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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The dataset of the paper "MoTIF: An end-to-end Multimodal Road Traffic Scene Understanding Foundation Model"
该数据集包括 2023 年 10 月城市十字路口四个方向的监控视频。 这些视频的分辨率为 3840×2160，帧速率为每秒 30 帧 （fps），场景理解标注涵盖交通拥堵程度、行人和车辆数量、行为意图等正常场景。
Asia, China, 天津 This repository includes the replication code for utilizing the PFD method for traffic state estimation applications.
Europe, Sweden North America, United States Beyond Conventional Vision: RGB-Event Fusion for Robust Object Detection in Dynamic Traffic Scenarios
The code is used in the paper:"Beyond Conventional Vision: RGB-Event Fusion for Robust Object Detection in Dynamic Traffic Scenarios"
Global Optimal speed limit under multi-class user equilibrium: A prescriptive approach using mathematical programming
The replication package contains the matlab code and data to replicate the performed experiments described in the manuscript.
Europe, Netherlands Original data used in the paper Privacy-preserving Personalized Pricing and Matching for Ride-hailing Platforms.
This dataset is the original data used in the paper Privacy-preserving Personalized Pricing and Matching for Ride-hailing Platforms. Based on the real demand information contained in this dataset, we generated the dataset used in our study. The generation process is detailed in the numerical experiments section of the paper.
Asia, China, Haikou 
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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