An Adaptive Dynamic Sensing Routing for Driving Environment in Internet of Vehicles

Abstract

The invention provides an adaptive dynamic perception routing for the driving environment of the Internet of Vehicles, which includes a driving behavior perception prediction module for dynamically predicting the vehicle position by using vehicle driving history information; a communication coverage radius prediction module for calculating the effective communication coverage radius; The beacon period environment adaptive adjustment module is used to dynamically adjust the beacon period of the neighbor discovery message frame; the chance weight selection forwarding module is used to calculate the chance weight values ​​of the vehicle nodes in all neighbor position tables and select the one with the largest chance weight value Forwarding and delivery by vehicles; and an environment-adaptive dynamic-aware routing protocol. The present invention can effectively alleviate the problem that in complex traffic environments such as urban blocks and highways, due to dynamic changes in vehicle traffic environments such as vehicle density and driving speed, it is very easy to cause deterioration in the performance of routing data packet packet delivery rate, and significantly improves the routing performance of the vehicle network. , providing low-latency, high-reliability forwarding quality, and improving vehicle network connectivity.

Description

technical field [0001] The invention belongs to the technical field of Internet of Vehicles research, and in particular relates to an adaptive dynamic perception routing for the driving environment of the Internet of Vehicles. Background technique [0002] With the advent of the 5G era and the rapid development of artificial intelligence and the Internet of Things, as an important part of smart cities, the blueprint for future urban intelligent transportation systems is gradually emerging. As a converged network, 5G can enable the acquisition of traffic conditions, low-latency communication, large-scale data storage, and real-time feedback of traffic forecasts, which promotes the development of intelligent collaboration technology between vehicles and vehicles, and vehicles and roads in the Internet of Vehicles. [0003] In order to meet the forwarding quality required for the real-time broadcast of safety messages of the Internet of Vehicles, it is very urgent to solve the ...

AI Technical Summary

Problems solved by technology

[0006] 2. The continuous change of the topology structure in the vehicle communication network brings corresponding changes in the quality of communication coverage, which leads to changes in the radius of communication coverage and affects the quality of communication links

[0007] 3. The usual geographic location-based routing relies significantly on high-precision electronic maps. It needs to continuously update the complex routing neighbor table according to changes in vehicle driving behavior. In complex urban traffic environments, due to the occlusion of elevated buildings, real-time not enough, too much

[0008] 4. In high-speed mobile scenarios, dynamic changes in traffic density lead to unstable network topology and decreased network connectivity

Usually, the peripheral forwarding of the route will increase the number of forwarding times, thereby increasing the end-to-end delay

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