Developing Information System on Blackspot Severity for Travellers by Using Python and Gis Techniques
Year: 2024
Type: article
Abstract: To reduce road traffic accidents, it is mandatory to identify and analyze road network blackspots with a high accident rate. This analysis aims to develop a framework to analyze the severity of blackspots for travelers using the Python programming language. The proposed study uses accident data to identify the black spots. Python programming language helps us perform geospatial-based analysis and data processing. It performs clustering of data spatially to identify the blackspots and statistics to calculate the severity and cause of accidents at these blackspot locations. The severity of each accident blackspot is calculated based on the frequency of accidents, injury severity, and volume of traffic at these locations. The analysis is performed using maps and provides information about the blackspots for the stretches of road networks i.e. Balampur Ghati to Chanchal Square, Golkhedhi Square to Chanchal Square, and Balampur Ghati to Police Control Room of Bhopal, Madhya Pradesh, India. By providing this information to the travelers this study ensures that the travelers choose the safest route possible.
Source: Archives for Technical Sciences
Authors: Nishant Singh, Sunil Kumar Katiyar
Institution: Maulana Azad National Institute of Technology
Language: English
Topic: Traffic and Road Safety
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405746312