Click “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise _location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf

ITS DataHub has partnered with the Federal Highway Administration's (FHWA's) Next Generation SIMulation (NGSIM) program to make available detailed vehicle trajectory data and supporting data files along with the raw and processed video files from the NGSIM data collection efforts. Researchers for the NGSIM program collected the specified data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, GA. This article provides a brief overview of the NGSIM program data collection as well as what types of data are available on ITS DataHub. Some examples of possible uses for the data and information on how to cite the various NGSIM datasets are also included.

As part of the Federal Highway Administration’s (FHWA) Next Generation Simulation (NGSIM) project, video data was collected on a freeway segment of US 101 (Hollywood Freeway) located in Los Angeles, California on June 15th, 2005. A total of 45 minutes of transcribed data are included in this full data set, segmented into three 15 minute periods representing: 1) 7:50 a.m. to 8:05 a.m., 2) 8:05 a.m. to 8:20 a.m., and 3) 8:20 a.m. to 8:35 a.m. on June 15th, 2005. The dataset includes files for both raw and processed video data from each of the eight cameras for the three time periods available for download. Camera numbering is in order of southern-most (1) to northern-most (8). The raw video files give the original vehicle movement data and offer users a view of how the section was observed. The processed video files provide videos of the vehicles along with a superimposition of the vehicle identification numbers. These videos can be used alone or can be used for cross referencing of the textual vehicle trajectory data provided in the NGSIM trajectory data with the corresponding video.

For related datasets please see the following: - NGSIM Vehicle Trajectories and Supporting Data: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf

As part of the Federal Highway Administration’s (FHWA) Next Generation Simulation (NGSIM) project, video data were collected on November 8th, 2006 on an arterial segment on Peachtree Street located in Atlanta, Georgia. The data represents 30 minutes total, segmented into two periods (12:45 p.m. to 1:00 p.m. and 4:00 p.m. to 4:15 p.m.). The dataset includes files for both raw and processed video data from each of the eight cameras for the two time periods available for download. Camera numbering is in order of southern-most (1) to northern-most (8). The raw video files give the original vehicle movement data and offer users a view of how the section was observed. The processed video files provide videos of the vehicles along with a superimposition of the vehicle identification numbers. These videos can be used alone or can be used for cross referencing of the textual vehicle trajectory data provided in the NGSIM trajectory data with the corresponding video.

For related datasets please see the following: - NGSIM Vehicle Trajectories and Supporting Data: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k

As part of the Federal Highway Administration’s (FHWA) Next Generation Simulation (NGSIM) project, video data were collected on June 16th, 2005 on an arterial segment on Lankershim Boulevard located in Los Angeles, California. The data represents 30 minutes total, segmented into two periods (8:30 a.m. to 8:45 a.m. and 8:45 a.m. to 9:00 a.m.). The dataset includes files for both raw and processed video data from each of the five cameras for the two time periods available for download. Camera numbering is in order of southern-most (1) to northern-most (5). The raw videos give the original vehicle movement data and offer users a view of how the section was observed. The processed video files provide videos of the vehicles along with a superimposition of the vehicle identification numbers. These videos can be used alone or can be used for cross referencing of the textual vehicle trajectory data provided in the NGSIM trajectory data with the corresponding video.

For related datasets please see the following: - NGSIM Vehicle Trajectories and Supporting Data: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf

As part of the Federal Highway Administration’s (FHWA) Next Generation Simulation (NGSIM) project, video data was collected on a segment of Interstate 80 located in Emeryville, California on April 13, 2005. A total of 45 minutes of video data are available, segmented into three 15 minute periods: 1) 4:00 p.m. to 4:15 p.m.; 2) 5:00 p.m. to 5:15 p.m.; and 3) 5:15 p.m. to 5:30 p.m. The dataset includes files for both raw and processed video data from each of the seven cameras for the three time periods available for download. Camera numbering is in order of southern-most (1) to northern-most (7). The raw videos give the original vehicle movement data and offer users a view of how the section was observed. The processed video files provide videos of the vehicles along with a superimposition of the vehicle identification numbers. These videos can be used alone or can be used for cross referencing of the textual vehicle trajectory data provided in the NGSIM trajectory data with the corresponding video.

For related datasets please see the following: - NGSIM Vehicle Trajectories and Supporting Data: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf

Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras.NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset.

This dataset contains the trajectories of all vehicles traveling on a section of the U.S. Highway 101 (Hollywood Freeway) in Los Angeles, CA from 7:50-8:05 AM on June 15, 2005 (a Wednesday). The trajectories were collected at a rate of 10 Hz. More details on the study section and method of collecting the trajectories are contained in the "data-analysis-report".

This data may be used to create models of driving behavior and is useful for studying phenomena such as traffic congestion and shockwaves. It includes both an on-ramp and an off-ramp as well.

Acknowledgements

Both the raw data and analysis report were provided by U.S. FHWA's Next Generation SIMulation (NGSIM) project.

which is also named as WUT-NGSIM.

As part of the Federal Highway Administration’s (FHWA) Next Generation Simulation (NGSIM) project, video data were collected on June 16th, 2005 on an arterial segment on Lankershim Boulevard located in Los Angeles, California. The data represents 30 minutes total, segmented into two periods (8:30 a.m. to 8:45 a.m. and 8:45 a.m. to 9:00 a.m.). The dataset includes files for both raw and processed video data from each of the five cameras for the two time periods available for download. Camera numbering is in order of southern-most (1) to northern-most (5). The raw videos give the original vehicle movement data and offer users a view of how the section was observed. The processed video files provide videos of the vehicles along with a superimposition of the vehicle identification numbers. These videos can be used alone or can be used for cross referencing of the textual vehicle trajectory data provided in the NGSIM trajectory data with the corresponding video.

For related datasets please see the following: - NGSIM Vehicle Trajectories and Supporting Data: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf

The dataset includes three documents.

HDV_data_NGSIM_I_80.xlsx

The vehicle trajectory data from Next Generation SIMulation (NGSIM) dataset was collected on eastbound I-80 in the San Francisco Bay area, in Emeryville, CA, on April 13, 2005, from 4:03:56 pm to 4:08:56 pm. Including vehicle id, frame id, the total count of frames of each vehicle, global time, local position, global position, vehicle length, vehicle width, vehicle class, speed, acceleration, lane id, preceding vehicle id, following vehicle id, space headway, time headway, and time.

CAV_data_CARLA_SUMO.xml

The simulated CAV trajectory data with CARLA and SUMO, including vehicle id, position, angle, type, speed, lane id, and slope of each frame.

LTPP_data.csv

The table including 21 columns is calculated from the Long-Term Pavement Performance (LTPP) database.

• IRI The IRI value measured when age was 0. (m/km)
• Cr_Gator Area of alligator cracking in square meters. (m^2)
• Cr_Lwp Length of longitudinal cracks within the defined wheel paths in meters. (m)
• Cr_Lnwp Length of longitudinal cracks not in the defined wheel paths in meters. (m)
• Pt_A Area of patches in square meters. (m^2)
• Pt_N Number of patches in square meters. (m^2)
• Cr_Wp Length of wheelpath cracks in meters. (m)
• Cr_Gt183 Total length of transverse cracks greater than 1.83. (m)
• Rt The depth of rutting in millimeters. (mm)
• Fr Friction number between the vehicle wheel tire and the pavement
• IRI_0 The IRI value measured when age was 0. (m/km)
• Tk_Sb Layer thickness measurement for surface coarse and binder course. (in)
• Md_s Average backcalculated elastic modulus of the surface layer.(psi)
• Hydr Average measured hydraulic conductivity of the specimen. (cm/sec)
• Prcp Average monthly precipitation in millimeters. (mm)
• Fz Average freeze index. (℃/day)
• Esal Annual average ESAL (kESAL)
• Esal_q quadratic form of Kesal (kESAL^2)
• Age Time duration between new construction to roughness survey date. (year)
• Gr Mean specific gravity of asphalt cement
• Pt_Ca Coarse aggregate amount percent by total weight of aggregate in percentage. (%)

Basic information of NIGSIM data.

Sensitivity analysis results of node Typ.

This repository supports the research on mitigating traffic oscillations using a Physics-Enhanced Residual Learning (PERL)-based predictive control approach. It contains all necessary components related to both the prediction and control aspects of the study. The prediction module includes the pre-processed NGSIM dataset, prediction models, and the resulting predictions, which focus on forecasting the behavior of preceding vehicles, including speed fluctuations, to allow timely responses. The control module implements a Model Predictive Control (MPC) approach that uses the prediction results to control connected and automated vehicles (CAVs), enhancing safety and comfort in mixed traffic environments. All code, data, and results are included to ensure that users can replicate the experiments and validate the findings effectively.

Bayesian network node variables and their discrete values.

Filtered NGSIM and Artificial Datasets used in the paper "A Compositional Paradigm for Read-time systems".

Driving style evaluation index.

Principal component score coefficient matrix.