Autonomous Vehicle Interaction Control Software, Urban Sensing and Computing Technologies, and Trajectory Planning and Route Detection Algorithms in Networked Transport Systems
Autonomous Vehicle Interaction Control Software, Urban Sensing and Computing Technologies, and Trajectory Planning and Route Detection Algorithms in Networked Transport Systems

Summary/Abstract: This paper provides a systematic literature review of studies investigating autonomous vehicle interaction control software, urban sensing and computing technologies, and trajectory planning and route detection algorithms in networked transport systems. The analysis highlights that intelligent transportation infrastructures develop on mobility simulation and geospatial data visualization tools and blockchain and extended reality technologies. Throughout April 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “networked transport systems” + “autonomous vehicle interaction control software,” “urban sensing and computing technologies,” and “trajectory planning and route detection algorithms.” As I inspected research published between 2021 and 2022, only 93 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstan- tiated by replication, too imprecise material, or having similar titles, I decided upon 13, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

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