Volume XL-1/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 487-492, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-487-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 487-492, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-487-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  29 Oct 2013

29 Oct 2013

Extraction of Accidents Prediction Maps Modeling Hot Spots in Geospatial Information System

R. Shad1, A. Mesgar2, and R. Moghimi2 R. Shad et al.
  • 1Rouzbeh Shad, Assistant professor, Civil Department, Ferdowsi University of Mashhad, Mashhad, Iran
  • 2Ali Mesgar, Dept. of Civil Engineering, Ferdowsi University of Mashhad (International Campus), Mashhad, Iran

Keywords: Geographic Information System, Spatial Distribution, Accident and Prediction

Abstract. In streets and intersections, identification of critical accident-prone points has an important role in using the acceptable model and method in order to decrease the probability of accident occurrence. for this purpose, deviate the factors affecting accidents and study each individually and collectively with the aid of the arithmetic operators is able to calculate and implement different extent of the effect and role of each of them. hence, different theoretical and practical solutions are provided in order to guarantee more safety and improve traffic conditions in transportation system, and the main factors affecting accidents in intersections are identified. so, in this paper, to help guarantee safety in mashhad transportation system, the capabilities of geographic information system are used in order to estimate and predict the probability of accident occurrence in intersections.

in this respect, the statistical data obtained from traffic observations and urban transport are gathered, and, by using arithmetic and statistical operators such as density estimation and interpolation methods, the data preparation processes are exercised in accordance with the needs and standards. then, with the aid of an integrated model of the probability of accident occurrence and considering experimental opinions of the experts, the probability of accident occurrence in intersections is identified and evaluated. finally, the results obtained are compared with the frequency of accidents recorded in the control points, and the model validity level is determined. these results can improve transportation system and provide desirable solutions for control, monitoring, and management of accidents.