High-Performance Computing for Distributed Route Computation in Traffic Flow Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10259562" target="_blank" >RIV/61989100:27740/25:10259562 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1877050925006246?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050925006246?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.procs.2025.02.263" target="_blank" >10.1016/j.procs.2025.02.263</a>
Alternative languages
Result language
angličtina
Original language name
High-Performance Computing for Distributed Route Computation in Traffic Flow Models
Original language description
In the dynamic landscape of smart cities and traffic management, it is necessary to further explore the synergistic potential of realtime traffic data and high-performance computing to optimise traffic flow through dynamic re-routing strategies. High-performance computing plays an essential role in achieving effective traffic flow optimisation. Our research builds upon existing studies highlighting the positive correlation between the integration of live traffic updates and route optimisation. The methodology involves simulations with our Ruth traffic simulator, where vehicles dynamically adjust routes based on up to date traffic information available to them at different levels. Scalability tests are conducted with varying numbers of CPUs and nodes to assess the simulator's capacity to scale. The results showcase the impact of live traffic data on both driving time and average speed, emphasising the adaptability of our approach for broader applications. In conclusion, our work not only advances the understanding of real-time traffic optimisation but also underscores the critical role of high-performance computing in achieving scalable solutions. The findings present practical implications for the implementation of dynamic re-routing strategies in transportation systems, paving the way for future research and real-world applications on smart cities.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
—
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Procedia Computer Science. Volume 255
ISBN
—
ISSN
1877-0509
e-ISSN
1877-0509
Number of pages
10
Pages from-to
83-92
Publisher name
Elsevier
Place of publication
Amsterdam
Event location
Amsterdam
Event date
Oct 22, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—