Edge Intelligence Multi-Source Data Processing for Autonomous Driving in Internet of Vehicles

doi:10.13190/j.jbupt.2020-266

Journal of Beijing University of Posts and Telecommunications ›› 2021, Vol. 44 ›› Issue (2): 102-108.doi: 10.13190/j.jbupt.2020-266

• The Special Issue on Internet of Vehicles • Previous Articles Next Articles

Edge Intelligence Multi-Source Data Processing for Autonomous Driving in Internet of Vehicles

Lü Xin-chen, ZHANG Chen-yu

National Engineering Laboratory for Mobile Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2020-12-13 Online:2021-04-28 Published:2021-04-28

Abstract

Abstract: Designing a highly reliable automatic driving system is challenging due to the limited perception range and computing resources of intelligent vehicles. To this end, the distributed data and available resources in the network should be exploited. An edge intelligence multi-source data processing scheme for autonomous driving in Internet of vehicles is proposed. Firstly, a three-layer network model is constructed to schedule the data transmission. Then the original vehicle nodes are mapped one by one into a set of virtual nodes to decouple the data transmission. Thereafter, the original problem into a minimum cost maximum flow problem, realizing the efficient allocation of computing, communication resources in the network are transformed. Simulations show that the proposed scheme can improve system throughput by 150% and system energy efficiency by 12% compared with local processing scheme.

Key words: edge intelligence, Internet of vehicles, multi-source data processing, network flow model

CLC Number:

TP399

Lü Xin-chen, ZHANG Chen-yu. Edge Intelligence Multi-Source Data Processing for Autonomous Driving in Internet of Vehicles[J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(2): 102-108.

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Edge Intelligence Multi-Source Data Processing for Autonomous Driving in Internet of Vehicles

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