39 citations · 135 across the 16 of their papers we have counts for
16 papers
ScienceFlow: A long-horizon agent for ML research, scientific discovery and beyond
Mingming Zhao, Jiqian Dong, Kangping Xu +16
Enabling LLM agents to sustain productive, stable, and goal-aligned research over extended horizons is a central challenge for autonomous machine learning and scientific discovery,…
Hista and Numca: Estimate State Value Effectively for LLM Reinforcement Learning
Zizhe Chen, Jiqian Dong, Yizhou Tian +4
Reinforcement learning (RL) refines large language models (LLMs) by directly optimizing model behavior through reward signals. While accurate state value estimation is critical for…
Generative Models in Decision Making: A Survey
Xinyu Shao, Jianping Zhang, Haozhi Wang +9
Generative models have fundamentally reshaped the landscape of decision-making, reframing the problem from pure scalar reward maximization to high-fidelity trajectory generation an…
Deep Reinforcement Learning Based Framework for Mobile Energy Disseminator Dispatching to Charge On-the-Road Electric Vehicles
Jiaming Wang, Jiqian Dong, Sikai Chen +2
The exponential growth of electric vehicles (EVs) presents novel challenges in preserving battery health and in addressing the persistent problem of vehicle range anxiety. To addre…
Transfusor: Transformer Diffusor for Controllable Human-like Generation of Vehicle Lane Changing Trajectories
Jiqian Dong, Sikai Chen, Samuel Labi
With ongoing development of autonomous driving systems and increasing desire for deployment, researchers continue to seek reliable approaches for ADS systems. The virtual simulatio…
Reason induced visual attention for explainable autonomous driving
Sikai Chen, Jiqian Dong, Runjia Du +2
Deep learning (DL) based computer vision (CV) models are generally considered as black boxes due to poor interpretability. This limitation impedes efficient diagnoses or prediction…
Development and testing of an image transformer for explainable autonomous driving systems
Jiqian Dong, Sikai Chen, Shuya Zong +3
In the last decade, deep learning (DL) approaches have been used successfully in computer vision (CV) applications. However, DL-based CV models are generally considered to be black…
Addressing crash-imminent situations caused by human driven vehicle errors in a mixed traffic stream: a model-based reinforcement learning approach for CAV
Jiqian Dong, Sikai Chen, Samuel Labi
It is anticipated that the era of fully autonomous vehicle operations will be preceded by a lengthy "Transition Period" where the traffic stream will be mixed, that is, consisting…
Urban traffic dynamic rerouting framework: A DRL-based model with fog-cloud architecture
Runjia Du, Sikai Chen, Jiqian Dong +3
Past research and practice have demonstrated that dynamic rerouting framework is effective in mitigating urban traffic congestion and thereby improve urban travel efficiency. It ha…
Using Empirical Trajectory Data to Design Connected Autonomous Vehicle Controllers for Traffic Stabilization
Yujie Li, Sikai Chen, Runjia Du +3
Emerging transportation technologies offer unprecedented opportunities to improve the efficiency of the transportation system from the perspectives of energy consumption, congestio…
A Cooperative Control Framework for CAV Lane Change in a Mixed Traffic Environment
Runjia Du, Sikai Chen, Yujie Li +3
In preparing for connected and autonomous vehicles (CAVs), a worrisome aspect is the transition era which will be characterized by mixed traffic (where CAVs and human-driven vehicl…
A DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network
Jiqian Dong, Sikai Chen, Paul Young Joun Ha +2
Connected Autonomous Vehicle (CAV) Network can be defined as a collection of CAVs operating at different locations on a multilane corridor, which provides a platform to facilitate…
Leveraging the Capabilities of Connected and Autonomous Vehicles and Multi-Agent Reinforcement Learning to Mitigate Highway Bottleneck Congestion
Paul Young Joun Ha, Sikai Chen, Jiqian Dong +3
Active Traffic Management strategies are often adopted in real-time to address such sudden flow breakdowns. When queuing is imminent, Speed Harmonization (SH), which adjusts speeds…
Facilitating Connected Autonomous Vehicle Operations Using Space-weighted Information Fusion and Deep Reinforcement Learning Based Control
Jiqian Dong, Sikai Chen, Yujie Li +3
The connectivity aspect of connected autonomous vehicles (CAV) is beneficial because it facilitates dissemination of traffic-related information to vehicles through Vehicle-to-Exte…
Leveraging Vehicle Connectivity and Autonomy to Stabilize Flow in Mixed Traffic Conditions: Accounting for Human-driven Vehicle Driver Behavioral Heterogeneity and Perception-reaction Time Delay
Yujie Li, Sikai Chen, Paul Young Joun Ha +3
The erratic nature of human driving tends to trigger undesired waves that amplify as successive driver reactions propagate from the errant vehicle to vehicles upstream. Known as ph…
A Dynamic Network and Representation LearningApproach for Quantifying Economic Growth fromSatellite Imagery
Jiqian Dong, Gopaljee Atulya, Kartikeya Bhardwaj +1
Quantifying the improvement in human living standard, as well as the city growth in developing countries, is a challenging problem due to the lack of reliable economic data. Theref…