Abstract:
India’s share of road accidents in the world is
an area of serious concern. Road traffic accidents have
been recognized as one of those adverse elements which
contribute to the suffocation of economic growth in the
developing countries, due to the heavy loss related to
them, hence causing social and economic concern. Traffic
safety is an important key and plays an integral role in
sustainable transportation development areas. Nowadays,
the main negative impact of modern road transportation
systems are loss of property injuries and deaths in road
accidents. The success of traffic safety and highway
improvement programs hinges on the analysis of accurate
and reliable traffic accident data. Thesis applied the
combination of geo-information technology and spatial statistical analysis to bring-out the influence of spatial
factors in their formation. With advancement in
technology, new and sophisticated models of vehicle are
available and their numbers are increasing day by day.
Development of a model for traffic accident density
estimation explained by GIS data can enable the
determination of dangerous areas objectively and easily,
indicating where area-wide traffic calming can be
implemented preferentially .A traffic accident has multi-facet characteristics associated with it. For proper traffic
accident analysis use of GIS technique has become an
inevitable tool. This Study examined the relations between
traffic accidents and city characteristics, such as
population, road factors, and spatial factors. A model was
developed to estimate traffic accident density. Kernel
density estimation (KDE) techniques were used to assess
the relations efficiently. In general, the location of traffic
accidents is described as an address with text, so they are
difficult to display on the map. Thesis concern with how
to utilize the GIS to work-out on Spatial Analyst to record
the traffic accidents. Thesis workout in presenting the
method which takes the potential of reducing accidents as
an index to extract the black spots
