High-precision map crowdsourcing system based on optimal time-stop rule and data collection method of system

Abstract

The invention discloses a high-precision map crowdsourcing system based on an optimal time-stop rule and a data collection method of the system. The system comprises a task issuing module, a member optimization module and an optimal time stop module. The task issuing module is used for issuing a high-precision map crowdsourcing task; the member optimization module is used for selecting superior participants from the candidate participant set, receiving data of the superior participants and providing rewards for the superior participants; and the optimal time stop module controls the stop opportunity of the crowdsourcing task of the high-precision map to maximize the crowdsourcing utility. Based on the system, the invention provides the data collection method of the high-precision map crowdsourcing system based on the optimal time-stop rule. According to the method, sufficient data sources are provided for updating of the high-precision map, the cost of data collection is reduced, and updating of the high-precision map is more real-time and efficient.

Description

technical field [0001] The invention relates to the technical field of urban intelligent transportation, in particular to a high-precision map crowdsourcing system based on optimal time-stop rules and a data collection method thereof. Background technique [0002] Nowadays, unmanned driving is developing rapidly. Perception, as an important module in unmanned driving, is the prerequisite for unmanned vehicles to drive safely on the road. Sensors such as cameras and lidar are the mainstream means for unmanned vehicles to perceive the surrounding environment. However, there are huge challenges in terms of cost to perceive the surrounding environment through sensors. As an emerging perception method, high-precision maps make up for the high cost of sensors. Therefore, how to obtain and update high-precision maps conveniently and quickly is the main task at present. In order to collect high-precision map data, map vendors and driverless car vendors, such as Baidu, Gaode, TomTo...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and propose a high-precision map crowdsourcing system and its data collection method based on the optimal stop-and-go rule. The collection solves the problem of not being able to efficiently obtain road surface environmental data and update high-precision maps in real time due to the shortage of professional collection vehicles, and it reduces the cost of collecting road surface environmental data and improves high-precision The efficiency of map generation expands the update range of high-precision maps

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