Road visibility is critical to motorists in making decisions such as stopping, slow downing, turning, entering a traffic stream from a driveway, or merging into traffic. Adequate visibility allows motorists the time they need to avoid vehicle crashes and conflicts and will help keep roadways operating safely and smoothly. Insufficient visibility is a significant factor in roadway crashes and near collisions. This paper utilizes the ArcMap-GIS viewshed tools, and the location analysis techniques to present an evaluation of the existing visibility on portions of the interstate highway I70 in the State of Missouri compared to AASHTO requirements. The evaluation of the existing visibility is conducted on the I70 segments at Boone, Callaway, and Cooper counties. This method is a useful tool for understanding location-based risks of limited visibility on the I70 or similar highways. The GIS techniques used show that the ArcMap-GIS tools can be used effectively in determining the road visibility and locating the hazardous locations without the need for field visits. Many highways were built years before tools like geographic information systems (GIS) and other computer aided designs were available. Therefore, this method can be considered as a relevant aid for assessing geometric consistency of the I70 interstate highway and similar roads, because it identifies different segments of the road layout that offer considerably different sight distances.
Cite this paper
Abdulhafedh, A. (2019). An Innovative GIS Method for Evaluating the Visibility of the Road Using the ArcMap-Tools. Open Access Library Journal, 6, e5586. doi: http://dx.doi.org/10.4236/oalib.1105586.
American Association of State Highway and Transportation Officials (AASHTO) (2011) A Policy on Geometric Design of Highways and Streets. Washington DC.
Azimi, M. and Hawkins, H. (2013) Algorithm for Analyzing Horizontal Sight Distance from Lane Centerline Coordinates. Transportation Research Record: Journal of the Transportation Research Board, 2358, 12-19. https://doi.org/10.3141/2358-02
Ben-Arieh, D., Chang, S., Rys, M. and Zhang, G. (2004) Geometric Modeling of Highways Using Global Positioning System Data and B-Spline Approximation. Journal of Transportation Engineering, 130, 632-636. https://doi.org/10.1061/(ASCE)0733-947X(2004)130:5(632)
Cai, H. and Rasdorf, W. (2008) Modeling Road Centerlines and Predicting Lengths in 3-D Using LIDAR Point Cloud and Planimetric Road Centerline Data. Computer-Aided Civil and Infrastructure Engineering, 23, 157-173. https://doi.org/10.1111/j.1467-8667.2008.00518.x
Abdulhafedh, A. (2017) Identifying Vehicular Crash High Risk Locations along Highways via Spatial Autocorrelation Indices and Kernel Density Estimation. World Journal of Engineering and Technology, 5, 198-215. https://doi.org/10.4236/wjet.2017.52016
Castro, M., Iglesias, L., Rodríguez-Solano, R. and Sánchez, J.A. (2006) Geometric Modelling of Highways Using Global Positioning System (GPS) Data and Spline Approximation. Transportation Research Part C—Emerging Technologies, 14, 233-243. https://doi.org/10.1016/j.trc.2006.06.004
Imran, M., Hassan, Y. and Patterson, D. (2006) GPS-GIS-Based Procedure for Tracking Vehicle Path on Horizontal Alignments. Computer-Aided Civil and Infrastructure Engineering, 21, 383-394. https://doi.org/10.1111/j.1467-8667.2006.00444.x
Khattak, A.J. and Shamayleh, H. (2005) Highway Safety Assessment through Geographic Information System-Based Data Visualization. Journal of Computing in Civil Engineering, 19, 407-411. https://doi.org/10.1061/(ASCE)0887-3801(2005)19:4(407)
Kitzpatrick, K., Fambro, D.B. and Stoddard, A.M. (2000) Safety Effects of Limited Stopping Sight Distance on Crest Vertical Curves. Transportation Research Record: Journal of the Transportation Research Board, 1701, 17-24. https://doi.org/10.3141/1701-03
Abdulhafedh, A. (2017) A Novel Hybrid Method for Measuring the Spatial Autocorrelation of Vehicular Crashes: Combining Moran’s Index and Getis-Ord Gi Statistic. Open Journal of Civil Engineering, 7, 208-221. https://doi.org/10.4236/ojce.2017.72013
Nehate, G. and Rys, M. (2006) 3D Calculation of Stop-ping-Sight Distance from GPS Data. Journal of Transportation Engineering, 132, 691-698. https://doi.org/10.1061/(ASCE)0733-947X(2006)132:9(691)
Polus A., Livneh, M. and Frischer B. (2000) Evaluation of the Passing Process on Two-Lane Rural Highways. Transportation Research Record: Journal of the Transportation Research Board, 1701, 53-60. https://doi.org/10.3141/1701-07
Rose, E.R., Hawkins, H.G., Holick, A.J. and Bligh, R.P. (2004) Evaluation of Traffic Control Devices: First Year Activities. FHWA/TX-05-0-4701-1, Texas Transportation Institute.
Berbel, D.C., Castro, M., Medina. L.C. and Maria, S.P.G. (2014) Sight Distance Studies on Roads: Influence of Digital Elevation Models and Roadside Elements. Procedia—Social and Behavioral Sciences, 160, 449-458. https://doi.org/10.1016/j.sbspro.2014.12.157
Abdulhafedh, A. (2017) How to Detect and Remove Temporal Autocorrelation in Vehicular Crash Data. Journal of Transportation Technologies, 7, 133-147. https://doi.org/10.4236/jtts.2017.72010
Shaker, A., Yan, W.Y. and Easa, S. (2011) Construction of Digital 3D Highway Model Using Stereo IKONOS Satellite Imagery. Geocarto International, 26, 49-67. https://doi.org/10.1080/10106049.2010.537785
Tsai, Y., Hu, Z. and Wang, Z. (2010) Vision-Based Roadway Geometry Computation. Journal of Transportation Engineering, 136, 223-233. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000073