CMU-Penn T-SET UTC Researcher Creates Smarter Parking in Pittsburgh

The Technologies for Safe and Efficient Transportation (T-SET) UTC, a partnership between Carnegie Mellon University (CMU) and the University of Pennsylvania, is working to increase both efficiency and safety in transportation using advanced intelligent transportation systems (ITS) technologies. One of T-SET's recent award-winning collaborations is the ParkPGH project\u2014a smart parking system that uses historical parking and event data to show the availability of parking in eight parking facilities operated by private (Alco Parking) and public (Pittsburgh Parking Authority) partners within the Pittsburgh cultural district

The DR-Train Dataset: Dynamic Responses, GPS Positions and Environmental Conditions of Two Light Rail Vehicles in Pittsburgh [Dataset landing page Title]

DTRT-13-GUTC-26National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT's Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. The current level of dataset documentation is the responsibility of the dataset creator. NTL staff last accessed this dataset at its repository URL on 2022-11-11. If, in the future, you have trouble accessing this dataset at the host repository, please email [email protected] describing your problem. NTL staff will do its best to assist you at that time.This dataset contains the dynamic responses (acceleration records) of two passenger trains with corresponding GPS positions, environmental conditions and track maintenance schedules for a light rail network in the city of Pittsburgh, Pennsylvania in the United States of America. In particular, two light rail vehicles were instrumented (identified as LRV4306 and LRV4313). LRV 4306 has 5 acceleration channels, corresponding to the two uni-axial accelerometers inside the train and the three channels of the tri-axial accelerometer on the wheel truck. LRV 4313 has 8 acceleration channels, corresponding to the two uni-axial accelerometer and the two tri-axial accelerometers inside the train: The dataset contained in this repository is a condensed version of the original raw data. While the accelerometers on the train were sampled continuously, this dataset contains only those measurements for when the train was actually moving along the track (i.e. not idling at a terminal). The data is stored in binary MAT-files (a MATLAB/Octave data format). These files contain MATLAB objects of the class "pass", which is defined in the file pass.m that can be found in the "code" folder. Specifically, two MAT-files named "obj_dic.mat", and found in the "LRV4306" and "LRV4313" folders, contain the "pass" objects of the two trains, respectively. Each category is described in detail. For more detail on the regions of the track, refer to the 'region.fig' file in this folder. The track was divided into distinct regions so that the data over specific sections of track could be compared. These regions were chosen for two reasons: (1) within a region, the train always followed the same track and (2) there are no tunnels in them so the GPS data is relatively consistent. To get started, using MATLAB or Octave try running "main_script.m" in the "code" folder. A data descriptor paper with details of the data collection process was published. The total size of the described zip file is 138.8 GB. Files that end in .MAT are binary data container format used by MATLAB, an open source program. The .csv, Comma Separated Value, file is a simple format that is designed for a database table and supported by many applications. The .csv file is often used for moving tabular data between two different computer programs, due to its open format. Any text editor or spreadsheet program will open .csv files