AI-assisted data dissemination methods for supporting intelligent transportation systems†

被引:10
|
作者
Sun, Peng [1 ]
Boukerche, Azzedine [1 ]
机构
[1] Univ Ottawa, Sch Elect Engn & Comp Sci, Paradise Res Lab, 800 King Edward Ave, Ottawa, ON K1N 6N, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
artificial intelligence; data dissemination; data pre-caching; intelligent transportation system; prediction;
D O I
10.1002/itl2.169
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
As an essential component of Smart Cities, the intelligent transportation system (ITS) utilizes a large number of deployed traffic monitoring equipment and Internet-of-Vehicles technologies to timely transfer traffic management measures formulated based on accurately grasped real-time traffic conditions to all transportation system participants for improving the operating efficiency and safety of the transportation system. The key to achieving this advantage is effective data transmission. Correspondingly, by exploiting these recorded massive traffic data, a variety of AI-assisted data transmission methods are designed to improve the data transmission performance in the vehicular network environment (VNE) to ensure the effective operation of ITS. To help readers get an initial understanding of how AI technology can help with data transmission in VNE, in this letter, we will discuss two types of AI-assisting methods targeting the data dissemination performance enhancement in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications respectively in detail, that is, predictive handover/pre-caching algorithm and predicted traffic flow-assisted data routing protocols. Additionally, empirical evaluation is conducted to demonstrate the effectiveness of the discussed methods.
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页数:5
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