Edge-Powered Assisted Driving For Connected Cars

نویسندگان

چکیده

Assisted driving for connected cars is one of the main applications that 5G-and-beyond networks shall support. In this work, we propose an assisted system leveraging synergy between vehicles and edge network infrastructure, in order to envision global traffic policies can effectively drive local decisions. Local decisions concern individual vehicles, e.g., which vehicle should perform a lane-change manoeuvre when; decisions, instead, involve whole flows. Such are made at different time scales by entities, integrated within edge-based architecture share information. particular, leverage queuing-based model formulate optimization problem make on To cope with complexity, then develop iterative, linear-time complexity algorithm called Bottleneck Hunting (BH). We show performance our solution using realistic simulation framework, integrating Python engine ns-3 SUMO, considering two relevant services, namely, lane change assistance navigation, real-world scenario. Results demonstrate leads reduction vehicles’ travel times 66 percent case 20 compared traditional, local-coordination approaches.

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ژورنال

عنوان ژورنال: IEEE Transactions on Mobile Computing

سال: 2023

ISSN: ['2161-9875', '1536-1233', '1558-0660']

DOI: https://doi.org/10.1109/tmc.2021.3084291