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Guide for authors

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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  • Published on: 2025-04-23

    Urban Visual Clusters and Road Transport Fatalities: A Global City-level Image Analysis

    Zhuangyuan Fan, Becky P.Y. Loo

    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`

    Road transportCity
    DOI: 10.26599/ETSD.2025.9190039
    CSTR: 32009.11.ETSD.2025.9190039
    Global
  • Published on: 2025-04-21

    Young urban dwellers' acceptance of autonomous vehicle-induced landscape changes: an eye-tracking study - dataset to JICV manuscript

    Miklós Lukovics, Barbara Nagy

    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:

    • Total Fixation Duration (TFD): the cumulative duration of all fixations within the defined Area of Interest (AOI), reflecting the overall level of visual attention.
    • Average Fixation Duration (AFD): the mean duration of individual fixations within an AOI.
    • Fixation Count (FC): the total number of fixations recorded within the AOI.
    • Time to First Fixation (TTFF): the time elapsed from the onset of the stimulus to the first fixation within the AOI.
    Autonomous vehiclesEye-trackingUrban landscapeUrban environment
    DOI: 10.26599/ETSD.2025.9190038
    CSTR: 32009.11.ETSD.2025.9190038
    Europe, Hungary, Szeged
  • Published on: 2025-04-21

    STFC: Spatio-Temporal Formation Control for Connected and Autonomous Vehicles in Multi-Lane Traffic

    JIANGHONG DONG

    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.

    Connected vehicleAutonomous vehicles
    DOI: 10.26599/ETSD.2025.9190037
    CSTR: 32009.11.ETSD.2025.9190037
    Asia, China
  • Published on: 2025-04-21

    InVDriver: Intra-Instance Aware Vectorized Query-Based Autonomous Driving Transformer

    zhenhua xu, Bo Zhang, Heye Huang, Chunyang Liu, Yaqin Zhang

    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).

    Autonomous vehiclesPath planning
    DOI: 10.26599/ETSD.2025.9190036
    CSTR: 32009.11.ETSD.2025.9190036
    Asia, China
  • Published on: 2025-04-09

    Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs

    Zheng Li
    This dataset is derived from the Waymo Motion dataset and focuses on capturing the interactions between autonomous vehicles (AVs) and traffic control devices such as traffic lights and stop signs. It addresses a critical gap by providing real-world trajectory data that reflects how AVs interpret and respond to traffic control signals, supporting research in AV behavior modeling, traffic simulation, and the design of intelligent transportation systems.
    Traffic flow controlAutonomous vehicles
    DOI: 10.26599/ETSD.2025.9190035
    CSTR: 32009.11.ETSD.2025.9190035
    Global
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Journal
Overview

Communications in Transportation Research

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.

Indexed by international databases