39 citations · 126 across the 47 of their papers we have counts for
12 papers · 1 filter
AccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model
Lening Wang, Yilong Ren, Han Jiang +9
Traffic accidents, being a significant contributor to both human casualties and property damage, have long been a focal point of research for many scholars in the field of traffic…
Towards Knowledge-driven Autonomous Driving
Xin Li, Yeqi Bai, Pinlong Cai +14
This paper explores the emerging knowledge-driven autonomous driving technologies. Our investigation highlights the limitations of current autonomous driving systems, in particular…
Open-sourced Data Ecosystem in Autonomous Driving: the Present and Future
Hongyang Li, Yang Li, Huijie Wang +16
With the continuous maturation and application of autonomous driving technology, a systematic examination of open-source autonomous driving datasets becomes instrumental in fosteri…
On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving
Licheng Wen, Xuemeng Yang, Daocheng Fu +15
The pursuit of autonomous driving technology hinges on the sophisticated integration of perception, decision-making, and control systems. Traditional approaches, both data-driven a…
TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Models
Siyao Zhang, Daocheng Fu, Zhao Zhang +2
With the promotion of chatgpt to the public, Large language models indeed showcase remarkable common sense, reasoning, and planning skills, frequently providing insightful guidance…
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
Licheng Wen, Daocheng Fu, Xin Li +7
Recent advancements in autonomous driving have relied on data-driven approaches, which are widely adopted but face challenges including dataset bias, overfitting, and uninterpretab…
EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planning
Xu Han, Xianda Chen, Meixin Zhu +3
Car-following models have made significant contributions to our understanding of longitudinal driving behavior. However, they often exhibit limited accuracy and flexibility, as the…
TrafficMCTS: A Closed-Loop Traffic Flow Generation Framework with Group-Based Monte Carlo Tree Search
Ze Fu, Licheng Wen, Pinlong Cai +3
Traffic flow simulation within the domain of intelligent transportation systems is garnering significant attention, and generating realistic, diverse, and human-like traffic patter…
LimSim: A Long-term Interactive Multi-scenario Traffic Simulator
Licheng Wen, Daocheng Fu, Song Mao +4
With the growing popularity of digital twin and autonomous driving in transportation, the demand for simulation systems capable of generating high-fidelity and reliable scenarios i…
Drive Like a Human: Rethinking Autonomous Driving with Large Language Models
Daocheng Fu, Xin Li, Licheng Wen +4
In this paper, we explore the potential of using a large language model (LLM) to understand the driving environment in a human-like manner and analyze its ability to reason, interp…
Human-like Decision-making at Unsignalized Intersection using Social Value Orientation
Yan Tong, Licheng Wen, Pinlong Cai +3
With the commercial application of automated vehicles (AVs), the sharing of roads between AVs and human-driven vehicles (HVs) becomes a common occurrence in the future. While resea…
Bringing Diversity to Autonomous Vehicles: An Interpretable Multi-vehicle Decision-making and Planning Framework
Licheng Wen, Pinlong Cai, Daocheng Fu +2
With the development of autonomous driving, it is becoming increasingly common for autonomous vehicles (AVs) and human-driven vehicles (HVs) to travel on the same roads. Existing s…