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Vehicle trajectory and pavement behavior data

<p>The dataset includes three documents.</p> <p><strong>HDV_data_NGSIM_I_80.xlsx</strong></p> <p>The vehicle trajectory data from&nbsp;Next Generation SIMulation (NGSIM) dataset was collected on eastbound I-80 in the San Francisco Bay area, in Emeryville, CA, on April 13, 2005,&nbsp;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,&nbsp;space headway, time headway, and time.</p> <p><strong>CAV_data_CARLA_SUMO.xml</strong></p> <p>The simulated CAV trajectory data with CARLA and SUMO, including vehicle id, position, angle, type, speed, lane id, and slope of each frame.</p> <p><strong>LTPP_data.csv</strong></p> <p>The table including 21 columns is calculated from the&nbsp;Long-Term Pavement Performance (LTPP) database.</p> <ul> <li>IRI&nbsp; &nbsp; The IRI value measured when age was 0. (m/km)</li> <li>Cr_Gator&nbsp;&nbsp; &nbsp;Area of alligator cracking in square meters. (m^2)</li> <li>Cr_Lwp&nbsp;&nbsp; &nbsp;Length of longitudinal cracks within the defined wheel paths in meters. (m)</li> <li>Cr_Lnwp&nbsp;&nbsp; &nbsp;Length of longitudinal cracks not in the defined wheel paths in meters. (m)</li> <li>Pt_A&nbsp;&nbsp; &nbsp;Area of patches in square meters. (m^2)</li> <li>Pt_N&nbsp;&nbsp; &nbsp;Number of patches in square meters. (m^2)</li> <li>Cr_Wp&nbsp;&nbsp; &nbsp;Length of wheelpath cracks in meters. (m)</li> <li>Cr_Gt183&nbsp;&nbsp; &nbsp;Total length of transverse cracks greater than 1.83. (m)</li> <li>Rt&nbsp;&nbsp; &nbsp;The depth of rutting in millimeters. (mm)</li> <li>Fr&nbsp;&nbsp; &nbsp;Friction number between the vehicle wheel tire and the pavement</li> <li>IRI_0&nbsp;&nbsp; &nbsp;The IRI value measured when age was 0. (m/km)</li> <li>Tk_Sb&nbsp;&nbsp; &nbsp;Layer thickness measurement for surface coarse and binder course. (in)</li> <li>Md_s&nbsp;&nbsp; &nbsp;Average backcalculated elastic modulus of the surface layer.(psi)</li> <li>Hydr&nbsp;&nbsp; &nbsp;Average measured hydraulic conductivity of the specimen. (cm/sec)</li> <li>Prcp &nbsp;&nbsp; &nbsp;Average monthly precipitation in millimeters. (mm)</li> <li>Fz&nbsp;&nbsp; &nbsp;Average freeze index. (℃/day)</li> <li>Esal&nbsp;&nbsp; &nbsp;Annual average ESAL (kESAL)</li> <li>Esal_q&nbsp;&nbsp; &nbsp;quadratic form of Kesal (kESAL^2)</li> <li>Age&nbsp;&nbsp; &nbsp;Time duration between new construction to roughness survey date. (year)</li> <li>Gr&nbsp;&nbsp; &nbsp;Mean specific gravity of asphalt cement</li> <li>Pt_Ca&nbsp;&nbsp; &nbsp;Coarse aggregate amount percent by total weight of aggregate in percentage. (%)&nbsp;</li> </ul>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0