{"ID":2853927,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.15365","arxiv_id":"2510.15365","title":"TranSimHub:A Unified Air-Ground Simulation Platform for Multi-Modal Perception and Decision-Making","abstract":"Air-ground collaborative intelligence is becoming a key approach for next-generation urban intelligent transportation management, where aerial and ground systems work together on perception, communication, and decision-making. However, the lack of a unified multi-modal simulation environment has limited progress in studying cross-domain perception, coordination under communication constraints, and joint decision optimization. To address this gap, we present TranSimHub, a unified simulation platform for air-ground collaborative intelligence. TranSimHub offers synchronized multi-view rendering across RGB, depth, and semantic segmentation modalities, ensuring consistent perception between aerial and ground viewpoints. It also supports information exchange between the two domains and includes a causal scene editor that enables controllable scenario creation and counterfactual analysis under diverse conditions such as different weather, emergency events, and dynamic obstacles. We release TranSimHub as an open-source platform that supports end-to-end research on perception, fusion, and control across realistic air and ground traffic scenes. Our code is available at https://github.com/Traffic-Alpha/TransSimHub.","short_abstract":"Air-ground collaborative intelligence is becoming a key approach for next-generation urban intelligent transportation management, where aerial and ground systems work together on perception, communication, and decision-making. However, the lack of a unified multi-modal simulation environment has limited progress in stu...","url_abs":"https://arxiv.org/abs/2510.15365","url_pdf":"https://arxiv.org/pdf/2510.15365v2","authors":"[\"Maonan Wang\",\"Yirong Chen\",\"Yuxin Cai\",\"Aoyu Pang\",\"Yuejiao Xie\",\"Zian Ma\",\"Chengcheng Xu\",\"Kemou Jiang\",\"Ding Wang\",\"Laurent Roullet\",\"Chung Shue Chen\",\"Zhiyong Cui\",\"Yuheng Kan\",\"Michael Lepech\",\"Man-On Pun\"]","published":"2025-10-17T06:56:34Z","proceeding":"eess.SY","tasks":"[\"eess.SY\",\"cs.LG\",\"cs.MA\"]","methods":"[]","has_code":false,"code_links":[{"ID":608099,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2853927,"paper_url":"https://arxiv.org/abs/2510.15365","paper_title":"TranSimHub:A Unified Air-Ground Simulation Platform for Multi-Modal Perception and Decision-Making","repo_url":"https://github.com/Traffic-Alpha/TransSimHub","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}