509 citations · 773 across the 12 of their papers we have counts for
12 papers
IR Design for Application-Specific Natural Language: A Case Study on Traffic Data
Wei Hu, Xuhong Wang, Ding Wang +5
In the realm of software applications in the transportation industry, Domain-Specific Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various other b…
Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors
Long Chen, Yuchen Li, Chao Huang +10
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys ha…
TransWorldNG: Traffic Simulation via Foundation Model
Ding Wang, Xuhong Wang, Liang Chen +7
Traffic simulation is a crucial tool for transportation decision-making and policy development. However, achieving realistic simulations in the face of the high dimensionality and…
Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys
Long Chen, Yuchen Li, Chao Huang +13
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys ha…
Drill the Cork of Information Bottleneck by Inputting the Most Important Data
Xinyu Peng, Jiawei Zhang, Fei-Yue Wang +1
Deep learning has become the most powerful machine learning tool in the last decade. However, how to efficiently train deep neural networks remains to be thoroughly solved. The wid…
Defining Digital Quadruplets in the Cyber-Physical-Social Space for Parallel Driving
Teng Liu, Yang Xing, Long Chen +2
Parallel driving is a novel framework to synthesize vehicle intelligence and transport automation. This article aims to define digital quadruplets in parallel driving. In the cyber…
Digital Quadruplets for Cyber-Physical-Social Systems based Parallel Driving: From Concept to Applications
Teng Liu, Xing Yang, Hong Wang +4
Digital quadruplets aiming to improve road safety, traffic efficiency, and driving cooperation for future connected automated vehicles are proposed with the enlightenment of ACP ba…
A Right-of-Way Based Strategy to Implement Safe and Efficient Driving at Non-Signalized Intersections for Automated Vehicles
Yadong Xing, Can Zhao, ZhiHeng Li +7
Non-signalized intersection is a typical and common scenario for connected and automated vehicles (CAVs). How to balance safety and efficiency remains difficult for researchers. To…
A Negotiation-based Right-of-way Assignment Strategy to Ensure Traffic Safety and Efficiency in Lane Change
Can Zhao, Zhiheng Li, Li Li +3
It is widely acknowledged that verifying the safety of autonomous driving strategies requires a substantial body of simulation testing and road testing. In recent years, the formal…
Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling
Xinyu Peng, Li Li, Fei-Yue Wang
Machine learning, especially deep neural networks, has been rapidly developed in fields including computer vision, speech recognition and reinforcement learning. Although Mini-batc…
An Efficient Deep Reinforcement Learning Model for Urban Traffic Control
Yilun Lin, Xingyuan Dai, Li Li +1
Urban Traffic Control (UTC) plays an essential role in Intelligent Transportation System (ITS) but remains difficult. Since model-based UTC methods may not accurately describe the…
DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction
Xingyuan Dai, Rui Fu, Yilun Lin +2
In this paper, we consider the temporal pattern in traffic flow time series, and implement a deep learning model for traffic flow prediction. Detrending based methods decompose ori…