Open AccessAn MEC Architecture-Oriented Improved RRT Algorithm for Regional Trajectory Planning
Author(s) -
Qingwen Han,
Ziyun Huang,
Lingqiu Zeng,
Yunqu Wu,
Lei Ye,
Hui Zu,
Yu Lei
Publication year - 2021
Publication title -
mobile information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.346
H-Index - 34
eISSN - 1875-905X
pISSN - 1574-017X
DOI - 10.1155/2021/6689293
Subject(s) - computer science , trajectory , hazard , feature (linguistics) , vehicular ad hoc network , tree (set theory) , function (biology) , process (computing) , enhanced data rates for gsm evolution , algorithm , distributed computing , real time computing , wireless ad hoc network , artificial intelligence , telecommunications , mathematical analysis , linguistics , chemistry , physics , philosophy , mathematics , organic chemistry , astronomy , evolutionary biology , wireless , biology , operating system
Multi-access Edge Computing (MEC), which could provide real-time computing ability, is considered as an effective approach to improve performance of Vehicular Ad Hoc Network (VANET). MEC could process regional vehicles information and generate real-time road hazard features, which could be used to realize trajectory planning progress of vehicles. In this paper, an MECoriented VANET infrastructure is presented, and a road hazard feature-based trajectory planning method is proposed. Back Propagation (BP) neural network is employed to predict road hazard feature changing, while a hazard-based cost function is defined. ,en, an improved Rapidly Exploring Random Tree (RRT) algorithm is proposed for novel regional trajectory planning. A joint simulation is done based on SUMO and NS3 platforms. Simulation results verify the effectiveness and stability of the proposed algorithm.
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