Algorithm for Determining Radius of Horizontal Curve
The radius of horizontal curve for the given road network is determined using an algorithm given in the flowchart. This algorithm is implemented in Visual C++. The algorithm is designed to determine the radius of simple circular curves and determines if the radius provided is greater than the minimum radius required.
Fig 1.2 Flowchart for Curvature Analysis GIS TechnologyA Geographic Information System (GIS) is a computer system for capturing, storing, querying, analyzing and displaying geographic data. GIS represents a new paradigm for the organization of the information and the design of information system, the essential aspect of which is the use of concept of location as the basis of structuring of information systems. GIS technology can be viewed as an offshoot from two major software technologies i.e., database management system (DBMS) and computer aided design (CAD), with the addition of specialized functions for managing and analyzing spatial data i.e., data that can be referenced to a geographical location. The objective of any GIS system is to capture, store, manage, analyze, and visualize geographical data.
GIS is a powerful computing tool for managing large amounts of heterogeneous data. A GIS can be effectively used to identify accident black spots on roads. The capability of GIS to link attribute data with spatial data facilitates prioritization of accident occurrence on roads and the results can be displayed graphically which can be used for planning and decision making. The process of rasterization, which involves conversion of vector data into raster data, helps in determining the suitability of horizontal curves provided on the roads. The results thus obtained can be combined using spatial and aspatial queries to obtain the desired results.
In the present study, GIS analysis is performed using ARCVIEW GIS 3.1 package. The road theme is classified for prioritization using classification theme mentioned in table 1.2. The results of Prioritization and Curvature Analysis are combined using a query which finds places on low accident prone level roads and having critical curve points. The results obtained are the required accident black spot locations
Case Study
The methodology developed for evaluating accident black spots on roads was applied for road network in BITS Pilani Campus. The results obtained are given below.
Fig 1.3 Road Network in BITS Pilani Campus
Fig 1.4 Location of Accident Black Spots ConclusionThe main advantage of using this approach for identifying accident black spots on roads is that it requires very less additional data other than the road network map. So the results obtained form this model can easily be used for planning road safety measures. Also these can be supplemented with the results obtained by using other approaches. Moreover the results can act as a quick guideline for road network planners and the authorities concerned with accident mitigation measures.
However the accuracy of this model highly depends on the way in which the road network is digitized. The road geometry can be inferred incorrectly if it is not properly digitized. Even the selection of proper resolution during rasterization and suitable check length for curvature analysis can affect the results.
References
- Khanna S.K., Justo C.E.G. "Highway Engineering", (1994), Nem Chand & Bros, Roorkee, 7th Edition.
- Environmental Systems Research Institute (ESRI) Inc. "ArcView GIS, version 3.1", 1996, New York Street, Redlands, California, USA.
- Baguley Chris, McDonald Mike, et al, "Towards Safer Roads in Developing Countries, A Guide for Planners and Engineers", Transport Research Laboratory, 1994, pp 1-60
- Kalga R.R, Silanda S.N, "Accident Rate Prediction on Arterial Roads of Durban, South Africa", Indian Highways Journal, July 2002.
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