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Traffic-VL: Reinforced Vision-Language Models for Generalizable End-to-End Traffic Signal Control
Xingchen Zou, Maonan Wang, Kemou Jiang +5
Existing traffic signal control methods typically rely on structured traffic states produced by dedicated perception pipelines. Emerging visual approaches often use idealized simul…
VLALight: Lightweight Vision-Language-Action Models for Emergency-Aware Traffic Signal Control
Kemou Jiang, Maonan Wang, Xingchen Zou +6
Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretation of intersection scenes, ope…
OmniTraffic: A Controllable Generation Pipeline and Benchmark for Spatio-Temporal Traffic Reasoning
Maonan Wang, Zhengyan Huang, Kemou Jiang +13
Traffic scene understanding requires models to reason beyond object recognition, including lane topology, multi-view geometry, temporal evolution, and signal-phase semantics. Howev…