Abstract
Vehicle accidents take human life all over the world particularly in developing countries like Pakistan. It is estimated that 1.2 million people lose their lives in road accidents every year. Apart from this, 20 to 50 million are injured on a yearly basis. This annual increase in the traffic accidents trend is alarming. To bring improvement in the current road network system, the specialists need to analyze the historical data of road crashes of an area. This research aims to use the visualization technique to have a better understanding of the accident data. This study uses the data of Peshawar, Pakistan, where the raw data were first organized, filtered, pre-processed and finally, visualization was performed to construct a systemic and homogenous data model. Various infographics were produced with the help of different software interface and visualization options. It was revealed that most of the accidents occur in the daytime and with those people who do not have enough traffic education. The 30 to 45 years age group was more active in causing the accidents. Therefore, the behaviour of this age group of drivers needs further investigation. This study will be useful for concerned authorities in devising an efficient mechanism to alleviate road accident cases.
Highlights
The presence of traffic is one of the unwanted gifts of urbanization [1,2,3]
The historical data of Road traffic accidents (RTAs) was collected for the Hayatabad area, which lies in the Peshawar region situated in the North West of Khyber Pakhtunkhwa province of Pakistan
The male drivers were mostly responsible for the injury accidents and it ranged to 431 injury accidents
Summary
Transportation is a type of infrastructure facility constructed by the government for its citizen for a quick and uninterrupted movement. It helps connect people, in commercial movements and ensures the ease of accessibility [4,5,6,7]. Failure to abide by road regulations and poor road conditions often result in crashes. The accident may occur due to many contributing factors, which depends on the time of the day, peak hour of the traffic, sex, age, geometric design of the road, type of vehicle, environmental conditions and vehicle occupancy [9,10,11]
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