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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Domain-Enhanced Dual-Branch Model for Efficient and Interpretable Accident Anticipation (code)
Replication code for 'Domain-Enhanced Dual-Branch Model for Efficient and Interpretable Accident Anticipation'.
Global Urban Visual Clusters and Road Transport Fatalities: A Global City-level Image Analysis
The uploaded files include:
Description file:
Description of the dataset and access to the replication codes.
Datasets
1) Hexagon level datasets used for the clustering analysis in the paper.
2) City-level data used for the main regression analysis.
Code
Code is accessible via `https://github.com/brookefzy/global-city-road-crash`
Global Young urban dwellers' acceptance of autonomous vehicle-induced landscape changes: an eye-tracking study - dataset to JICV manuscript
During the eye-tracking-based data collection —using a Tobii Pro eye camera— participants were presented with a total of nine image pairs depicting streetscapes in their "before" (current) and "after" (following the proliferation of AVs) states for a specific street segment. As a preliminary step, a 60-second calibration procedure was conducted, during which participants were instructed to visually track a moving dot on the screen. Following the briefing and calibration, the image pairs were displayed for data collection, with each pair shown on the screen for 12 seconds.
In terms of the data collected via eye cameras, four important measures can be defined:
Europe, Hungary, Szeged STFC: Spatio-Temporal Formation Control for Connected and Autonomous Vehicles in Multi-Lane Traffic
Replication code for study of “STFC: Spatio-Temporal Formation Control for Connected and Autonomous Vehicles in Multi-Lane Traffic”.
Please refer to Replication package explanatory file.docx for instructions on running the program and contact information.
Asia, China InVDriver: Intra-Instance Aware Vectorized Query-Based Autonomous Driving Transformer
This is the package to reproduce the main results of paper "InVDriver: Intra-Instance Aware Vectorized Query-Based Autonomous Driving Transformer" submitted to JICV (Journal of Intelligent and Connected Vehicles).
Asia, China 
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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