Author

Jing Gan

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#graph neural networks Open access Oct 2026

Structure-behavior integrated risk prediction of vehicle groups using Graph Neural Networks.

Accurate identification of vehicle-group-level traffic risk is important for intelligent transportation safety management. Existing risk-prediction studies have mainly focused on individual vehicles, pairwise interactions, or aggregated surrogate safety indicators, while the role of group-level structure-behavior coupl...

Jing Gan, Yao Wu, Da-Peng Zhang et al. · Accident Analysis and Preven... · 0 citations

#reinforcement learning Open access Oct 2026

Event-Triggered Pinning Control for Cooperative Ramp Merging in Mixed Traffic via Graph Reinforcement Learning

This paper proposes event-triggered pinning graph reinforcement learning (EPGRL) for cooperative ramp merging in mixed traffic with connected and automated vehicles (CAVs) and human-driven vehicles. EPGRL represents vehicle interactions as a time-varying directed graph and uses a dual-stream graph encoder with temporal...

Can Wang, Zhi-Yu Wang, Wei-Jie Wang et al. · Systems · 0 citations

Open access Aug 2026

Cold-Start Traffic State Forecasting at Unseen Sensor Locations via Support-Conditioned Meta-Graph Learning

Support-conditioned sensor-adaptive meta-graph learning (SC-SAMG) is proposed, which derives target-node representations and spatial dependencies from a short support period and consistently outperforms fine-tuned gated recurrent unit (GRU), adaptive graph convolutional recurrent network (AGCRN), and diffusion convolut...

Can Wang, Zhiyu Wang, Weijie Wang et al. · Italian National Conference... · 0 citations