# Construction and application of artificial intelligence crowdsourcing map based on multi-track GPS data

arXiv: https://arxiv.org/abs/2402.15796 · HTML: https://mlsanity.com/paper/2402.15796/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 16 references that are in the map.
- First posted on arXiv 24 Feb 2024.

## Builds on (most cited first, 3 of 3)

- [Zero-Resource Knowledge-Grounded Dialogue Generation](https://mlsanity.com/paper/2008.12918/) (2020)
- [RoadMap: A Light-Weight Semantic Map for Visual Localization towards Autonomous Driving](https://mlsanity.com/paper/2106.02527/) (2021)
- [Integration and Performance Analysis of Artificial Intelligence and Computer Vision Based on Deep Learning Algorithms](https://mlsanity.com/paper/2312.12872/) (2023)

## Built on by (most cited first, 4 of 4)

- [Machine Learning-Based Vehicle Intention Trajectory Recognition and Prediction for Autonomous Driving](https://mlsanity.com/paper/2402.16036/) (2024)
- [Maximizing User Experience with LLMOps-Driven Personalized Recommendation Systems](https://mlsanity.com/paper/2404.00903/) (2024)
- [Intelligent Classification and Personalized Recommendation of E-commerce Products Based on Machine Learning](https://mlsanity.com/paper/2403.19345/) (2024)
- [RNA Secondary Structure Prediction Using Transformer-Based Deep Learning Models](https://mlsanity.com/paper/2405.06655/) (2024)

## Abstract (arXiv)

In recent years, the rapid development of high-precision map technology combined with artificial intelligence has ushered in a new development opportunity in the field of intelligent vehicles. High-precision map technology is an important guarantee for intelligent vehicles to achieve autonomous driving. However, due to the lack of research on high-precision map technology, it is difficult to rationally use this technology in the field of intelligent vehicles. Therefore, relevant researchers studied a fast and effective algorithm to generate high-precision GPS data from a large number of low-precision GPS trajectory data fusion, and generated several key data points to simplify the description of GPS trajectory, and realized the "crowdsourced update" model based on a large number of social vehicles for map data collection came into being. This kind of algorithm has the important significance to improve the data accuracy, reduce the measurement cost and reduce the data storage space. On this basis, this paper analyzes the implementation form of crowdsourcing map, so as to improve the various information data in the high-precision map according to the actual situation, and promote the high-precision map can be reasonably applied to the intelligent car.