• Update Date: 10/08/2018
  • Basemap Data Source: Connecticut Department of Transportation Web-GIS (Link) (Copyright: Connecticut Department of Transportation (CTDOT))
  • Coverage: Connecticut State Highway System
  • Layers: CTDOT_Curve (11,983 Events), State_Route_LRS (408 Routes)
  • Format: CTDOT_Curve_v03.gdb
  • Dataframe: GCS_WGS_1984 (GCS), WGS_84_Pseudo_Mercator (WGS_1984_Web_Mercator_Auxiliary_Sphere) (PCS)
  • Download Link: Please contact Ai Research Group for instructions

Definition – The curve inventory results will include all the properties that are necessary for safety analysis or other applications. Depending on different basemap formats, the curve inventory will at least include the following attributes and represented based on the corresponding linear reference system. 

CitationIf the results and the datasets are used for academic publication, please appropriately cite the basemap data source (as listed in the corresponding result section) and the following paper in the publication.

Ai, C. and Tsai, Y. (2015). ”Automatic Horizontal Curve Identification and Measurement Method Using GPS Data.” ASCE Journal of Transportation Engineering, 141(2), 04014078

Disclaimer – All the results and information for the horizontal curves on this website were derived ONLY for academic research purposes. The Ai Research Group derived the results based on the publicly available data at the time of processing, but it does not guarantee any changes in the data sharing policy of the hosting agencies. Please contact the data hosting agencies for more information. The copyright of the data belongs to the data hosting source as the copyright text indicates. The Ai Research Group has internally evaluated and validated the results before it releases any results on this website, but it does not guarantee the quality and the accuracy of the results, nor imply any of its potential applications. Please use the data and the results at your risk, and please use the data ONLY for academic purposes.

The VMZ-2000 has finally started spinning and accumulating point cloud data at the rate of approximately 230k pts/sec. Let’s just give it a spin for a moment, and then figure out the cable management for the mount and the shadow removal for the data.