# Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology

arXiv: https://arxiv.org/abs/2404.04492 · HTML: https://mlsanity.com/paper/2404.04492/

## Key facts

- Cited by 1 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 6 Apr 2024.

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

- [Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age](https://mlsanity.com/paper/1606.05830/) (2016)
- [ViTCN: Vision Transformer Contrastive Network For Reasoning](https://mlsanity.com/paper/2403.09962/) (2024)
- [Comprehensive Implementation of TextCNN for Enhanced Collaboration between Natural Language Processing and System Recommendation](https://mlsanity.com/paper/2403.09718/) (2024)

## Built on by (most cited first, 1 of 1)

- [A Physics-Informed Neural Network Approach for UAV Path Planning in Dynamic Environments](https://mlsanity.com/paper/2510.21874/) (2025)

## Abstract (arXiv)

In addition to environmental perception sensors such as cameras, radars, etc. in the automatic driving system, the external environment of the vehicle is perceived, in fact, there is also a perception sensor that has been silently dedicated in the system, that is, the positioning module. This paper explores the application of SLAM (Simultaneous Localization and Mapping) technology in the context of automatic lane change behavior prediction and environment perception for autonomous vehicles. It discusses the limitations of traditional positioning methods, introduces SLAM technology, and compares LIDAR SLAM with visual SLAM. Real-world examples from companies like Tesla, Waymo, and Mobileye showcase the integration of AI-driven technologies, sensor fusion, and SLAM in autonomous driving systems. The paper then delves into the specifics of SLAM algorithms, sensor technologies, and the importance of automatic lane changes in driving safety and efficiency. It highlights Tesla's recent update to its Autopilot system, which incorporates automatic lane change functionality using SLAM technology. The paper concludes by emphasizing the crucial role of SLAM in enabling accurate environment perception, positioning, and decision-making for autonomous vehicles, ultimately enhancing safety and driving experience.