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Distribution of Traffic Accident Times in India - Some Insights Using Circular Data Analysis


Affiliations
1 Indian Institute of Management, Ahmedabad, Gujarat, India
2 Saurashtra University, Rajkot, Gujarat, India
     

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Traffic accidents are a major hazard for travellers on Indian roads. These are caused by a variety of reasons including the bad condition of roads, traffic density, lack of proper training of drivers, slack in enforcement of traffic rules, poor road lighting etc. It is further known that certain times of the day are more prone to traffic accidents than others. In this paper we investigate the distribution of traffic accident times using the data published annually by the National Crime Records Bureau (NCRB) over the period 2001-2014 using the tools of circular data analysis. It is seen that the observed distribution of the traffic accident times in most years is bimodal. Thus, several modelling strategies for bimodal distributions are tried which include fitting of mixture of von-Mises distributions and mixture of Kato-Jones distribution. It is seen from this analysis that the distribution of the traffic accident times are changing over the years. Notably, the proportion of accidents happening in late night has reduced over the years while the same has increased for late evening hours. Some more insights obtained from this analysis are also discussed.

Keywords

Circular Statistics, Kato-Jones Distribution, Mixture Distribution, Traffic Accidents, Von-Mises Distribution.
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  • Distribution of Traffic Accident Times in India - Some Insights Using Circular Data Analysis

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Authors

Arnab Kumar Laha
Indian Institute of Management, Ahmedabad, Gujarat, India
A. C. Pravida Raja
Indian Institute of Management, Ahmedabad, Gujarat, India
Dilip Kumar Ghosh
Saurashtra University, Rajkot, Gujarat, India

Abstract


Traffic accidents are a major hazard for travellers on Indian roads. These are caused by a variety of reasons including the bad condition of roads, traffic density, lack of proper training of drivers, slack in enforcement of traffic rules, poor road lighting etc. It is further known that certain times of the day are more prone to traffic accidents than others. In this paper we investigate the distribution of traffic accident times using the data published annually by the National Crime Records Bureau (NCRB) over the period 2001-2014 using the tools of circular data analysis. It is seen that the observed distribution of the traffic accident times in most years is bimodal. Thus, several modelling strategies for bimodal distributions are tried which include fitting of mixture of von-Mises distributions and mixture of Kato-Jones distribution. It is seen from this analysis that the distribution of the traffic accident times are changing over the years. Notably, the proportion of accidents happening in late night has reduced over the years while the same has increased for late evening hours. Some more insights obtained from this analysis are also discussed.

Keywords


Circular Statistics, Kato-Jones Distribution, Mixture Distribution, Traffic Accidents, Von-Mises Distribution.

References