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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VTOL sites location considering obstacle clearance during approach and departure
This dataset constains data and codes for determining the VTOL sites.
Asia, China, Shenzhen Empowering highway network: optimal deployment and strategy for dynamic wireless charging lanes
The OD data in this paper are from the real road network data of Guangdong province. The initial SoC in the paper is randomly generated and follows a normal distribution.
Asia, China, Guangdong Real-Time Intersection Vehicle Turning Movement Counts from Live UAV Video Stream using Multiple Object Tracking
There are two folders containing the replication files.
The first folder contains the Voc-Poc tool for transmitting the captured video stream from the Goggles to the local server.
The second folder contains the main code and main results of this manuscript. The main code is for the YOLO + StrongSORT + TMC collection algorithm. The main code is in the track.py file.
Asia, China, Hong Kong Less is more: Lightweight reinforcement learning method for traffic signal control with less observation
Data and code for "Less is more: Lightweight reinforcement learning method for traffic signal control with less observation"
Asia, China, Hangzhou and Jinan Electric Vehicle Trip Energy Consumption Data
The data consists of normal driving records for dozens of private cars over several months (from June 5, 2015 to June 30, 2016), with a sampling frequency of one minute. The basic specifications of the vehicles are as follows: Roewe E50 is a pure electric vehicle, weighing 1080 kilograms. It is equipped with a 22.4 kWh battery pack, and is reported to have a driving range of 170 kilometers. The raw data has been preprocessed and denoised, resulting in a final dataset containing 10,000 trips. This dataset offers substantial potential for reuse in research and analysis focused on electric vehicle energy consumption. Researchers, engineers, and policy makers can leverage this data to understand patterns, develop optimization algorithms, and inform energy-efficient practices. The dataset adheres to all applicable legal requirements. All sensitive information has been removed, and the data has been preprocessed to ensure confidentiality. There are no known legal or ethical obstacles to its use.
Asia, China, Shanghai 
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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