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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Exploring levels of adoption of multi-function transport apps: Transtheoretical model of change on the customer journey of Transport-SuperApps (TSA) users
Data used in this study is based on questionnaire distribution in four Indonesian cities about Transport-SuperApps behaviour. 1,051 valid data are used for the analysis. The list of questions that were used in this study is described in the paper. The script and the packages for analysis were disclosed, however, due to funders’ terms and conditions, the data cannot be disclosed.
Asia, Indonesia, Indonesia Laboratory Experimental Datasets on Route-choice Games
Total 312 participants in approximately equal proportions of males and females were invited to participate the decision-making experiments for the payoffs that were contingent on their performance. The participants were randomly assigned to 17 groups and they were required to make DTD route choices with no mutual communication. The following eight DTD scenarios with the same origin-destination (OD) pair were set.
• Scenario 1 was the baseline scenario containing a symmetric two-route network.
• Scenarios 2-5 extended Scenario 1 by using asymmetric two-route networks and different cost functions to investigate subject’s route choice behaviors under different cost feedback.
• Scenarios 6-7 employed asymmetric networks with three routes to observe more complicated route choice behavior. •Scenario 8 extended the configuration to non-linear cost functions and different group sizes (24 subjects per group in Scenario 8, while 16 in others), which would demonstrate the robustness of the proposed theoretical model.
Asia, China, Tianjin Multi-Level Objectives Control of AVs at A Saturated Signalized Intersection with Multi-Agent Deep Reinforcement Learning Approach
Code and experimental data for "Multi-Level Objectives Control of AVs at A Saturated Signalized Intersection with Multi-Agent Deep Reinforcement Learning Approach."Codes are written in Python and developed on an open-source tool “Flow”.( https://flow.readthedocs.io/en/latest/index.html)
Global Vehicle and charging scheduling of electric bus fleets: a comprehensive review
Purpose — Transit electrification has emerged as an unstoppable force, driven by the considerable environmental benefits if offers. Nevertheless, the adoption of battery electric bus is still impeded by its limited flexibility. The constraint necessitates adjustments to current bus scheduling plans. To this end, this paper aspires to offer a thorough review of articles focused on battery electric bus scheduling.
Design/methodology/approach — We provide a comprehensive review of 42 papers on electric bus scheduling and related studies, with a focus on the most recent developments and trends in this research domain.
Asia, China VTOL sites location considering obstacle clearance during approach and departure
This dataset constains data and codes for determining the VTOL sites.
Asia, China, Shenzhen 
Communications in Transportation Research publishes peer-reviewed high-quality research representing important advances of significance to emerging transport systems. The mission is to provide fair, fast, and expert peer review to authors and insightful theories, impactful advances, and interesting discoveries to readers. We welcome submissions of significant and general topics, of inter-disciplinary nature (transport, civil, control, artificial intelligence, social science, psychological science, medical services, etc.), of complex and inter-related system of systems, of strong evidence of data strength, of visionary analysis and forecasts towards the way forward, and of potentially implementable and utilizable policies/practices. It is indexed in Scopus and DOAJ.
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