activity
20172024
most citedAn Efficient Deep Reinforcement Learning Model for Urban Traffic Control

55 citations · 119 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2024★ 18 cited

S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

Xiao Wang, Ke Tang, Xingyuan Dai +5

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying soc…

cs.LG2023★ 1 cited

Counterfactual Graph Transformer for Traffic Flow Prediction

Ying Yang, Kai Du, Xingyuan Dai +1

Traffic flow prediction (TFP) is a fundamental problem of the Intelligent Transportation System (ITS), as it models the latent spatial-temporal dependency of traffic flow for poten…

eess.SY2023

Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization

Shengyue Yao, Jingru Yu, Yi Yu +5

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired…

cs.AI2018★ 55 cited

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…

cs.LG2017★ 45 cited

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…