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 unsubstantiated 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.

Keywords: autonomous vehicle; sensing; trajectory planning; route detection

How to cite: Popescu Ljungholm, D. (2022). “Autonomous Vehicle Interaction Control Software, Urban Sensing and Computing Technologies, and Trajectory Planning and Route Detection Algorithms in Networked Transport Systems,” Contemporary Readings in Law and Social Justice 14(1): 57–72. doi: 10.22381/CRLSJ14120224.

Received 11 April 2022 • Received in revised form 25 July 2022
Accepted 28 July 2022 • Available online 30 July 2022

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