ETS-Data
ETS-Data is jointly established by Tsinghua University Press and School of Vehicle and Mobility, Tsinghua University, China and is a publicly accessible database, providing indispensable materials for result replications (data, codes, scripts, simulations, experimental designs, etc.). ETS-Data has been indexed by DCI (Data Citation Index) and Google Dataset Search.
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Replication package for STAR: Structure-Aware Representation Learning for Efficient and Robust UAV-based Geo-Localization
Replication package for STAR: Structure-Aware Representation Learning for Efficient and Robust UAV-based Geo-Localization
Asia, China, Macau Region-specific highway driving scenarios generation for accelerating automated driving systems validation: A large-language-model assisted framework
This replication package includes the source codes of the pipeline, source data and results data, demo video, and the complementary material package (mentioned in the paper).
Global Prior knowledge-assisted reinforcement learning for vehicle platoon control in cut-in scenarios
Model and experimental data for “Prior knowledge-assisted reinforcement learning for vehicle platoon control in cut-in scenarios.” The co-simulation model uses TruckSim and MATLAB/Simulink, and the shared data support the main experimental results presented in the paper.
Asia, China, Wuhan Implementation and experimental validation of multi-vehicle cooperation method at intersections
The dataset is obtained from miniature-vehicle experiments at intersections. It contains the experimental results used to evaluate multi-vehicle cooperation under fully connected and mixed-traffic conditions, including vehicle motion data and the main performance indicators reported in the manuscript.
Asia, China Infrastructure-Assisted Cooperative Decision Model With Priority Awareness at Unsignalized Intersections
This replication package contains code necessary to reproduce the results reported in the manuscript "Infrastructure-Assisted Cooperative Decision Model With Priority Awareness at Unsignalized Intersections" (COMMTR-2026-0005).
Hardware: Intel Core i7-11700F processor and an NVIDIA GeForce RTX 3060 Ti
Asia, China, Beijing 
Communications in Transportation Research was launched in 2021, with academic support provided by Tsinghua University and China Intelligent Transportation Systems Association. The Editors-in-Chief are Professor Xiaobo Qu, a member of the Academia Europaea from Tsinghua University and Professor Shuai’an Wang from Hong Kong Polytechnic University. The journal mainly publishes high-quality, original research and review articles that are of significant importance to emerging transportation systems, aiming to become an international platform and window for showcasing and exchanging innovative achievements in transportation and related fields, to promote the exchange and development of transportation research between China and the international academic community. It has been indexed in SCIE, SSCI, ESCI, Ei Compendex, Scopus, DOAJ, TRID and other databases. On June 20, 2024, Communications in Transportation Research achieved its first Impact Factor of 12.5, ranking it top in the "TRANSPORTATION" category (1/58, Q1), and its 2023 CiteScore of 15.2 places it in the top 5% of journals in the Scopus database.
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