This is the EVENT data captured from the New York City CV Pilot project that was processed by the independent evaluators at Volpe. Additional data collected and data dictionary are in the attachments. Each EVENT record documents the details of one application warning that occurred on an Aftermarket Safety Device (ASD) in an equipped host vehicle and includes CV messages from a defined recording time both before and after the warning was generated by the host ASD. Messages in the recording time window include the Basic Safety Messages (BSM) of the host vehicle that received the warning, as well as other BSMs received from the warning target equipped vehicle (for V2V applications) or other nearby equipped vehicles. Depending on the application warning type, MAP messages, Signal Phase and Timing (SPaT) messages, and Traveler Information Messages (TIM) that were heard by the host vehicle may also be included in the event record.

The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Basic Safety Messages (BSMs) generated by participant and public transportation vehicles onboard units (OBU) and transmitted to road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, BSM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 and J2945/1 standards and adopted units of measure. This dataset holds a flattened sample of the BSM data from Tampa CV Pilot. An extra geo column (coreData_position) was added to this dataset to allow for mapping of the geocoded BSM data within Socrata, and a column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.

ITS JPO's Connected Vehicle Pilot Deployment Program integrates connected vehicle research concepts into practical and effective elements to enhance existing operational capabilities. Data were collected throughout each pilot to facilitate independent evaluations of the use of connected vehicle technology on real roadways. To encourage additional study and reuse of these data, ITS DataHub has partnered with each pilot site to make sanitized and anonymized tabular and non-tabular data from these projects available to the public. This article gives you a brief overview of what each pilot focused on and what types of CV Pilot data and tools are available on ITS DataHub.

This dataset contains a one-month sample of flattened EVENT data records from the New York City (NYC) Connected Vehicle (CV) Pilot that have undergone obfuscation of precise time and location details as well as other vehicle identifiers. The full unflattened event data from NYC CV pilot can be found in the ITS Sandbox. Each EVENT record documents the details of one application warning that occurred on an Aftermarket Safety Device (ASD) in an equipped host vehicle and includes CV messages from a defined recording time both before and after the warning was generated by the host ASD. Messages in the recording time window include the Basic Safety Messages (BSM) of the host vehicle that received the warning, as well as other BSMs received from the warning target equipped vehicle (for V2V applications) or other nearby equipped vehicles. Depending on the application warning type, MAP messages, Signal Phase and Timing (SPaT) messages, and Traveler Information Messages (TIM) that were heard by the host vehicle may also be included in the event record.

The Trajectory Conversion Algorithm Version 2.3 (TCA) is designed to test different strategies for producing, transmitting, and storing Connected Vehicle information. The TCA uses vehicle trajectory data, roadside equipment (RSE) location information, cellular region information and strategy information to emulate the messages connected vehicles would produce. This data set contains common data sets generated by the TCA using the BSM and PDM at 100% market penetration for two simulated traffic networks, an arterial network (Van Ness Avenue in San Francisco, CA) and a freeway network (the interchange of I-270 and I-44 in St. Louis, MO). This legacy dataset was created before data.transportation.gov and is only currently available via the attached file(s). Please contact the dataset owner if there is a need for users to work with this data using the data.transportation.gov analysis features (online viewing, API, graphing, etc.) and the USDOT will consider modifying the dataset to fully integrate in data.transportation.gov.

The files in this data environment were produced using the Vehicle Awareness Device (VAD) installed on one test vehicle over a two month period. The VAD installed in the test car is identical to the VADs installed in over 2800 vehicles participating in the Safety Pilot Model Demonstration conducted from August 2012 through August 2013 by the National Highway Traffic Safety Administration (NHTSA) in Ann Arbor, Michigan. This legacy dataset was created before data.transportation.gov and is only currently available via the attached file(s). Please contact the dataset owner if there is a need for users to work with this data using the data.transportation.gov analysis features (online viewing, API, graphing, etc.) and the USDOT will consider modifying the dataset to fully integrate in data.transportation.gov.

Data is from the small-scale demonstration of the Intelligent Network Flow Optimization (INFLO) Prototype System and applications in Seattle, Washington. Connected vehicle systems were deployed in 21 vehicles in a scripted driving scenario circuiting this I-5 corridor northbound and southbound during morning rush hour. Basic Safety Messages (BSM) sent by connected vehicles (CVs) through either the cellular network or Dedicated Short Range Communication (DSRC) when the vehicle is in the range of Roadside Units (RSU). These messages were received by the traffic management center (TMC).

Contains all Basic Safety Messages (BSMs) collected during the Advanced Messaging Concept Development (AMCD) field testing program. For this project, all of the Part I BSM message fields were populated. Additional data fields were also added to the row to identify sender, time of communication, mode of communication, etc., allowing the consumer of this data set to accurately track messages through the system. All BSMs are generated by OBUs and ultimately received by the VCC Cloud server.

The objective of this project was to develop technical relationships between reliability improvement strategies and reliability performance metrics. This project defined reliability, explained the importance of travel time distributions for measuring reliability, and recommended specific reliability performance measures. The research reexamined the contribution of the various causes of nonrecurring congestion on urban freeway sections, however, some attention was also given to rural highways and urban arterials). Numerous actions that can potentially reduce nonrecurring congestion were identified with an indication of their relative importance. Models for predicting nonrecurring congestion were developed using three methods, all based on empirical procedures: The first involved before and after studies; the second was termed a 'data poor' approach and resulted in a parsimonious and easy-to-apply set of models; the third was entitled a 'data rich model' and used cross-section inputs including data on selected factors known to directly affect nonrecurring congestion. An important conclusion of the study is that actions to improve operations, reduce demand, and increase capacity all can improve travel time reliability. The 3 attached zip files contains comma separated value (.csv) files of data to support SHRP 2 report S2-L03-RR-1, Analytical procedures for determining the impacts of reliability mitigation strategies.Zip size is 1.83 MB. Files were accessed in Microsoft Excel 2016. Data will be preserved as is. To view publication see: https://rosap.ntl.bts.gov/view/dot/3605