Llm4drive: A survey of large language models for autonomous driving

Z Yang, X Jia, H Li, J Yan - … 2024 Workshop on Open-World Agents, 2023 - openreview.net
Autonomous driving technology, a catalyst for revolutionizing transportation and urban
mobility, has the tend to transition from rule-based systems to data-driven strategies …

Traj-llm: A new exploration for empowering trajectory prediction with pre-trained large language models

Z Lan, L Liu, B Fan, Y Lv, Y Ren… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Predicting the future trajectories of dynamic traffic actors is a cornerstone task in
autonomous driving. Though existing notable efforts have resulted in impressive …

Genfollower: Enhancing car-following prediction with large language models

X Chen, M Peng, PH Tiu, Y Wu, J Chen… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Accurate modeling of car-following behaviors is crucial for autonomous driving systems.
While recent advancements in large language models (LLMs) have shown promise in …

XLM for Autonomous Driving Systems: A Comprehensive Review

S Fourati, W Jaafar, N Baccar, S Alfattani - arXiv preprint arXiv:2409.10484, 2024 - arxiv.org
Large Language Models (LLMs) have showcased remarkable proficiency in various
information-processing tasks. These tasks span from extracting data and summarizing …

Explainable Traffic Flow Prediction with Large Language Models

X Guo, Q Zhang, M Peng, M Zhua - arXiv preprint arXiv:2404.02937, 2024 - arxiv.org
Traffic flow prediction provides essential future views in the intelligent transportation system.
Explainable predictions offer valuable insights into the factors influencing traffic patterns …

From ideas to ventures: building entrepreneurship knowledge with LLM, prompt engineering, and conversational agents

M Thanasi-Boçe, J Hoxha - Education and Information Technologies, 2024 - Springer
Entrepreneurship education has evolved to meet the demands of a dynamic business
environment, necessitating innovative teaching methods to prepare entrepreneurs for …

SwapTransformer: Highway overtaking tactical planner model via imitation learning on OSHA dataset

A Shamsoshoara, SB Salih, P Aghazadeh - IEEE Access, 2024 - ieeexplore.ieee.org
This paper investigates the high-level decision-making problem in highway scenarios
regarding lane changing and over-taking other slower vehicles. In particular, this paper aims …

Diffusion Models for Intelligent Transportation Systems: A Survey

M Peng, K Chen, X Guo, Q Zhang, H Lu… - arXiv preprint arXiv …, 2024 - arxiv.org
Intelligent Transportation Systems (ITS) are vital in modern traffic management and
optimization, significantly enhancing traffic efficiency and safety. Recently, diffusion models …

Trajectory-Guided Driving Behavior Prediction for Autonomous Driving

Z Zhang, Y Chang, Q Dong… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Driving behavior prediction (DBP) plays an important role in autonomous driving systems.
Accurately anticipating driving behaviors of ego-vehicles, such as lane changes or left/right …

Large (Vision) Language Models for Autonomous Vehicles: Current Trends and Future Directions

H Tian, K Reddy, Y Feng, M Quddus, Y Demiris… - Authorea Preprints - techrxiv.org
As autonomous vehicles (AVs) advance, the integration of Large (Vision) Language Models
(L (V) LMs) has emerged as a promising approach to enhance AV capabilities in perception …