Road detection method, system, device and storage medium based on collaborative vehicles

Abstract

The present application relates to a road detection method, system, device and storage medium based on collaborative vehicles. The method uses a monitoring platform to generate a road detection request in a set road section to a road detection task, and the road detection task is assigned to a set road detection task through a base station. Different smart cars in the road section; according to the road detection task, the road environment data of the set road section is collected, and the collected road environment data is preprocessed by the smart car; according to the vehicle communication cloud computing system, all smart cars are constrained Select a smart car as the aggregation vehicle, and aggregate the road environment data through the aggregation vehicle; the aggregation vehicle uploads the aggregated road environment data to the monitoring platform through the base station, and completes the set road section detection. Therefore, which of the present application realizes the prevention of abnormal conditions on the road, avoids the occurrence of accidents, and is conducive to the realization of fully automatic driving of smart cars.

Description

technical field [0001] The present application relates to the field of automatic driving, in particular to a road detection method, system, device and storage medium based on cooperative vehicles. Background technique [0002] With the rapid development of self-driving technology, smart cars are already on the road, which is believed to provide a safer driving environment. Smart cars are usually equipped with communication, computing and storage resources, and equipped with various sensors to achieve fully autonomous driving. Smart cars can use on-board sensors and computing resources to perceive the road environment and make driving decisions. Although edge computing brings lower latency for requesting services, it still cannot meet the needs of fully autonomous driving. In order to support fully autonomous driving, the distribution of base stations and edge servers should cover all regions to provide computing services for vehicles, which is expensive and impractical. I...

AI Technical Summary

Problems solved by technology

Although edge computing brings lower latency to request services, it still cannot meet the needs of fully autonomous driving

In order to support fully autonomous driving, the distribution of base stations and edge servers should cover all areas to provide computing services for vehicles, which is expensive and impractical

Besides, driving safety is the most important issue in traffic, and any mistake can lead to fatal accident

In this case, executing tasks for smart cars on edge servers is not always stable due to many communication reasons

[0003] In addition, because smart cars generally interact with base stations, but the coverage of existing base stations is limited, how to improve the information interaction between vehicles and base stations is also an accompanying problem that needs to be solved

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