven miles. (Chen et al., 2019) Advancement of trust is a fluid process (Andrei et al., 2020; Englund, 2019; Krizanova et al., 2019; Lazaroiu et al., 2019; Nica et al., 2014; Popescu, 2014; Popescu et al., 2019) and should be adjusted to the adequate degrees of comfortable implementation to ensure convenient harnessing of autonomous vehicle technologies. (Khastgir et al., 2018) (Tables 1-8)

5. Conclusions and Implications

   Autonomous vehicle perception can be permeated by the categorization of surrounding objects and by networking directly with them, to clarify identities and access data particular to the connected technologies and...