The Moral Decision-Making Capacity of Autonomous Mobility Technologies: Route Planning Algorithms, Simulation Modeling Tools, and Intelligent Traffic Monitoring Systems
The Moral Decision-Making Capacity of Autonomous Mobility Technologies: Route Planning Algorithms, Simulation Modeling Tools, and Intelligent Traffic Monitoring Systems

Summary/Abstract: The purpose of this study is to examine road environment data, tracking control and spatial cognition algorithms, and virtual navigation and simulation modeling tools. In this article, I cumulate previous research findings indicating that urban transportation systems leverage autonomous vehicle decision-making algorithms, deep learning-based sensing technologies, and interactive data visualization tools. I contribute to the literature on vehicle and pedestrian detection tools, image processing and motion planning algorithms and deep learning and edge intelligence technologies by showing that autonomous vehicle routing and navigation develop on sensor data fusion algorithms, urban computing technologies, and data modeling tools. Throughout June 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “moral decision-making” + “autonomous mobility technologies” + “route planning algorithms,” “simulation modeling tools,” and “intelligent traffic monitoring systems.” As I inspected research published in 2022, only 174 articles satisfied the eligibility criteria. By removing controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 37, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, MMAT, and SRDR.

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