The Algorithmic Governance of Connected Autonomous Vehicles: Data-driven Decision Support Systems and Smart Sustainable Urban Mobility Behaviors.

• Author: Davidson, Robert
• Position: Report

1. Introduction

   Connected and autonomous vehicle technologies will considerably lead to enhanced mobility and safety. (Fakhrmoosavi et al., 2020) Irrespective of technological breakthroughs, trust is still a main issue associated with acceptance and adoption of self-driving cars. (Ha et al., 2020) The only manner to supply adequate protection to a manufacturer striving to carry out ethical options as regards autonomous vehicle behavior is by specific legislation or regulation. (Wu, 2020) For self-driving cars, road testing constitutes substantiation for developing public trust in safety and reliability. (Zhao et al., 2020)

2. Conceptual Framework and Literature Review

   Self-driving cars constitute a promising way out to further traffic safety. (Wang et al., 2020) The pertinent moral norms for autonomous vehicles encompass whether self-driving cars should protect the rider or the pedestrian if damage is unpreventable. (Gill, 2020) As the amount of self-driving cars increases, the steadiness of traffic flow consistently improves, reducing snarl-up. (An et al., 2020) Cutting-edge technologies have altered the transportation system, especially concerning safety and mobility. (Das et al., 2020) The influx of self-driving cars to consumer markets will accelerate the shift to car-sharing and facilitate co-owning/leasing a vehicle. (Takalloo et al., 2020) Drivers having behavioral intention to harness autonomous vehicles essentially are dissimilar among users having significant/irrelevant personal information in relation to technology innovativeness. (Keszey, 2020) Self-driving cars can definitely enhance traffic capacity, performance, reliability, and safety (Andrei et al., 2016; Bacalu, 2019; Kovacova et al., 2019; Meyer and Meyer, 2019; Popescu Ljungholm, 2019) of current mobility systems. (Lu et al., 2020) Having an errorless algorithm for instantaneous assessment (Atwell et al., 2019; Kliestik et al., 2020; Peters et al., 2020) of road roughness is pivotal for self-driving cars in an attempt to attain safe driving and user comfort. (Jiang et al., 2020a)

3. Methodology and Empirical Analysis

   I inspected, used, and replicated survey data from AAA, ANSYS, Atomik Research, AUVSI, BCG, Brookings, Capgemini, CivicScience, GenPop, Ipsos, Perkins Coie, Statista, and World Economic Forum, performing analyses and making estimates regarding data-driven decision support systems and smart sustainable urban mobility behaviors. Structural equation modeling was used to analyze the data and test the proposed conceptual model.

4. Results and Discussion

   Self-driving cars may alter established moral norms and encourage an amplified personal concern among users. (Gill, 2020) Individual-level behavioral intention to harness autonomous vehicles networks with required societal-level corollaries. (Keszey, 2020) An extensive variety of self-driving car applications use to good advantage integration of data from sources of heterogeneous processes to cut down the misgivings or constraints transmitted when any of such starting points are deployed separately. (Castorena et al., 2020) A heightened grasp of user acceptance and adoption is paramount to further autonomous vehicle usage. (Yuen et al., 2020) (Tables 1-14)

   Big data-related digital technologies are instrumental in the advancement and harnessing of inspecting and modeling tools in the intricate urban realm of smart transportation and mobility. (Jiang et al., 2020b) Autonomous vehicles may have to make decisions that can cause injury to the car passengers or to other road users. (Gill, 2020) Full automation level self-driving cars may tackle various traffic circumstances without human input, consequently cutting down the amount of crashes generated by fallible inaccuracies. (Das et al., 2020) Temporal disparities in public perceptions as regards likely safety upsides and security-related issues from the subsequent adoption of autonomous vehicles may assist regulatory and governance bodies and self-driving car manufacturers in adjusting their approaches and implementation procedures. (Ahmed et al., 2020) Autonomous vehicles may enhance highway capacity particularly as regards high penetration. (Lu et al., 2020)

   By harnessing portable sensors having high accuracy and integrated communication technologies on diverse self-driving cars that typically...