Multi-Sensor Fusion Technology, Spatial Simulation and Environment Mapping Algorithms, and Real-World Connected Vehicle Data in Smart Sustainable Urban Mobility Systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F02819180%3A_____%2F22%3A%230000134" target="_blank" >RIV/02819180:_____/22:#0000134 - isvavai.cz</a>
Result on the web
<a href="https://addletonacademicpublishers.com/contents-crlsj/2511-volume-14-1-2022/4280-multi-sensor-fusion-technology-spatial-simulation-and-environment-mapping-algorithms-and-real-world-connected-vehicle-data-in-smart-sustainable-urban-mobility-systems" target="_blank" >https://addletonacademicpublishers.com/contents-crlsj/2511-volume-14-1-2022/4280-multi-sensor-fusion-technology-spatial-simulation-and-environment-mapping-algorithms-and-real-world-connected-vehicle-data-in-smart-sustainable-urban-mobility-systems</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.22381/CRLSJ14120227" target="_blank" >10.22381/CRLSJ14120227</a>
Alternative languages
Result language
angličtina
Original language name
Multi-Sensor Fusion Technology, Spatial Simulation and Environment Mapping Algorithms, and Real-World Connected Vehicle Data in Smart Sustainable Urban Mobility Systems
Original language description
The aim of this systematic review is to synthesize and analyze multi-sensor fusion technology, spatial simulation and environment mapping algorithms, and real-world connected vehicle data in smart sustainable urban mobility systems. With increasing evidence of autonomous vehicle planning algorithms, object localization and mapping tools, and spatial computing technology, there is an essential demand for comprehending whether road anomaly detection tools, blockchain and data fusion technologies, and trajectory estimation algorithms assist smart traffic planning and analytics. In this research, prior findings were cumulated indicating that automated collision avoidance systems, data monitoring algorithms, and virtual navigation tools reduce crash severities. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2022, with search terms including “smart sustainable urban mobility systems” + “multi-sensor fusion technology,” “spatial simulation and environment mapping algorithms,” and “real-world connected vehicle data.” As we analyzed research published between 2019 and 2022, only 88 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 13, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.
Czech name
—
Czech description
—
Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
—
OECD FORD branch
21100 - Other engineering and technologies
Result continuities
Project
—
Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Contemporary Readings in Law and Social Justice
ISSN
1948-9137
e-ISSN
—
Volume of the periodical
14
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
105-120
UT code for WoS article
—
EID of the result in the Scopus database
2-s2.0-85142222498